Abstract:
A MEMS-based system that enables low cost, low power, single chip realization of real-time signal detection and fault diagnosis. The system is suitable for analyzing the time-varying properties of a signal that are important for condition-based monitoring of electro-mechanical machines or structures. The system includes mechanical sensors that sense input signals such as vibration, signal templates of fault conditions, logic units that detect, store, and compare signal features to provide a diagnostic state, and an output readout mechanism to couple the diagnostic state to readout device that provides an external signal.

Description:
FIELD OF THE INVENTION 
     The present invention relates generally to the field of signature analysis, and more particularly to a micromechanical sensor for real-time, time-frequency analysis of signals. 
     BACKGROUND OF THE INVENTION 
     Future electro-mechanical machines and structures will increasingly participate in their own service and maintenance using embedded distributed self-diagnostics that are remotely accessible to monitor machine health, detect and isolate subtle performance degradation, and in some cases even reconfigure some machines to adapt to changing operating environments. Traditionally, corrective maintenance and preventative maintenance have been the only two service paradigms. An estimate for the cost of service and maintenance for one major equipment manufacturer, however, is on the order of tens of billions of dollars. More recently, predictive or condition-based maintenance, enabled by low-cost sensors is emerging as an alternative. 
     Condition-based maintenance is just-in-time maintenance based on the actual health of the machine and its components. Since it avoids the cumulative cost of unnecessary service calls associated with preventative maintenance and the occurrence of machine failure and degradation associated with corrective maintenance, condition-based maintenance provides substantial cost savings. 
     Real-time signal analysis is critical for a variety of applications including condition-based monitoring and damage assessment for structures and electro-mechanical systems. Fault manifestation in machine vibration signals, however, is typically non-stationary in that the frequencies describing the faults vary over time. Identifying signatures of these types of faults requires analysis of properties of signals, such as frequency content, that vary over time. To isolate and identify a fault in a motor bearing, for example, the onset and temporal pattern of the changes in the spectral content of the signal must be determined. Traditional Fourier methods, including the short time Fourier transform (STFT), allows analysis of the time-varying properties of a signal that are important for diagnosis purposes. 
     Micro-Electro-Mechanical Systems (MEMS) integrate mechanical elements, such as microsensors and microactuators, and electronics on a common substrate through the utilization of microfabrication technology. MEMS are typically micromachined using integrated circuit (IC) compatible batch-processing techniques that selectively etch away parts of a silicon wafer or add new structural layers. They range in size from several micrometers to many millimeters. These systems sense, control, and actuate on a micro scale and function individually or in arrays to generate effects on a macro scale. MEMS sensors are known in the prior art and have been integrated into conventional non-MEMS signature analysis systems. The first problem with conventional systems is that sensors such as a tuning fork are not suitable for measuring time-varying spectral content of a signal because of the frequency-dependent damping constant of each individual fork. Second, the use of electronic processing in conventional systems make them susceptible to electronic interference. Third, the electronic processing requires adequate electrical power supply. Fourth, conventional systems are typically bulky in size because of the multitude of discrete component modules such as sensors, electronics, and readout. Thus, conventional systems are less portable than a monolithic MEMS implementation of the entire system. 
     In light of the foregoing, there is a need for a micromechanical sensor for signal detection an fault diagnosis that provides time-based windowing of event capture with control sequencing and data interpretation. 
     SUMMARY OF THE INVENTION 
     Accordingly, the present invention is directed to a MEMS system that allows real-time signal detection and fault diagnosis that substantially obviates one or more of the problems due to limitations and disadvantages of the related art. 
     In accordance with the purposes of the present invention, as embodied and broadly described, the invention provides a micro-electro-mechanical system for signature analysis including an array of sensors that measure a time varying event, wherein the array outputs a time-windowed sensor signal in response to operation of a system of interest. The sensor further includes a plurality of signal templates representing normal and faulty operating conditions of the system of interest, at least one logic unit that compares the sensor signal with the signal templates and provides a diagnostic state based on the comparison, and a readout device that outputs the diagnostic state as an external signal. 
     In another embodiment, the present invention provides a micro-electro-mechanical system for signature analysis of a system including an array of sensors detecting a physical phenomenon of interest, wherein the array of sensors has a time-frequency configuration that represents a template of a faulty operating condition of the system and a readout device that outputs an external signal indicating the faulty operating condition if the detected physical phenomenon matches the fault template. 
     The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate several embodiments of the invention and together with the description serve to explain the principles of the invention. 
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS 
     The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate an embodiment of the invention and, together with the description, serve to explain the objects, advantages, and principles of the invention. 
     FIG. 1 is a block diagram representing the components of a signature analysis system consistent with the present invention. 
     FIG. 2 is a schematic representation of a MEMS fabricated sensor for use in a signature analysis system consistent with the present invention. 
     FIG. 3 is a schematic representation of a single array of sensors that are timed to measure frequency contents of a signal for each time window for use in a signature analysis system consistent with the present invention. 
     FIG. 4 is a schematic representation of a plurality of sensor arrays which are timed to measure frequency content for different time windows for use in a signature analysis system consistent with the present invention. 
     FIG. 5 is a spectral analysis of a paper drive plate vibration in a Xerox copying system having a motor unbalance fault. 
     FIG. 6 is a schematic of an electronic logic unit consistent with the present invention. 
     FIG. 7 is a schematic representation of a mechanical logic unit. 
     FIG. 8 is a signal template extracted from the vibration signal of a paper drive assembly in a Xerox copying system. 
     FIG. 9 is a schematic representation of an array of sensors where the spatial and frequency configuration of the sensors match that of a known operating fault. 
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
     Reference will now be made in detail to the preferred embodiments of the invention, examples of which are illustrated in the accompanying drawings. 
     FIG. 1 is a block diagram of the components of a signature analysis system consistent with the present invention. System  100  is preferably on a single semiconductor chip and includes sensor  112 , logic unit  114 , signal templates  116 , and readout device  118 . 
     In one embodiment sensor  112  is an array comprising a plurality of MEMS sensors responsive to a system of interest  111 . Alternatively, sensor  112  can be a single sensor for a particular frequency. The system of interest can be a structure or an electro-mechanical machine. As shown in FIG. 2, sensor  210  is a MEMS fabricated device such as a tuning fork responsive to vibration from the electro-mechanical machine or structure. Sensor  210  has a fixed end  211  and a free end  212 . Sensor  210  further includes substrate  221 , insulating layer  222  on substrate  221 , and bottom conductor  224  on a portion of insulating layer  222 . Substrate  221  can be silicon or any other semiconductor base material. Sensor  210  responds to vibration near its resonant frequency by resonating at a higher amplitude at its free end. Although sensor  210  is described as a tuning fork to illustrate an embodiment of the present invention, sensor  210  can be any sensor responsive to, for example, shock, vibration, acceleration, temperature, pressure or electrical signals. 
     Sensor  210  further preferably includes a detector that detects and converts the resonance of the tuning forks into a sensor signal. Examples of such detectors include capacitive, piezoelectric, strain gauge, or other conventional detectors. FIG. 2 shows sensor  210  with capacitive detector  215 . As free end  212  of sensor  210  moves, capacitive detector  215  senses the capacitive change between free end  212  of sensor  210  and bottom conductor  224 . 
     In order to measure time-varying events of interest, sensors  210  preferably includes clamping or damping mechanisms, such as electrostatic clamp  213 , to stop the movement of the free end of the resonant member. The clamping or damping mechanism effectively resets each sensor of array  112  and allows the temporal configuration of each sensor to be controlled. This provides the ability to do time-based windowing of event capture. Electrostatic clamp  213  allows sensors  210  to detect and then release (by clamping or damping) a frequency in order to track and readout time-varying frequency information in the system of interest. Other examples of such mechanisms include actively controlled open or closed loop vibration damping after releasing the tuning forks and tuning Q-factors by varying areas of electrodes. 
     In another embodiment, a sensor array employs a plurality of sensors each having a different resonant frequency preferably with a clamping or damping mechanism. As shown in FIG. 3, a frequency spectrum of the detected physical phenomenon of interest can be constructed using array  300  comprising a plurality of sensors  310  having different resonant frequencies. In this embodiment, the signal from each sensor  310  represents a portion of the frequency spectrum. 
     In another embodiment shown in FIG. 4, sensor  400  comprises a plurality of sensor arrays  410 . This embodiment is preferred when the time-varying content of the signal is significantly faster than the tuning fork damping constant of the MEMS device. In this embodiment, each array of sensors detects the frequency content of a signal for a particular time window. Different arrays are timed to activate at fixed time intervals apart from each other. Once an array is read out, the oscillation of the tuning forks in the array is clamped or damped so that it can be activated to record new frequency content at a subsequent time interval. The number of arrays depends on the damping constant as well as the rate at which the time-varying components of the signal change. 
     An example of a vibration signal having time-varying frequency information is shown in FIG.  5 . The vibration signal shown in FIG. 5 is from a paper drive plate of a Xerox copying system having a fault due to unbalance in the main drive motor. The main frequency content of the signal is primarily in the 10 Hz to 1 kHz range. The time-varying components of the frequency content due to the unbalance of the main motor is around 10 Hz to 1 kHz. 
     Referring back to FIG. 1, logic unit  114  compares the sensor signal to stored signal templates  116 . Stored signal templates  116  represent, for example, normal operating conditions and potential fault conditions of the electro-mechanical machine or structure. If multiple sensor arrays are used as shown in FIG. 4, logic unit  114  comprises a plurality of logic units wherein one unit is coupled to each sensor array. The output from the plurality of logic units  114  is compared against an event sequence template and the results are aggregated. 
     Logic unit  114  is preferably an electronic component that stores signal templates  116  of fault conditions and performs the comparison. As shown in FIG. 6, an example of logic unit  614  comprises multiple bit comparators  615 , each of which can be coupled to each sensor  610  in array  612 . The readout from each sensor  610  is compared with a corresponding bit of stored bit pattern  616  using bit comparator  615 . An adder  619  connecting the output of comparators sums the differences and reports detection results by examining the total difference. In detection applications where only templates for normal conditions are known, a fault condition is reported if the total difference exceeds a predetermined threshold. In signal discriminate analysis where normal and faulty conditions are known, a detection is reported when the total difference is within a preset tolerance. This can be accomplished, for example, by cycling the comparison through all the templates until a match is reported. 
     When detecting time varying spectral content of signals using the single sensor array, an additional counter, preferably an electronic component, is necessary to record the sequence of detection events. When using multiple sensor arrays, the output of multiple logic units activated at consecutive time intervals is compared with a stored event sequence template to determine if a particular fault signal sequence is present or not. 
     In another embodiment, logic unit  114  stores the sensor signal as a mechanical state or position and counts signal events using MEMS fabricated gates, relays, and gears. Logic unit  116  compares the mechanically stored signal with signal templates of fault conditions  116  using mechanical logic implementations. An example of a mechanical logic implementation is shown in FIG.  7 . Sensor  700  comprises a plurality of sensors  710  each comprising restoring springs  712  attached to pins  714 . Pins  714  restrain gate mechanism  730  from traveling to a set mechanical state. The displacement required to pull pins  714  from gate  730  is pre-calibrated. Once pins  714  are pulled out, gate  730  is free to travel in the direction shown by the arrow to its set mechanical state indicting that a particular combinations of sensor readings is present. 
     Signal templates of fault conditions  116  are preferably time-frequency signal templates recorded as bit sequences. They are typically extracted from diagnostic data generated from lifetime tests of the system of interest. Since the diagnostic data includes normal and faulty operating conditions, the templates of faulty operation are useful for detecting and isolating fault occurrence. Signal templates  116  can be extracted from diagnostic data using techniques such as wavelet analysis and short time Fourier transform (STFT). FIG. 8 shows an example of a signal template extracted from the vibration signal of a paper drive assembly in a Xerox copying system having a defective solenoid using wavelet analysis. 
     Based on the comparison, logic unit  114  provides a diagnostic state to readout device  118 . Readout device couples the diagnostic state to an external signal that can be read by another system or a human being. A human readable signal is, for example, a modulated LED. A signal readable by another system is, for example, an optical signal from a vertical cavity surface emitting laser (VCSEL). 
     Another embodiment consistent with the present invention is shown in FIG.  9 . This signature analysis system comprises an array of sensors  910  where the sensors themselves, timed to activate at different times, represent a template of a faulty operating condition. In other words, the temporal and frequency configuration of sensors  912  in the array match the time-frequency components of a signal of a known faulty operating condition. In this embodiment, the frequency and spatial configuration of sensors  912  in array  910  match a known fault, such as a vibration signal due to a faulty solenoid in the main drive plate of a copying system. During normal operation of the copying system, the time-frequency components of the vibration signal do not correspond to the temporal and frequency configuration of sensors  912 . 
     During faulty operation, however, the time-frequency components of the vibration match the temporal and frequency configuration of sensors  912 . As each sensor of array  910  is activated, a mechanical logic unit (not shown) records the sensor&#39;s activation by, for example, movement of a gear, positioning of a relay, sliding of a linear slider element, mechanical movement of particles distributed on a surface, opening a fluidic valve to permit fluid pressure to store a record of the sensors activation, closing of an electrical contact, mechanical movement exposing or masking an optical source or reflector. Once all of the sensors  912  in array  910  representing the known fault condition are activated, the mechanical logic unit determines that the system is operating in the known fault condition. A readout device (not shown) then outputs a signal indicating the faulty operating condition. The signature analysis system preferably includes multiple sensor arrays that represent multiple known fault conditions. 
     In another embodiment, a portable signature analysis system is provided including an array of sensors, a plurality of stored signal templates, at least one logic unit, and a readout component. The sensor array outputs a sensor signal in response to operation of a system of interest. The portable system stores a plurality of signal templates representing normal and faulty operating conditions of the system of interest. Once a signal is detected, one or more logic units compare the detected sensor signal with the stored signal templates and provides a diagnostic state based on the comparison. Once the diagnostic state is determined, a readout component displays the diagnostic state in a human readable form. 
     It will be apparent to those skilled in the art that various modifications and variations can be made in the system level sensor that relies on mechanical component implementation and integration for real-time signal detection and fault diagnosis. Thus, it is intended that the present invention cover the modifications and variations of this invention provided they come within the scope of the appended claims and their equivalents.