Automatic activation of a fog protection system onboard a vehicle

A method is provided that includes a number of operations performed in real-time during operation of a vehicle. That is, the method may include detecting fog on an interior surface of the window using one or more sensors according to a process, and automatically activating a fog protection system to reduce or prevent fog on the interior surface of the window in an instance in which fog is detected according to the process. For each sensor, the process may include receiving a measurement from the sensor. And from the measurement, the process may include identifying or calculating a dew-point temperature in a compartment of the vehicle including the window to an exterior thereof, and detecting fog on the interior surface of the window in an instance in which the dew-point temperature is near, at, or above a surface temperature of the interior surface of the window.

TECHNOLOGICAL FIELD

The present disclosure relates generally to fog detection/prediction and, in particular, to fog detection/prediction and automatic activation of a fog protection system onboard a vehicle such as an aircraft.

BACKGROUND

Throughout the history of pressurized aircraft, the accumulation of fog on cockpit windows has presented a challenge to the flight of aviators. Given that windshield or side window fog can obstruct clear flight path visibility, the real-time detection of environmental humidity conditions conducive to windshield and/or side window fog is an important cockpit input needed to ensure normal flight operations, especially during the flight phases of approach and landing.

In the aerospace industry certification regulations mandate that any aircraft window heat system must provide anti-fog capability to ensure the at least a portion of the interior surfaces of the cockpit windshield and side windows remain clear of fog to the extent that both pilots have clear visibility of a typical flight path. In order to achieve this directive, any anti-fog system that is installed must be capable of maintaining a window clear of fog at any cockpit ambient dew point temperature.

Historically, the majority of aircraft have not had an automatic real-time window fog detection/prediction system installed, but rather depended on the physical identification of windshield or side window fog by the flight crew and subsequent manual activation of fog protection systems. Alternatively, some aircraft have been equipped with electric or pneumatic anti-fog systems to prevent the formation of fog on windshield surfaces from ever occurring in the course of a given flight. But these anti-fog systems are typically operated for the entire flight and therefore impose excessive energy and fuel burn requirements since the systems are often operating when fog accumulation conditions are not present.

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

BRIEF SUMMARY

Example implementations of the present disclosure are generally directed to an improved apparatus, method and computer-readable storage medium for real-time or near real-time detection or prediction of fog on one or more windows of a vehicle such as transport category commercial aircraft due to environmental humidity conditions. Example implementations may then automatically activate one or more fog protection systems to reduce or prevent the accumulation of fog. Example implementations may reduce operator workload and/or optimize energy use by activating the fog protection systems only when in or near fog conditions due to environmental humidity conditions.

According to one aspect of example implementations, the method includes a number of operations performed in real-time during operation of the vehicle. That is, the method may include detecting or predicting fog on an interior surface of the window using one or more sensors according to one or more processes. And the method may include automatically activating a fog protection system to reduce or prevent fog on the interior surface of the window in an instance in which fog is detected or predicted according to one or more of the processes, or in some examples, only in an instance in which fog is detected or predicted from the measurement from a majority of the sensor(s) used in the process(es).

For each sensor, the process may include receiving a measurement from the sensor. From the measurement, the process may include identifying or calculating a dew-point temperature in a compartment of the vehicle including the window to an exterior thereof, and detecting or predicting fog on the interior surface of the window in an instance in which the dew-point temperature is near, at, or above a surface temperature of the interior surface of the window. In some examples, the process may further include calculating the surface temperature of the interior surface of the window as a function of a total air temperature exterior to the vehicle, and a speed of the vehicle.

In some examples, the sensor may include a temperature sensor, and receiving the measurement from the sensor includes receiving a measurement of an ambient temperature in the compartment from the temperature sensor. In these examples, the process may further include receiving a measurement of a relative humidity in the compartment from a relative-humidity sensor. The dew-point temperature may then be calculated as a function of the ambient temperature and relative humidity within the compartment.

In some examples, the process may be a first process, and the sensor(s) may be or include first sensor(s). Alternatively, carrying out a first process can be characterized as receiving and/or manipulating measurements from first sensors to obtain a first result. The first result may then be used to identify and/or calculate certain data, such as dew-point temperature, and to detect or predict the presence of fog. In these examples, the method may further include detecting fog on the interior surface of the window using one or more second sensors according to a second process. Similar to the foregoing characterization of carrying out a first process, carrying out a second process can be characterized as receiving and/or manipulating measurements from second sensors to obtain a second result. The second result may then be used to identify and/or calculate certain data, such as intensity of a light beam reflected off the interior surface of the window. The second result may then be used to detect or predict the presence of fog. For each second sensor, this process may include receiving a measurement from the second sensor, with the measurement being of an intensity of a light beam reflected off the interior surface of the window; and from the measurement. The process may then include detecting fog on the interior surface of the window in an instance in which the intensity is below a predetermined threshold, which could be defined by a quantifiable obscuration level from the light beam receiver. This obscuration level could further be defined or stored by software within the system controller, such as but not limited to, 90% of the baseline (no obscuration) intensity as an indication of a fog condition.

The fog protection system may be automatically activated in an instance in which fog is detected or predicted according to the first process or second process. Or in some further examples, the fog protection system may be automatically activated only in an instance in which fog is detected or predicted from the measurement from a majority of the collective of first sensor(s) and second sensor(s).

In other aspects of example implementations, an apparatus and a computer-readable storage medium are provided for detecting or predicting inflight fog on a window of a vehicle. The features, functions and advantages discussed herein may be achieved independently in various example implementations or may be combined in yet other example implementations further details of which may be seen with reference to the following description and drawings.

Each figure shown in this disclosure shows a variation of an aspect of the embodiments presented, and only differences will be discussed in detail.

DETAILED DESCRIPTION

Some implementations of the present disclosure will now be described more fully hereinafter with reference to the accompanying drawings, in which some, but not all implementations of the disclosure are shown. Indeed, various implementations of the disclosure may be embodied in many different forms and should not be construed as limited to the implementations set forth herein; rather, these example implementations are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art. Also, something may be shown or described as being to a first, second, third or the like should not be taken to imply a specific order, unless otherwise stated. Further, although reference may be made herein to a number of measures, predetermined thresholds and the like such as times, distances, speeds, percentages and the like, according to which aspects of example implementations may operate; unless stated otherwise, any or all of the measures/predetermined thresholds may be configurable. Like reference numerals refer to like elements throughout.

Example implementations of the present disclosure are generally directed to real-time or near real-time detection or prediction of fog on one or more windows of a vehicle. Example implementations will be primarily described in the context of a vehicle such as transport category commercial aircraft. It should be understood, however, that example implementations may be equally applicable to any of a number of other vehicles such as general aviation aircraft (e.g., airplanes, helicopters), automobiles, trains, watercraft (e.g., boats, ships) and the like.

FIGS. 1A and 1Billustrate respectively an aircraft100and its cockpit102(sometimes referred to as a flight deck—and more generally a compartment), the aircraft being equipped with fog detection/prediction system104in accordance with example implementations of the present disclosure. As shown, the aircraft is a commercial, twin-engine aircraft. It should be understood, however, that other types of aircraft including fixed-wing aircraft and rotorcraft, commercial and military aircraft, and the like may be equally equipped with the system of example implementations.

In addition to the cockpit102, the aircraft100includes a fuselage106to which a pair of wings108are attached; and the aircraft includes a pair of engines110attached to the wings. The fuselage has a nose section112at the forward part of the aircraft, and a tail section114at the aft part of the aircraft. A vertical stabilizer116and a pair of horizontal stabilizers118are attached to the tail section of the fuselage.

The fog detection/prediction system104may be generally configured to detect fog on one or more windows of the aircraft100. The fog detection/prediction system includes one or more of each of a number of components such as one or more sensors120at a location proximate one or more windows of the aircraft, and coupled to a processor unit122. These windows may include, for example, one or more windows in the cockpit102such as one or more windshield windows124, side windows126and the like in the cockpit, although any of a number of other windows throughout the aircraft may equally benefit from example implementations. A temperature sensor128at a location on the surface130of the aircraft is also depicted in addition to sensors120.

The sensors120may be any of a number of different types of sensors configured to detect, predict, or otherwise measure conditions on an interior surface of the window(s)124,126or in an interior environment of the window(s) such as within the cockpit102, which may be indicative of fog on the interior surface of the window(s). As explained in greater detail below, examples of suitable sensors include first sensors120asuch as a dew-point sensor, temperature sensor, relative humidity sensor and the like, which in some examples may be located near the ceiling of the cockpit. Other examples of suitable sensors include second sensors120bsuch as one or more light emitter/detector pairs, which in some examples may be located adjacent to the window(s). In examples including a light emitter/detector pair, the pair may be located to ensure that the angle formed between the interior surface of the window and incident light beam emitted from the emitter is greater than the critical angle of the light beam, which may ensure total internal reflection of the emitted light beam.

In accordance with example implementations, the processor unit122may be configured to detect or predict fog on an interior surface of a window124,126using one or more sensors120, and perform one or more actions in response thereto, in real-time (real-time generally herein including near real-time) during flight of the aircraft100(or more generally operation, or transportive operation of the vehicle). For each sensor, the processor unit may receive a measurement from the sensor. From the measurement, the processor unit may identify or calculate a dew-point temperature in the cockpit102(compartment) of the aircraft100(vehicle) including the window to an exterior thereof. The processor unit may then detect or predict fog on the interior surface of the window in an instance in which the dew-point temperature is near, at, or above a surface temperature of the interior surface of the window. “Near or at” a surface temperature, for reference purposes herein, can indicate that a surface temperature above the dew-point temperature by less than 5° F. (˜3° C.), such as may fulfill the following:
DPT+5° F.≧ST>DPT
where DPT is the dew-point temperature and ST is the surface temperature.

In some examples, the sensor120may be a dew-point sensor from which the processor unit122may receive a measurement of the dew-point temperature in the cockpit102. In some examples, the sensor may be a temperature sensor from which the processor unit122may receive a measurement of an ambient temperature in the cockpit. In these examples, the sensors may also include a relative-humidity sensor from which the processor unit may further receive a measurement of a relative humidity in the cockpit. The processor unit may then calculate the dew-point temperature as a function of the ambient temperature and relative humidity within the cockpit. In one example, the dew-point temperature may be calculated based on a known relationship between ambient temperature, relative humidity and dew-point temperature such as from a database or table of values from a psychrometric chart such as that shown inFIG. 2.

In some examples, the processor unit122may calculate the surface temperature of the interior surface of the window124,126as a function of one or more aircraft flight parameters such as total air temperature exterior to the aircraft100, and a speed of the aircraft. In some examples, the processor unit may monitor an aircraft data bus for one or more of these aircraft flight parameters. In another example, the total air temperature may be obtained from the temperature sensor128.

In some examples, the aforementioned process by which the processor unit122detects or predicts fog may be a first process and the sensors120(e.g., dew-point sensor, temperature sensor, relative-humidity sensor) may include first sensors120a. In these examples, the processor unit may further detect or predict fog on the interior surface of the window124,126using one or more second sensors120baccording to a second process. For each second sensor, the processor unit may receive a measurement from the second sensor, with the measurement being of an intensity of a light beam reflected off the interior surface of the window. From the measurement, then, the processor unit may detect fog on the interior surface of the window in an instance in which the intensity is below a predetermined threshold, such as in an instance in which the intensity decreases by at least a certain percentage indicative of fog on the interior surface.

The processor unit122may perform one or more alert or remedial actions in an instance in which fog is detected or predicted according to the first process or second process, such as to receive a first and/or second result. For example, the processor unit may cause automatic activation of one or more fog protection systems132(e.g., anti-fog systems, defog systems) onboard the aircraft. These systems may be deployed proximate the windows124,126and employ various different types of mechanisms to remove or prevent the formation of fog on their interior surfaces. Examples of suitable fog protection systems include an electrically-heated element embedded into or on the surface of the window, or a blower with a nozzle configured to direct pneumatic (hot air) across the surface of the window, in either instance the fog protection systems being configured to raise the interior surface temperature of the window to above the dew-point temperature, which may reduce or prevent fog on the interior surface of the window.

In some examples, the sensors120may be distributed over a plurality of windows124,126. In these examples, the processor unit122may detect or predict fog and cause activation of the fog protection systems132on a per-window basis. Or the processor unit may detect or predict fog on a per-window basis, but activate fog across multiple of the windows in an instance in which fog is detected or predicted on the interior surface of one of the windows. Additionally or alternatively, one or more of the windows may include redundant sensors so as to avoid false detections or predictions. In any instance, in some examples, the processor unit may cause automatic activation of the fog protection system only in an instance in which fog is detected or predicted from the measurement from a majority of the sensors, such as a majority of first sensors120a, a majority of the second sensors120b, or a majority of the collective first and second sensors.

FIG. 3illustrates a flowchart including various operations in a method300according to one example implementation of the present disclosure. As shown, the method may include a number of operations performed continuously in real-time during operation of a vehicle such as the aircraft100.

The method300may include detecting or predicting fog on an interior surface of a window124,126using one or more sensors120according to a process, as shown at block310. And the method may include automatically activating a fog protection system132to reduce or prevent fog on the interior surface of the window in an instance in which fog is detected or predicted according to the process, or in some examples, only in an instance in which fog is detected or predicted from the measurement from a majority of the sensor(s), as shown at block320.

For each sensor120, the process may include receiving a measurement from the sensor, as shown at block302. From the measurement, the process may include identifying or calculating a dew-point temperature in the cockpit102(compartment) of the aircraft100(vehicle) including the window124,126to an exterior thereof, as shown in block304. In some examples, the method may further include calculating the surface temperature of the interior surface of the window as a function of a total air temperature exterior to the aircraft, and a speed of the aircraft, as shown in block306. In one example, the outer surface temperature (Tsurface) may be calculated as a function of total temperature (Ttotal) and Mach number as follows:
Tsurface=f[Ttotal/(1+0.2×Mach)]
In the preceding, Ttotalrepresents the total air temperature and Mach represents the Mach number relationship to speed of the aircraft. In some examples, the surface temperature may be assumed to be the same on internal and external surfaces of the window124,126, with the window being unheated until the time when the fog protection system132is activated. In the above and in other notational examples, temperatures may be represented in degrees Celsius, although the temperatures may be similarly represented and calculated in other appropriate units.

In some examples in which the sensor is a temperature sensor, and the measurement from the temperature sensor may be an ambient temperature in the cockpit102from the temperature sensor. In these examples, the process may further include receiving a measurement of a relative humidity in the cockpit from a relative-humidity sensor. The dew-point temperature may then be calculated as a function of the ambient temperature and relative humidity within the cockpit. More notationally, for example, the dew-point temperature (Tdew-point) may be calculated as follows:
Tdew-point=RH0.125×(112+0.9×Tcockpit)+(0.1×Tcockpit)−112
In the preceding, RH represents the percentage relative humidity, and Tcockpitrepresents the ambient temperature in degrees Celsius. And in some further more simplified examples, the numerical value of the dew-point temperature may be calculated as follows:
Tdew-point=(100−RH)/5 (whereTdew-pointis in degrees Celsius)
The method may include detecting or predicting fog on the interior surface of the window in an instance in which the dew-point temperature (e.g., Tdew-point) is near, at, or above a surface temperature (e.g., Tsurface) of the interior surface of the window, as shown in blocks308,310.

In some examples, the aforementioned process may be a first process, and the sensor(s)120may be or include first sensor(s)120a. Alternatively, carrying out a first process can be characterized as receiving and/or manipulating measurements from first sensors to obtain a first result. The first result may then be used to identify and/or calculate certain data, such as dew-point temperature, and to detect or predict the presence of fog. In these examples, the method may further include detecting fog on the interior surface of the window using one or more second sensors120baccording to a second process, as shown at block316. Similar to the foregoing characterization of carrying out a first process, carrying out a second process can be characterized as receiving and/or manipulating measurements from second sensors to obtain a second result. The second result may then be used to identify and/or calculate certain data, such as intensity of a light beam reflected off the interior surface of the window. The second result may then be used to detect or predict the presence of fog. For each second sensor, this process may include receiving a measurement from the second sensor, with the measurement being of an intensity of a light beam reflected off the interior surface of the window; and from the measurement, as shown at block312. The process may then include detecting fog on the interior surface of the window in an instance in which the intensity is below a predetermined threshold, as shown at blocks314,316.

The fog protection system132may be automatically activated in an instance in which fog is detected or predicted according to the first process or second process, as shown at block320. Or in some further examples, the fog protection system may be automatically activated only in an instance in which fog is detected or predicted from the measurement from a majority of the collective of first sensor(s) and second sensor(s), as shown at blocks318,320.

The fog protection system132may be activated to reduce or prevent fog on the interior surface of the window124,126, and may remain active until deactivated. In some examples, the fog protection system may be deactivated after some point in time determined to be sufficient for the fog protection system to clear the window of fog and/or to bring the surface temperature of the window up to a point in which fog is no longer predicted, which may optimize energy usage required by the fog protection system. In some examples, the fog protection system may remain active until measurements from the sensors no longer indicate fog or a prediction of fog on the interior surface of the window, as according to the first and/or second processes; or for a period of time (e.g., five minutes) after the measurements last indicate or predict fog.

FIG. 4illustrates an apparatus400that according to some examples may be configured to at least partially implement the processor unit122. Generally, the apparatus of exemplary implementations of the present disclosure may comprise, include or be embodied in one or more fixed, portable or embedded electronic devices. The apparatus may include one or more of each of a number of components such as, for example, a processor402comprising hardware and software connected to a memory404.

The processor402is generally any piece of computer hardware that is capable of processing information such as, for example, data, computer-readable program code, instructions or the like (at times generally referred to as “computer programs,” e.g., software, firmware, etc.), and/or other suitable electronic information. The processor is composed of a collection of electronic circuits some of which may be packaged as an integrated circuit or multiple interconnected integrated circuits (an integrated circuit at times more commonly referred to as a “chip”). The processor may be configured to execute computer programs, which may be stored onboard the processor or otherwise stored in the memory404(of the same or another apparatus).

The processor402may be a number of processors, a multi-processor core or some other type of processor, depending on the particular implementation. Further, the processor may be implemented using a number of heterogeneous processor systems in which a main processor is present with one or more secondary processors on a single chip. As another illustrative example, the processor may be a symmetric multi-processor system containing multiple processors of the same type. In yet another example, the processor may be embodied as or otherwise include one or more application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs) or the like. Thus, although the processor may be capable of executing a computer program to perform one or more functions, the processor of various examples may be capable of performing one or more functions without the aid of a computer program.

The memory404is generally any piece of computer hardware that is capable of storing information such as, for example, data, computer programs (e.g., computer-readable program code406) and/or other suitable information either on a temporary basis and/or a permanent basis. The memory may include volatile and/or non-volatile memory, and may be fixed or removable. Examples of suitable memory include random access memory (RAM), read-only memory (ROM), a hard drive, a flash memory, a thumb drive, a removable computer diskette, an optical disk, a magnetic tape or some combination of the above. Optical disks may include compact disc-read only memory (CD-ROM), compact disc-read/write (CD-R/W), digital versatile disc (DVD) or other standard media and format. In various instances, the memory may be referred to as a computer-readable storage medium which, as a non-transitory device capable of storing information, may be distinguishable from computer-readable transmission media such as electronic transitory signals capable of carrying information from one location to another. Computer-readable medium as described herein may generally refer to a computer-readable storage medium or computer-readable transmission medium.

In addition to the memory404, the processor402may also be connected to one or more interfaces for displaying, transmitting and/or receiving information. The interfaces may include a communications interface408(e.g., communications unit). The communications interface may be configured to transmit and/or receive information, such as to and/or from other apparatus(es), network(s) or the like. The communications interface may be configured to transmit and/or receive information by physical (wireline) and/or wireless communications links. Examples of suitable communication interfaces include a network interface controller (NIC), wireless NIC (WNIC) or the like.

Retrieval, loading and execution of the program code instructions may be performed sequentially such that one instruction is retrieved, loaded and executed at a time. In some example implementations, retrieval, loading and/or execution may be performed in parallel such that multiple instructions are retrieved, loaded, and/or executed together. Execution of the program code instructions may produce a computer-implemented process such that the instructions executed by the computer, processor or other programmable apparatus provide operations for implementing functions described herein.

Execution of instructions by a processor, or storage of instructions in a computer-readable storage medium, supports combinations of operations for performing the specified functions. In this manner, an apparatus400may include a processor402and a computer-readable storage medium or memory404coupled to the processor, where the processor is configured to execute computer-readable program code406stored in the memory. It will also be understood that one or more functions, and combinations of functions, may be implemented by special purpose hardware-based computer systems and/or processors which perform the specified functions, or combinations of special purpose hardware and program code instructions.