Time delay based health monitoring system using a sensor network

A method and apparatus for detecting an inconsistency in an object. Signals sent on a plurality of paths in the object are received at a plurality of transducer units associated with the object. Time delays are identified for a number of modes in the signals received at the plurality of transducer units. A determination is made as to whether a time delay in the time delays for the number of modes in the signals has a difference from a number of other time delays for the number of modes that is greater than a desired amount.

CROSS-REFERENCE TO RELATED APPLICATION

This application is related to the following patent application entitled: “Transducer Based Health Monitoring System”, Ser. No. 13/083,957; filed even date hereof, assigned to the same assignee, and incorporated herein by reference.

BACKGROUND INFORMATION

The present disclosure relates generally to monitoring aircraft structures and, in particular, to monitoring aircraft structures for inconsistencies. Still more particularly, the present disclosure relates to a method and apparatus for detecting inconsistencies in aircraft structures using signals sent through the aircraft structures.

Composite and metallic aircraft structures may be susceptible to internal changes that may occur from fatigue, impacts, and/or other events or conditions. Composite materials typically have a minimal visual indication of these types of changes. As a result, an aircraft may be inspected to assess the integrity of the structure on a periodic basis, or after visual indications of surface inconsistencies, such as a dent or a scratch.

For example, impacts to a structure, such as an aircraft, may occur during cargo loading and unloading. Inspections of the structure of an aircraft may be time consuming and costly in terms of the time and skill needed to perform the inspection. Further, an airline may incur a loss of revenue from the aircraft being out of service.

Structural health monitoring techniques have been developed and used to monitor materials and structures. These techniques often build the health monitoring systems into the structures. These health monitoring systems may be used to determine whether changes have occurred to these materials and structures over time.

Sudden changes in environments, such as electromagnetic effects, mechanical stresses, and other environmental effects may affect various materials and structures over time. By having health monitoring systems built into or associated with the structures to monitor the structures during use, appropriate measures and responses may be taken to prevent inconsistencies and may prolong the life span of these structures.

The monitoring of these structures may include various non-destructive elevation methods, such as ultrasonic testing or x-ray testing. Ultrasonic testing uses contact-based transducers to mechanically scan a structure. These sensors and actuators may be surface-mounted on the structure or may be embedded in the structure to generate and propagate signals into the structure being monitored.

A structural health monitoring system uses transducers to transmit waveforms at various frequency ranges and acquire data from the responses. Although structural health monitoring systems may provide an automated onboard system for detecting and characterizing inconsistencies or changes that may require maintenance, these types of systems may require updates and adjustments when maintenance, modifications, and reconfigurations of an aircraft occur.

For example, if a skin panel is changed, if a landing gear is modified, or if other changes occur, additional transducers may need to be moved or configured for use with the replaced or new components. These and other types of updates to the structural health monitoring system are time-consuming and expensive. The time needed to update the health monitoring system may make the aircraft unavailable for use longer than desired.

Therefore, it would be advantageous to have a method and apparatus that takes into account at least some of the issues discussed above, as well as possibly other issues.

SUMMARY

In one advantageous embodiment, a method for detecting an inconsistency in an object is provided. Signals sent on a plurality of paths in the object are received at a plurality of transducer units associated with the object. Time delays are identified for a number of modes in the signals received at the plurality of transducer units. A determination is made as to whether a time delay in the time delays for the number of modes in the signals has a difference from a number of other time delays for the number of modes that is greater than a desired amount.

In another advantageous embodiment, an apparatus comprises a signal analysis module. The signal analysis module is configured to identify time delays for a number of modes in signals received at a plurality of transducer units. The signals are received on a plurality of paths in an object in which the plurality of transducer units is associated with the object. The signal analysis module is configured to determine whether a time delay in the time delays for the number of modes in the signals has a difference from a number of other time delays in the time delays for the number of modes in the signals that is greater than a desired amount.

In yet another advantageous embodiment, a health monitoring system of an aircraft comprises a transducer system and a signal analysis module. The transducer system is associated with a number of structures in the aircraft. The signal analysis module is configured to cause a first plurality of transducer units associated with the number of structures in the aircraft to send signals on a plurality of paths in an object. The signal analysis module is configured to identify time delays for asymmetric modes in the signals received by a second plurality of transducer units in the transducer system. The signal analysis module is configured to determine whether a time delay in the time delays for the asymmetric modes in the signals has a difference from a number of other time delays for the asymmetric modes that is greater than a desired amount.

DETAILED DESCRIPTION

Referring more particularly to the drawings, advantageous embodiments of the disclosure may be described in the context of aircraft manufacturing and service method100as shown inFIG. 1and aircraft200as shown inFIG. 2. Turning first toFIG. 1, an illustration of an aircraft manufacturing and service method is depicted in accordance with an advantageous embodiment. During pre-production, aircraft manufacturing and service method100may include specification and design102of aircraft200inFIG. 2and material procurement104.

During production, component and subassembly manufacturing106and system integration108of aircraft200inFIG. 2takes place. Thereafter, aircraft200inFIG. 2may go through certification and delivery110in order to be placed in service112. While in service112by a customer, aircraft200inFIG. 2is scheduled for routine maintenance and service114, which may include modification, reconfiguration, refurbishment, and other maintenance or service.

With reference now toFIG. 2, an illustration of an aircraft is depicted in which an advantageous embodiment may be implemented. In this illustrative example, aircraft200is produced by aircraft manufacturing and service method100inFIG. 1and may include airframe202with plurality of systems204and interior206. Examples of plurality of systems204include one or more of propulsion system208, electrical system210, hydraulic system212, environmental system214, and health monitoring system216. Any number of other systems may be included. Although an aerospace example is shown, different advantageous embodiments may be applied to other industries, such as the automotive industry.

Apparatuses and methods embodied herein may be employed during at least one of the stages of aircraft manufacturing and service method100inFIG. 1. As used herein, the phrase “at least one of”, when used with a list of items, means that different combinations of one or more of the listed items may be used and only one of each item in the list may be needed. For example, “at least one of item A, item B, and item C” may include, for example, without limitation, item A or item A and item B. This example may also include item A, item B, and item C or item B and item C.

In one illustrative example, components or subassemblies produced in component and subassembly manufacturing106inFIG. 1for health monitoring system216may be fabricated or manufactured in a manner similar to components or subassemblies produced for health monitoring system216while aircraft200is in service112inFIG. 1. As yet another example, a number of apparatus embodiments, method embodiments, or a combination thereof may be utilized during production stages, such as component and subassembly manufacturing106and system integration108inFIG. 1. A “number”, when referring to items, means “one or more items.” For example, a number of apparatus embodiments is one or more apparatus embodiments. A number of apparatus embodiments, method embodiments, or a combination thereof may be utilized while aircraft200is in service112and/or during maintenance and service114inFIG. 1. The use of a number of the different advantageous embodiments may substantially expedite the assembly of and/or reduce the cost of aircraft200.

The different advantageous embodiments recognize and take into account a number of different considerations. For example, the different advantageous embodiments recognize and take into account that many currently used health monitoring systems that use baseline data may have a higher rate of false positive indications of inconsistencies than desired. These false indications may occur from different environmental and operational variations.

For example, the different advantageous embodiments recognize and take into account that many currently used health monitoring systems rely on baseline data. Baseline data is data generated from sending signals through structures in the aircraft during a time at which the structures are considered to have no inconsistencies.

The different advantageous embodiments recognize and take into account that this baseline data is typically generated under conditions that may vary from those present during operating conditions. For example, the data may be generated using the temperature, pressure, and other environmental factors that are present, while the aircraft or parts are on the ground or not installed. These parameters may change when the aircraft is operating. The parameters may also change between various phases of flight such as taxiing, takeoff, en route, landing, and other phases. Temperature, pressure, and other changes in the environment around an aircraft during operation of the aircraft may result in false indications of the presence of inconsistencies when compared to baseline data taken during generation of the baseline data when the aircraft is not in operation.

The different advantageous embodiments recognize and take into account that currently used health monitoring systems may attempt to compensate for changes in the environment. The different advantageous embodiments recognize and take into account that currently used systems may attempt to obtain data for the structures without inconsistencies under the different operating conditions that may occur to take into account changes that may occur in the environment. This information may then be used as a comparison to data generated during the operation of the aircraft to determine whether inconsistencies are present.

The different advantageous embodiments recognize and take into account, however, that this type of compensation for operating conditions may require recording more data than desired. The amount of data obtained for different environmental conditions may use more storage space than desirable in a health monitoring system. Further, the different advantageous embodiments also recognize and take into account that it may not be possible to record data from all possible types of operating conditions that may be encountered during the operation of the aircraft.

The different advantageous embodiments also recognize and take into account that this type of health monitoring system may also require re-recording of data when sensors are replaced. The different advantageous embodiments recognize and take into account that it would be desirable to detect inconsistencies without requiring the use of baseline data.

Thus, the different advantageous embodiments provide a method and apparatus for detecting inconsistencies in an object. In one advantageous embodiment, signals sent on a plurality of paths in the object are received at a plurality of transducer units associated with the object. Time delays are identified for a number of modes in the signals received at the plurality of transducer units. A determination is made as to whether a time delay in the time delays for the number of modes in the signals has a difference from a number of other time delays for the number of modes that is greater than a desired amount.

With reference now toFIG. 3, an illustration of a health monitoring environment is depicted in accordance with an advantageous embodiment. Health monitoring environment300is an example of an environment that may be implemented in aircraft200inFIG. 2. As depicted, health monitoring environment300includes object302and health monitoring system304in this illustrative example.

In this illustrative example, object302is an example of an object that may be monitored using health monitoring system304. In this illustrative example, object302may take various forms. In this example, object302takes the form of aircraft200or a structure or system within aircraft200inFIG. 2.

Health monitoring system304is associated with object302. A first component may be considered to be associated with a second component by being secured to the second component, bonded to the second component, fastened to the second component, and/or connected to the second component in some other suitable manner. The first component may also be connected to the second component using a third component. The first component may also be considered to be associated with the second component by being formed as part of and/or an extension of the second component.

In these depicted examples, health monitoring system304is configured to detect a presence of inconsistency306in object302. Inconsistency306may be any element or portion of object302that does not have a desired or expected state. Inconsistency306may be, for example, at least one of a delamination, a number of voids, and/or some other suitable type of inconsistency.

As depicted, health monitoring system304comprises transducer system308and signal analysis module310. Transducer system308comprises group of transducer units312. A transducer unit within group of transducer units312may function as a transmitter, a sensor, or both a transmitter and a sensor, depending on the particular implementation.

In these illustrative examples, group of transducer units312may be divided into first plurality of transducer units316and second plurality of transducer units318. First plurality of transducer units316may be configured to function as transmitters321. Second plurality of transducer units318may be configured to function as sensors322.

Each transducer unit in group of transducer units312may include one or more transducers depending on the particular implementation. Transducers within group of transducer units312may be implemented using any known transducer configured to generate signals that may be sent through object302. Additionally, transducers within group of transducer units312may also include transducers configured to receive signals324sent through object302.

In these illustrative examples, transducer system308is connected to signal analysis module310. Signal analysis module310is configured to control transducer system308in monitoring or testing object302for inconsistency306.

In these illustrative examples, signal analysis module310is comprised of hardware, software, or a combination of the two. For example, signal analysis module310may be comprised of number of computers314with software315.

Signal analysis module310is configured to cause first plurality of transducer units316to send signals324on plurality of paths326. Signals324travel on path320to second plurality of transducer units318in these depicted examples. In these illustrative examples, plurality of paths326have same direction328. Although plurality of paths326may have same direction328, lengths330for paths within plurality of paths326may be different.

In particular, in these illustrative examples, plurality of paths326have same direction328when object302comprises composite materials. Composite materials, particularly in aircraft structures, generally have directionality of wave propagation. In other words, different wave speeds occur depending on the direction of the wave propagation.

For composite materials, when plurality of paths326do not have same direction328, the arrival time of number of modes340may be unmated even if inconsistency306is not present in object302. Of course, in other illustrative examples, plurality of paths326may have different directions.

Signals324travel from first plurality of transducer units316to second plurality of transducer units318in times332. Times332are identified by signal analysis module310. Times332may also be referred to as times of flight or times of travel.

Additionally, signals324have plurality of modes334. In other words, each signal in signals324has plurality of modes334. A mode, as used herein, is a component of a waveform that makes up a signal in signals324. A mode is one type of physical propagation of waveforms in these illustrative examples.

In these illustrative examples, different modes within plurality of modes334for each signal of signals324may arrive at a sensor within second plurality of transducer units318at different times within times332. These times are also referred to as time delays336.

In these illustrative examples, signal analysis module310identifies time delays338for number of modes340in plurality of modes334for signals324received by second plurality of transducer units318in group of transducer units312. In these illustrative examples, one mode is selected for number of modes340. In other illustrative examples, additional modes may also be identified. Each time delay for a particular mode in number of modes340is identified for a particular path in plurality of paths326.

Time delays338may be identified by signal analysis module310in the form of velocities342. In other words, a velocity within velocities342is present for each mode in number of modes340for a particular path in plurality of paths326. For example, a velocity is present in velocities342for each path in plurality of paths326for a particular mode in number of modes340along that path.

In these illustrative examples, time delays338may be measured using velocities342. For example, when a signal in signals324is detected at second plurality of transducer units318, signal analysis module310identifies the velocity for a mode in number of modes340for the signal at the time of detection. A slower velocity for the mode for the signal as compared to the velocities for the same mode in other signals in signals324may indicate that inconsistency306was encountered along the path in plurality of paths326for the signal. In this manner, a slower velocity for the signal indicates a time delay for the mode that may be caused by inconsistency306. The velocity along with a length of the path may be used to calculate the time delay.

In this manner, lengths330for plurality of paths326may be different. As a result, normalizing for actual time in time delays338may be unnecessary when velocities342are used to represent time delays338. A velocity within velocities342that varies from other velocities represents a difference in time delay as compared to the other velocities.

In these illustrative examples, signal analysis module310is configured to determine whether time delay344in time delays338has difference346from other time delays348in time delays338that is greater than desired amount350. Time delay344is for a particular mode in number of modes340for a particular path associated with time delay344. In other words, difference346may be greater than other time delays348and time delays338for number of modes340when inconsistency306is present along the path associated with time delay344.

Signal analysis module310generates alert352if difference346of time delay344is greater than desired amount350. Alert352is an indication that inconsistency306is present in object302. In these illustrative examples, alert352may be a signal, a message, or some other suitable type of alert. Alert352may include other information. For example, alert352may include the particular path, the transmitting and receiving transducer, the time at which the inconsistency was detected, operating conditions, state of the aircraft, and other suitable information.

In some illustrative examples, time delays338for number of modes340may be identified without using velocities342. For example, time delays338for number of modes340for signals324may be identified by normalizing lengths330for plurality of paths326along which signals324travel from first plurality of transducer units316to second plurality of transducer units318. These normalized lengths may then be used to identify time delays338.

Thus, the different advantageous embodiments in health monitoring environment300identify a presence of inconsistency306without needing or using baseline data.

For example, although object302has been described with respect to an aircraft, object302may take other forms. For example, object302may be selected from one of a mobile platform, a stationary platform, a land-based structure, an aquatic-based structure, a space-based structure, an aircraft, a surface ship, a tank, a personnel carrier, a train, a spacecraft, a space station, a satellite, a submarine, an automobile, a power plant, a bridge, a dam, a manufacturing facility, a building, a skin panel, an engine, a fuselage, a wing, a rib, and a stringer.

In yet other illustrative examples, additional signal analysis modules in addition to signal analysis module310may be present to provide for more coverage of object302, redundancy, or for some other suitable purpose. Further, health monitoring system304may be embedded or built into object302in some illustrative examples. In other illustrative examples, health monitoring system304may be connected to or attached to object302for monitoring object302for a period of time and then removed or detached from object302.

Additionally, although the different advantageous embodiments have been described for an object comprising composite materials, objects comprising other types of materials may also be tested using health monitoring system304.

For example, object302may comprise materials such as, without limitation, steel, titanium, aluminum, a metal alloy, and/or other suitable types of materials. When object302is comprised of materials other than composite materials, paths in plurality of paths326may not all have same direction328. In other words, paths in plurality of paths326may have different directions.

With reference now toFIG. 4, an illustration of a signal analysis module is depicted in accordance with an advantageous embodiment. Signal analysis module400is an example of one implementation for signal analysis module310inFIG. 3.

In this illustrative example, signal analysis module400includes mode selection unit402, time delay identification unit404, and classification unit406. These different units may be implemented in hardware, software, or a combination of the two. As one illustrative example, these units may be implemented within program code410running on number of computers412.

In this depicted example, signal generation unit408is configured to cause transducer units414to generate signals416that travel on plurality of paths418and are then detected by transducer units420. Transducer units414function as transmitters422, while transducer units420function as sensors424.

In these illustrative examples, signals416take the form of Lamb waves426. Lamb waves426are waves that propagate in solid media. For example, Lamb waves426may propagate within the thickness of an object, such as a plate, or other type of object. Signal425in signals416has modes428. Modes428include asymmetric modes430and symmetric modes434.

In these illustrative examples, asymmetric modes430may be affected more by certain types of inconsistencies in an object as compared to symmetric modes434. In particular, asymmetric modes430may be affected more by inconsistencies in the form of delaminations as compared to symmetric modes434.

In these illustrative examples, mode selection unit402identifies number of modes436in modes428for use in determining whether an inconsistency is present. In the depicted examples, number of modes436takes the form of asymmetric mode437in asymmetric modes430. Of course, in other examples, additional asymmetric modes may be selected in addition to asymmetric mode437depending on the particular implementation.

With delamination of composite materials, an asymmetric mode in signals416is affected more than a symmetric mode in symmetric modes434. Of course, for other types of materials, other modes may be selected in modes428.

Number of modes436is selected as modes that may provide a greatest desired ability to identify inconsistencies in the object.

In these illustrative examples, this identification of number of modes436is performed for each signal in signals416. After asymmetric mode437has been selected for signal425and the same asymmetric mode is selected for other signals in signals416, time delays438in the form of velocities440are identified by time delay identification unit404. In these illustrative examples, time delays438are used by classification unit406to generate index values442. Index values442are used by classification unit406to determine whether an inconsistency is present along one of plurality of paths418.

If any of index values442are greater than threshold444, alert446is generated by classification unit406to indicate the presence of an inconsistency. In these illustrative examples, threshold444may be selected as a value that indicates that an inconsistency is present. An index value in index values442that is greater than threshold444may be considered an outlier. The selection of threshold444and index values442may be performed using various known statistical analysis techniques.

The illustration of signal analysis module400inFIG. 4is not meant to imply physical or architectural limitations to the manner in which signal analysis module310inFIG. 3may be implemented. In other illustrative examples, the different units may be implemented as a single unit, or other subdivisions may be made depending on the particular implementation.

With reference now toFIG. 5, an illustration of a transducer system is depicted in accordance with an advantageous embodiment. In this illustrative example, transducer system500is an example of one implementation of transducer system308inFIG. 3. In this illustrative example, transducer units502,504,506,508,510, and512are associated with skin panel514. Skin panel514is a composite skin panel with composite layers in these illustrative examples. Skin panel514is an example of one implementation for object302or a portion of object302inFIG. 3.

As depicted, transducer units502,504, and506function as transmitters, while transducer units508,510, and512function as sensors. In these illustrative examples, transducer unit502and transducer unit508form path516, transducer unit504and transducer unit510form path518, and transducer unit506and transducer unit512form path520. As can be seen in these illustrative examples, path516, path518, and path520extend in the direction of arrow522. All of these paths have the same direction.

Although the paths are illustrated as having the same length, these paths may have different lengths depending on the particular implementation. Also, in other tests, transducer units502,504, and506may become sensors while transducer units508,510, and512become transmitters. In this case, the paths formed between the transducer units have a direction that is in the opposite direction of arrow522. Of course, paths may be generated by other combinations of transducer units in these examples, having the same direction.

In this illustrative example, inconsistency524is present along path520. Inconsistency524takes the form of a delamination of layers within skin panel514.

Inconsistency524results in a time delay for signals sent along path520being greater than those sent along paths516and518. As a result, the velocity of a signal sent along path520will be less than the velocities of signals sent along paths516and518. This difference in velocities is used to identify the presence of inconsistency524.

With reference now toFIG. 6, an illustration of graphs identifying a time delay for a signal due to a presence of an inconsistency is depicted in accordance with an advantageous embodiment. Asymmetric mode waveforms600,601, and602may be waveforms extracted from signals transmitted and received by transducer units.

In this illustrative example, asymmetric mode waveform600is the asymmetric mode extracted from a signal transmitted by transducer unit502along path516inFIG. 5. Asymmetric mode waveform601is the asymmetric mode extracted from a signal transmitted by transducer unit504along path518inFIG. 5. Asymmetric mode waveform602is the asymmetric mode extracted from a signal transmitted by transducer unit506along path520inFIG. 5.

As illustrated, asymmetric mode waveforms600,601, and602are transmitted at substantially the same time. In particular, asymmetric mode waveforms600,601, and602are transmitted at initial transmission time604in this example.

Time606is the time it takes for asymmetric mode waveform600to reach transducer unit508along path516inFIG. 5. Time608is the time it takes for asymmetric mode waveform601to reach transducer unit510along path518inFIG. 5. Time610is the time it takes for asymmetric mode waveform602to reach transducer unit512along path520inFIG. 5. Times606,608, and610may also be referred to as times of flight for asymmetric mode waveforms600,601, and602, respectively.

Time delay612is the difference between time610and time608. Time delay612is the same difference between time610and time606. With paths516,518, and520having substantially the same length, the presence of time delay612indicates that inconsistency524is present along path520. In other words, when one of times606,608, and610is not substantially the same as the other times, an inconsistency is present along the corresponding path in skin panel514. When times606,608, and610are substantially the same, an inconsistency is not present along the corresponding paths.

In this manner, the identification of inconsistencies does not require the use of prior baseline data. Further, this process may be performed to identify inconsistencies even under changing operational and environmental conditions of the object.

With reference now toFIGS. 7-10, examples of transducer units are depicted in accordance with an advantageous embodiment. InFIG. 7, an illustration of three transducers for a transducer unit is depicted in accordance with an advantageous embodiment. In this illustrative example, transducer unit700is shown in a top view and a side view. Transducer unit700comprises transducer702,704, and706. As can be seen, transducer unit700is symmetric along axis708.

InFIG. 8, an illustration of a two-segment transducer unit is depicted in accordance with an advantageous embodiment. In this illustrative example, transducer unit800comprises segment802and segment804. Transducer unit800is symmetric about axis806.

With reference now toFIG. 9, an illustration of a ring-based transducer is depicted in accordance with an advantageous embodiment. In this illustrative example, transducer unit900comprises segment902and segment904. Segment902is a ring segment. Segment904is a circular segment. Transducer unit900is symmetric about axis906in these examples.

With reference now toFIG. 10, an illustration of a ring transducer unit is depicted in accordance with an advantageous embodiment. In this illustrative example, transducer unit1000comprises segment1002and segment1004. Segment1002is a ring segment. Segment1004is a circular segment. Transducer unit1000is symmetric about axis1006in these illustrative examples.

With reference now toFIG. 11, an illustration of signals detected by two different segments of a transducer unit is depicted in accordance with an advantageous embodiment. In this illustrative example, transducer unit1100functions as a transmitter, while transducer unit1102functions as a sensor. Transducer unit1100has ring segment1104and circular segment1106, while transducer unit1102has ring segment1108and circular segment1110.

As depicted in this illustrative example, path1112is formed between transducer unit1100and transducer unit1102. Activation of different segments for the transducer units allows four different Lamb wave signals to be obtained.

In this illustrative example, the modes for signal1114and signal1116may have substantially identical arrival times at ring segment1108and circular segment1110, respectively, but different amplitudes. Further, the amplitudes of the symmetric (S0) modes and the asymmetric (A0) modes change at different rates as the size of the segment in the transmitting transducer unit that transmits the signal and the size of the segment in the sensing transducer unit that detects the signal changes.

In other words, the amplitudes of the symmetric modes and the asymmetric modes change depending on which segment is activated to transmit in transducer unit1100and which segment is activated to detect in transducer unit1102.

Additionally, the rate at which the amplitude of each mode in the modes for the signal changes, with respect to the size of the particular segments in the transducer units, is not based on the distance between transducer unit1100and transducer unit1102.

Signal1114and signal1116may be used by, for example, signal analysis module400inFIG. 4to identify a number of modes for which time delays may be identified. For example, signal1114and signal1116may be measured at ring segment1108and circular segment1110for transducer unit1102. The amplitudes of the symmetric modes in signal1114and signal1116are normalized such that the amplitudes of the symmetric modes are substantially equal.

The symmetric modes may then be removed by subtracting signal1114, Vrr, from signal1116, Vrc. In other words, the symmetric modes are subtracted from each other such that only the asymmetric mode remains. The asymmetric mode waveform formed by this subtraction does not preserve amplitude information. However, this signal does retain arrival time information for the asymmetric mode. In this manner, time delay information may be identified using the asymmetric mode waveform.

However, the asymmetric mode waveform contains information for the time of travel between transducer unit1100and transducer unit1102. In this manner, time delay information may be identified using the asymmetric mode waveform.

With reference now toFIG. 12, an illustration of a flowchart of a process for detecting an inconsistency in an object is depicted in accordance with an advantageous embodiment. The process illustrated inFIG. 12may be implemented in health monitoring environment300inFIG. 3. In particular, this process may be implemented within signal analysis module310inFIG. 3.

The process begins by sending signals on a plurality of paths in an object using a first plurality of transducer units (operation1200). This first plurality of transducer units functions as transmitters. Signals are received at a second plurality of transducers associated with the object (operation1202). The second plurality of transducer units functions as sensors.

The process then identifies time delays for a number of modes in the signals received by the second plurality of transducer units (operation1204). In this illustrative example, the number of modes includes one type of mode. The process then selects a time delay that has not yet been processed from the identified time delays (operation1206). A determination is then made as to whether a time delay in the time delays for the number of modes in the signals has a difference from the other time delays for the number of modes that is greater than a desired amount (operation1208).

If the time delay for the number of modes has a difference from the other time delays for the number of modes that is greater than the desired amount, the process generates an alert (operation1210) and terminates thereafter.

With reference again to operation1208, if the time delay for the number of modes has a difference from the other time delays for the number of modes that is not greater than the desired amount, a determination is made as to whether additional time delays are present that have not yet been processed (operation1212). If additional time delays are not present, the process terminates. Otherwise, the process returns to operation1206to select another time delay that has not yet been processed from the identified time delays.

With reference now toFIG. 13, a flowchart of a process for selecting modes in signals received at transducers is depicted in accordance with an advantageous embodiment. The process illustrated inFIG. 13may be implemented in signal analysis module400and, in particular, within mode selection unit402in signal analysis module400inFIG. 4.

The process begins by identifying a group of paths having a substantially equal spacing and a same direction in an object (operation1300). In operation1300, the object may be, for example, a composite skin panel. The object may have a number of inconsistencies in the object.

The paths are formed by transducer units placed on or in the object. In particular, the paths are formed along the distances between pairs of transducer units. For example, a signal transmitted by a transducer unit functioning as a transmitter travels along a path to a transducer unit functioning as a sensor. The transducer unit functioning as the sensor detects and measures the signal.

In this illustrative example, the transducer units may be any of a number of different forms having a number of segments. In one illustrative example, the transducer units take the form of, for example, transducer unit800inFIG. 8, transducer unit900inFIG. 9, transducer unit1100inFIG. 11, and/or transducer unit1102inFIG. 11. In other words, each of the transducer units forming the paths identified may have a ring segment and a circular segment. Of course, in other illustrative examples, other types of transducer units having segments with other types of shapes may be used.

The process selects a path from the identified group of paths for processing (operation1302). The process then identifies a first signal detected by a first segment of the sensing transducer unit (operation1304). The first segment may be a ring segment. The process identifies a second signal detected by a second segment of the sensing transducer unit (operation1306). The second segment may be a circular segment. In this illustrative example, the first signal and the second signal may be detected by the first segment and the second segment, respectively, at substantially the same time.

Thereafter, the process normalizes the amplitudes for the symmetric modes of the first signal and the second signal such that the normalized amplitudes for the symmetric modes are substantially equal (operation1308). The process then subtracts the first signal from the second signal to form a new signal (operation1310).

Next, the new signal is processed to extract an asymmetric mode waveform for the path (operation1312). The asymmetric mode waveform contains information about the amount of time the first signal and the second signal take traveling along the path from the transmitting transducer unit to the sensing transducer unit.

The process then determines whether any additional unprocessed paths are present in the group of paths identified (operation1314). If additional unprocessed paths are not present, the process terminates. Otherwise, the process returns to operation1302as described above.

The process illustrated inFIG. 13may be performed for each group of paths that are substantially equally spaced and have a same direction.

With reference now toFIG. 14, an illustration of a classification process for paths is depicted in accordance with an advantageous embodiment. The process illustrated inFIG. 14may be implemented in classification unit406in signal analysis module400inFIG. 4. Further, this process may be implemented after the process illustrated inFIG. 13.

The process begins by calculating an index value for each path in a group of paths (operation1400). In operation1400, the group of paths is the group of paths identified in operation1300inFIG. 13.

The index value is calculated to identify the time delay for the asymmetric mode identified for each path. The index value is calculated based on an assumption that more than half of the paths in the group of paths are along portions of the object without inconsistencies.

The index value may be calculated using the following equations:

DI⁡(i,Ω)=12⁢(1-2nd⁢∑jnd/2⁢corr⁡(A0⁡(i,Ω),A0⁡(j,Ω)))DI⁡(i)=1N⁢∑ΩN⁢DI⁡(I,Ω).
where DI is the index value, i is an identifier for a particular path, Ω is an input frequency, d is an identifier for the group of paths, ndis the number of paths in a group of paths, corr is the cross-correlation function, j is the identifier for a path along which an inconsistency is not present, A0is the asymmetric mode, and A0(i, Ω) and A0(j, Ω) are the first arrival asymmetric modes at the input frequency Ω in the i and j paths, respectively. The j paths are selected as the half of the asymmetrical modes that are the fastest asymmetrical modes in the group of paths d.

In these illustrative examples, the first arrival asymmetric mode or the first arrival A0mode is a first asymmetric mode that arrives at the sensor. For example, the signals received at a sensor often include multiple modes. These modes may be, for example, directly propagated waves from a transmitter and a sensor, reflections from the structural boundary of the object, and/or from other types of sources. If an inconsistency is present between the sensor and the transmitter, only the first arrival A0mode is affected.

The index value DI indicates how much a signal traveling along a particular path is delayed as compared with other paths along which inconsistencies are not present.

The index value DI is normalized to have a range between 0 and 1 by subtracting the cross-correlation values from one and dividing it by 2. If the asymmetric mode obtained for a particular path has a similar arrival time with the asymmetric modes obtained for other paths along which inconsistencies are assumed to not be present, the index value approaches 0. Otherwise, if the asymmetric mode is delayed, the corresponding index value approaches 1.

Thereafter, the process arranges all of the index values calculated in an ascending order (operation1402). In the ascending order, the first index value is the smallest index value and the Nthindex value is the largest index value. The Nthindex value is the last index value. In this illustrative example, N is the total number of index values. Further, each index value is for a particular path. In this manner, N is the total number of paths.

Next, the process selects a first nthsmallest index value for analysis (operation1403). In this example, n is an identifier for a particular index value in the group of index values. In operation1403, the first index value may be selected as about half of the total number of paths. For example, if 20 paths are in the group of paths, the first n is selected as 10. In this manner, the 10thsmallest index value is selected as the first index value for analysis.

The process then fits a parametric distribution function to the n−1 smallest index value (operation1404). For example, in operation1404, when the 10thindex value is selected, a parametric distribution function is fitted to the nine smallest index values in the group of index values.

A truncated exponential distribution is used for the parametric distribution function in this illustrative example. This distribution is bounded because the index values have the upper limit of 1 and the lower limit of 0. A truncated exponential distribution with parameter c has the following probability density function:
f(x)=ce−cx(1−e−c)−1,(0<x≦1).
where f(x) is the probability density function, e is the exponential function, and x is the index value. Further, the maximum likelihood estimator of c is denoted as cb. The maximum likelihood estimator cbcan estimate a parameter of c of the best-fit truncated exponential distribution of x as follows:

x_
is the mean of x.

The process then identifies a threshold value for the nthindex value (operation1406). In operation1406, the threshold value is identified based on fitting the parametric distribution function to the n−1 smallest index values in operation1404and a specific confidence level. This confidence level may be set by user input.

Next, the process determines whether the value of the nthsmallest index value is greater than the threshold value (operation1408). If the value of the nthsmallest index value is not greater than the threshold value, the process determines whether n is equal to the total number of index values, N (operation1410). If n is not equal to the total number of index values, N, the process increments n (operation1412). Then the process returns to operation1404as described above.

With reference again to operation1410, if n is equal to the total number of index values, N, the process terminates. Further, with reference again to operation1408, if the value of the nthsmallest index value is greater than the threshold value, the process identifies the paths associated with the nth, n+1th, . . . Nthindex values as having inconsistencies along the paths (operation1414), with the process terminating thereafter.

The flowcharts and block diagrams in the different depicted embodiments illustrate the architecture, functionality, and operation of some possible implementations of apparatus and methods in different advantageous embodiments. In this regard, each block in the flowchart or block diagrams may represent a module, segment, function, and/or a portion of an operation or step. For example, one or more of the blocks may be implemented as program code, in hardware, or a combination of the program code and hardware. When implemented in hardware, the hardware may, for example, take the form of integrated circuits that are manufactured or configured to perform one or more operations in the flowcharts or block diagrams.

In some alternative implementations, the function or functions noted in the block may occur out of the order noted in the figures. For example, in some cases, two blocks shown in succession may be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. Also, other blocks may be added in addition to the illustrated blocks in a flowchart or block diagram.

With reference now toFIG. 15, an illustration of a top view of an experimental setup on a portion of an object for testing for inconsistencies in the object is depicted in accordance with an advantageous embodiment. In this illustrative example, object1500is an example of object302inFIG. 3that may be tested for inconsistencies. Object1500is a composite skin panel in this illustrative example. In particular, object1500is a carbon fiber composite skin panel.

As depicted, transducer units1502,1504,1506,1508,1510,1512,1514,1516, and1518are placed on object1500. These transducer units take the form of piezoelectric transducer (PZT) units. These transducer units are installed on surface1515of object1500in a square grid pattern having a spacing of about 15 centimeters.

In this illustrative example, transducer units1502,1504,1506,1508,1510,1512,1514,1516, and1518are arranged with substantially equal spacing. However, in other examples, these transducer units may have different distances from each other.

As depicted, various groups of paths may be formed by these transducer units. For example, groups1520,1522,1524, and1526may be formed by the transducer units. In this illustrative example, each group only includes paths that are substantially equally spaced from other paths in the group and paths that have the same direction. Each group includes five paths. In this manner, a total number of 20 paths are formed by the transducer units.

Further, as depicted, object1500may have inconsistencies1528,1530, and1532. Each of these inconsistencies may be, for example, a delamination of the composite skin panel. These inconsistencies may be located along some of the paths formed by the transducer units. For example, inconsistency1528is present along path1534in group1520. These inconsistencies may be caused by undesired temperatures for object1500.

With reference now toFIG. 16, an illustration of a portion of a health monitoring system is depicted in accordance with an advantageous embodiment. In this illustrative example, health monitoring system1600is an example of one implementation for health monitoring system304inFIG. 3. Only a portion of health monitoring system1600is depicted in this illustrative example. Health monitoring system1600includes transducer units1502,1504,1506,1508,1510,1512,1514,1516, and1518inFIG. 15, but are not shown in this view.

As depicted, health monitoring system1600includes arbitrary waveform generator1602, high speed signals digitizer1604, low noise preamplifier1606, power amplifier1608, multiplexers1610, and controller1612. These components are used to generate signals that are transmitted in object1500inFIG. 15by a first portion of transducer units1502,1504,1506,1508,1510,1512,1514,1516, and1518inFIG. 15and detected and measured by a second portion of these transducer units. These signals are sent into object1500to identify the effects of inconsistencies1528,1530, and1532on Lamb wave modes.

With reference now toFIG. 17, an illustration of a graph comparing extracted asymmetric modes for a group of paths is depicted in accordance with an advantageous embodiment. In this illustrative example, graph1700includes horizontal axis1702and vertical axis1704. Horizontal axis1702is time in milliseconds. Vertical axis1704is normalized amplitude for the asymmetric modes.

As depicted, curves1706are for the asymmetric modes extracted for a group of paths. These asymmetric modes may be extracted using the process illustrated inFIG. 13, for example. The asymmetric modes are extracted from signals traveling along paths in group1520at a temperature of about 50 degrees Celsius.

In this illustrative example, curves1706are for the asymmetric modes for paths in group1520inFIG. 15. In particular, curves1706are for group1520before any inconsistencies are present for object1500. More specifically, curves1706are for group1520before inconsistency1528is present along path1534inFIG. 15.

As depicted, the arrival times for the asymmetric modes are substantially the same. In other words, in this illustrative example, a time delay is not present along the paths in group1520when an inconsistency is not present along the paths in group1520.

With reference now toFIG. 18, an illustration of a graph comparing extracted asymmetric modes for a group of paths is depicted in accordance with an advantageous embodiment. In this illustrative example, curves1706in graph1700are for the asymmetric modes extracted for the paths in group1520inFIG. 15when inconsistency1528is present along path1534.

As depicted, the presence of inconsistency1528along path1534causes curve1800for the asymmetric mode extracted for path1534to be shifted to the right of the other curves in curves1706. In other words, the arrival time for the asymmetric mode for path1534is delayed as compared to the arrival times for the other asymmetric modes for the other paths in group1520. In this manner, the time delay identified using the asymmetric modes provides an indicator of the presence of an inconsistency.

With reference now toFIG. 19, an illustration of a portion of the charts identifying index values for paths is depicted in accordance with an advantageous embodiment. In this illustrative example, graphs1900provide an indication of which paths in the paths formed by transducer units1502,1504,1506,1508,1510,1512,1514,1516, and1518inFIG. 15have inconsistencies present along the paths.

Graphs1900have horizontal axes1902and vertical axes1904. The horizontal axes are identifiers for index values calculated using cross-correlation. For example, these index values may be calculated in operation1400inFIG. 14. The identifiers for the index values range from 1 to 20 because each index value is for a particular path in the 20 paths formed by transducer units1502,1504,1506,1508,1510,1512,1514,1516, and1518inFIG. 15.

Further, the index values are arranged in ascending order such that the first index value is the smallest index value and the twentieth index value is the twentieth smallest index value or the largest index value. In this illustrative example, charts for only some of the index values for the paths are depicted.

Inconsistencies are identified as being present along a path when an index value is greater than a threshold. This threshold is calculated each time a new index value is taken into consideration.

As depicted, in this illustrative example, inconsistencies are identified as being present along the paths corresponding to seventeenth smallest index value1906, eighteenth smallest index value1908, nineteenth smallest index value1910, and twentieth smallest index value1912.

With reference now toFIG. 20, an illustration of a table containing the results of testing an object for inconsistencies under different conditions is depicted in accordance with an advantageous embodiment. In this illustrative example, table2000contains the results of testing object1500inFIG. 15for inconsistencies under various conditions.

Case 12002is the test case for when inconsistencies are not present in object1500. Case 22004is the test case for when only one inconsistency, such as inconsistency1528inFIG. 15, is present in object1500. Case 32006is the test case for when two inconsistencies, such as inconsistency1528and inconsistency1530inFIG. 15, are present in object1500. Case 42008is the test case for when three inconsistencies, such as inconsistency1528, inconsistency1530, and inconsistency1532inFIG. 15, are present in object1520.

Inconsistency locations2010identify the number of locations at which inconsistencies have been introduced in object1500for each case. Temperature2012identifies the different temperatures at which the different cases were tested.

Threshold value2014identifies the threshold value at which a first path corresponding to an index value is identified as having an inconsistency when the index values are arranged in the ascending order. Path and index value2016identify the particular paths with corresponding index values for which inconsistencies are identified as being present along the path.

As indicated by the data presented in table2000, the method used for identifying inconsistencies in object1500accurately identifies inconsistency1528, inconsistency1530, and/or inconsistency1532at various temperatures. In particular, these inconsistencies are identified even at high temperatures, up to about 50 degrees Celsius, and low temperatures, up to about negative 10 degrees Celsius.

Turning now toFIG. 21, an illustration of a data processing system is depicted in accordance with an advantageous embodiment. In this illustrative example, data processing system2100may be used to implement one or more of number of computers314inFIG. 3. As depicted, data processing system2100includes communications fabric2102, which provides communications between processor unit2104, memory2106, persistent storage2108, communications unit2110, input/output (I/O) unit2112, and display2114.

Processor unit2104serves to execute instructions for software that may be loaded into memory2106. Processor unit2104may be a number of processors, a multi-processor core, or some other type of processor, depending on the particular implementation. A “number”, as used herein with reference to an item, means “one or more items.” Further, processor unit2104may be implemented using a number of heterogeneous processor systems in which a main processor is present with secondary processors on a single chip. As another illustrative example, processor unit2104may be a symmetric multi-processor system containing multiple processors of the same type.

Memory2106and persistent storage2108are examples of storage devices2116. A storage device is any piece of hardware that is capable of storing information, such as, for example, without limitation, data, program code in functional form, and/or other suitable information either on a temporary basis and/or a permanent basis. Storage devices2116may also be referred to as computer readable storage devices in these examples. Memory2106, in these examples, may be, for example, a random access memory or any other suitable volatile or non-volatile storage device. Persistent storage2108may take various forms, depending on the particular implementation.

For example, persistent storage2108may contain one or more components or devices. For example, persistent storage2108may be a hard drive, a flash memory, a rewritable optical disk, a rewritable magnetic tape, or some combination of the above. The media used by persistent storage2108may also be removable. For example, a removable hard drive may be used for persistent storage2108.

Communications unit2110, in these examples, provides for communications with other data processing systems or devices. In these examples, communications unit2110is a network interface card. Communications unit2110may provide communications through the use of either or both physical and wireless communications links.

Input/output unit2112allows for input and output of data with other devices that may be connected to data processing system2100. For example, input/output unit2112may provide a connection for user input through a keyboard, a mouse, and/or some other suitable input device. Further, input/output unit2112may send output to a printer. Display2114provides a mechanism to display information to a user.

Instructions for the operating system, applications, and/or programs may be located in storage devices2116, which are in communication with processor unit2104through communications fabric2102. In these illustrative examples, the instructions are in a functional form on persistent storage2108. These instructions may be loaded into memory2106for execution by processor unit2104. The processes of the different embodiments may be performed by processor unit2104using computer implemented instructions, which may be located in a memory, such as memory2106.

These instructions are referred to as program code, computer usable program code, or computer readable program code that may be read and executed by a processor in processor unit2104. The program code in the different embodiments may be embodied on different physical or computer readable storage media, such as memory2106or persistent storage2108.

Program code2118is located in a functional form on computer readable media2120that is selectively removable and may be loaded onto or transferred to data processing system2100for execution by processor unit2104. Program code2118and computer readable media2120form computer program product2122in these examples. In one example, computer readable media2120may be computer readable storage media2124or computer readable signal media2126. Computer readable storage media2124may include, for example, an optical or magnetic disk that is inserted or placed into a drive or other device that is part of persistent storage2108for transfer onto a storage device, such as a hard drive, that is part of persistent storage2108. Computer readable storage media2124may also take the form of a persistent storage, such as a hard drive, a thumb drive, or a flash memory that is connected to data processing system2100. In some instances, computer readable storage media2124may not be removable from data processing system2100. In these examples, computer readable storage media2124is a physical or tangible storage device used to store program code2118rather than a medium that propagates or transmits program code2118. Computer readable storage media2124is also referred to as a computer readable tangible storage device or a computer readable physical storage device. In other words, computer readable storage media2124is a media that can be touched by a person.

Alternatively, program code2118may be transferred to data processing system2100using computer readable signal media2126. Computer readable signal media2126may be, for example, a propagated data signal containing program code2118. For example, computer readable signal media2126may be an electromagnetic signal, an optical signal, and/or any other suitable type of signal. These signals may be transmitted over communications links, such as wireless communications links, optical fiber cable, coaxial cable, a wire, and/or any other suitable type of communications link. In other words, the communications link and/or the connection may be physical or wireless in the illustrative examples.

In some advantageous embodiments, program code2118may be downloaded over a network to persistent storage2108from another device or data processing system through computer readable signal media2126for use within data processing system2100. For instance, program code stored in a computer readable storage medium in a server data processing system may be downloaded over a network from the server to data processing system2100. The data processing system providing program code2118may be a server computer, a client computer, or some other device capable of storing and transmitting program code2118.

In still another illustrative example, processor unit2104may be implemented using a combination of processors found in computers and hardware units. Processor unit2104may have a number of hardware units and a number of processors that are configured to run program code2118. With this depicted example, some of the processes may be implemented in the number of hardware units, while other processes may be implemented in the number of processors.

Additionally, a communications unit may include a number of one or more devices that transmit data, receive data, or transmit and receive data. A communications unit may be, for example, a modem or a network adapter, two network adapters, or some combination thereof. Further, a memory may be, for example, memory2106, or a cache, such as found in an interface and memory controller hub that may be present in communications fabric2102.

Thus, the different advantageous embodiments provide a method and apparatus for detecting an inconsistency in an object. In one advantageous embodiment, a method for detecting an inconsistency in an object is provided. Signals sent on a plurality of paths in the object are received at a plurality of transducer units associated with the object. Time delays are identified for a number of modes in the signals received at the plurality of transducer units. A determination is made as to whether a time delay in the time delays for the number of modes in the signals has a difference from a number of other time delays for the number of modes that is greater than a desired amount.

The different advantageous embodiments provide a detection apparatus and process that does not rely on pre-existing data. In other words, baseline data for the object without inconsistencies is unnecessary. Thus, the storage space for baseline data and generating baseline data for an object at various temperatures and other environmental conditions also is unnecessary. As a result, the time and expense needed for monitoring an object may be reduced.

In one or more of the advantageous embodiments, inconsistencies are detected without any comparison with previously obtained baseline data. This type of identification of inconsistencies may be performed even in the presence of environmental variations, such as, for example, without limitation, temperature, pressure, and/or other environmental changes. In some advantageous embodiments, velocities are identified from signals sent through an object during a current state for a structure. These velocities are used to determine whether an inconsistency is present in the object. Baseline or other comparisons formed at prior times based on different environmental conditions are not used. As a result, the identification of an inconsistency is not affected by environmental conditions.

The description of the different advantageous embodiments has been presented for purposes of illustration and description, and is not intended to be exhaustive or limited to the advantageous embodiments in the form disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art.

Further, different advantageous embodiments may provide different advantages as compared to other advantageous embodiments. The advantageous embodiment or embodiments selected are chosen and described in order to best explain the principles of the advantageous embodiments, the practical application, and to enable others of ordinary skill in the art to understand the disclosure for various advantageous embodiments with various modifications as are suited to the particular use contemplated.