Method for monitoring the operation of a plurality of aeronautical measurement probes, and associated aeronautical measurement monitoring system and architecture

Abstract

TITLE Method for monitoring the operation of a plurality of aeronautical measurement probes, and associated monitoring system and aeronautical measurement architecture. The present invention relates to a method for monitoring the operation of a plurality of aeronautical measurement probes, each probe comprising heating means, the method comprising the following steps: - acquisition (110) of a plurality of consumption data, each consumption data characterizing the electrical consumption of the heating means of one of the aeronautical measurement probes; - determination (120) of at least one similarity relationship between at least two consumption data; - comparison (130) of the similarity relationship(s) with a threshold; - detection (140) of an operating anomaly based on the result of the comparison(s). Figure for the abstract: Figure 3

Description

Title of the invention: Method for monitoring the operation of a plurality of aeronautical measurement probes, and associated aeronautical measurement monitoring system and architecture

[0001] The present invention relates to a method for monitoring the operation of a plurality of aeronautical measuring probes.

[0002] The present invention also relates to a monitoring system and an aeronautical measurement architecture associated with this monitoring method.

[0003] The field of the invention is that of anemobaroclinometric and temperature systems and in particular, of supervision and security of such systems.

[0004] In a manner known per se, an anemobarroclinometric system allows the measurement of several physical quantities usable in the aeronautical field, such as total pressure, static pressure, angle of attack, temperature, speed, etc. To do this, such a system comprises a plurality of aeronautical measuring probes.

[0005] To ensure the protection of aeronautical measuring probes against icing and the risks of water accumulation in any form, they are generally equipped with electric heating means which maintain them at a sufficiently high temperature to prevent the accretion of frost or the deterioration of performance by the presence of frost.

[0006] The power strictly required to heat these probes depends heavily on external conditions (speed, temperature, altitude, amount of water, etc.).

[0007] The proper functioning of this anemobaroclinometric system is essential to the operational safety of the aircraft. Therefore, a monitoring system is generally dedicated to such an anemobaroclinometric system.

[0008] In addition, new regulations require the monitoring system to be able to resolve ambiguities between the normal operation of the heating of a probe under particular environmental conditions and the malfunction of the heating, knowing that the two scenarios overlap greatly, particularly in terms of power consumed.

[0009] To meet this requirement, the use of electrical consumption data from the probes is known. In particular, the electrical consumption of each probe can be compared to upper and lower thresholds describing the overall possible consumption envelope of the probes. This solution makes it possible to adequately detect a clear fault such as an open circuit or a short circuit. However, its main drawback is its inability to highlight certain faults, particularly latent faults. This leads to an "average" degradation. "performance, making the power consumed and the probe temperature insufficient compared to expectations and therefore unable to defrost in icing conditions.

[0010] For example, it is possible that the heating element for a probe may consume significantly less power than it would under normal operating conditions and, therefore, may not be able to properly defrost the probe when it encounters freezing conditions. This underconsumption can also result from certain environmental conditions without the probe heating element itself being defective. It is therefore necessary to implement a monitoring system capable of distinguishing between heating element failures and normal operating conditions.

[0011] To overcome this problem, document EP 3 766 782 A1 proposes calculating the monitoring thresholds a priori based on available external information, such as external conditions. However, in this case, the calculation of the thresholds is hampered by the complexity of modeling the effect of external conditions on heating power. Unexpected or thermodynamically complex conditions can alter the threshold calculations and render the system inoperative by triggering inappropriate alerts.

[0012] Other solutions involve measuring the probe temperature. A temperature that is too low or inconsistent with the power supplied indicates a failure. However, such systems incorporating temperature measurement encounter difficulties due to, on the one hand, the complexity of integrating the temperature sensor into the probe and, on the other hand, the sensor's own failure modes, which induce detection errors.

[0013] The present invention aims to solve all the problems of the prior art and to propose means of effectively detecting failures that may occur in the heating means of an aeronautical measuring probe in a simple and reliable manner.

[0014] To this end, the invention relates to a method for monitoring the operation of a plurality of aeronautical measuring probes, each probe comprising heating means, the method comprising the following steps:

[0015] - acquisition of a plurality of consumption data, each data point consumption characterizing the electrical consumption of the heating means of one of the aeronautical measuring probes;

[0016] - determination of at least one similarity relationship between at least two data points consumption ;

[0017] - comparison of the or each similarity relationship with a threshold;

[0018] - detection of a malfunction based on the result of the or each comparison.

[0019] According to other advantageous aspects of the invention, the method comprises one or more of the following features, taken individually or in all technically possible combinations:

[0020] - each consumption data item includes at least one of the selected elements in the group comprising:

[0021] - the voltage of the current supplying the heating means of the measuring probe corresponding aeronautics;

[0022] - the intensity of the current supplying the heating means of the measuring probe corresponding aeronautics;

[0023] - the power consumed by the heating means of the measuring probe corresponding aeronautics;

[0024] - each consumption data point characterizes an electrical consumption over time actual heating means of the corresponding aeronautical measuring probe;

[0025] - the similarity relation corresponds to at least one of the elements chosen in the group including:

[0026] - the difference between the corresponding consumption data;

[0027] - the joint evolution of the corresponding consumption data;

[0028] - the threshold or each threshold is determined by an artificial intelligence algorithm;

[0029] - the threshold(s) is determined based on anemobometric information and / or meteorological, preferably from measuring equipment located in an aircraft carrying said aeronautical measuring probes and / or from surrounding aircraft and / or from remote installations;

[0030] - at least one similarity relationship is determined between data from consumption from aeronautical measurement probes belonging to the same anemobarometric channel;

[0031] - at least one similarity relationship is determined between data from consumption from aeronautical measurement probes belonging to different anemobarometric channels;

[0032] - at least one similarity relationship is determined between data from consumption from aeronautical measuring probes measuring the same physical quantity or different physical quantities;

[0033] - the step of detecting a malfunction includes determining of a failing aeronautical measuring probe based on the results of comparisons of at least two similarity relationships including one or more consumption data from this aeronautical measuring probe.

[0034] The invention also relates to a computer program comprising software instructions which, when executed by a computer, implement the process as defined above.

[0035] The invention also relates to a monitoring system comprising technical means configured to implement the process as defined below.

[0036] Finally, the invention also relates to an aeronautical measurement architecture comprising:

[0037] - a plurality of aeronautical measuring probes;

[0038] - a monitoring system as defined above.

[0039] The invention will become clearer upon reading the following description, given solely by way of non-limiting example, and made with reference to the drawings in which:

[0040] - [Fig. 1] [Fig. 1] is a schematic view of a measurement architecture aeronautics according to a first embodiment of the invention, the architecture comprising a monitoring system according to the invention;

[0041] - [Fig.2] [Fig.2] is a schematic view of a measurement architecture aeronautics according to a second embodiment of the invention, the architecture comprising a monitoring system according to the invention;

[0042] - [Fig.3] [Fig.3] is a flowchart of a monitoring process according to the invention, the method being implemented by the monitoring system of [Fig.1] or [Fig.2].

[0043] Figure 1 illustrates an aeronautical measurement architecture 10 according to a first embodiment of the invention. This architecture 10 is advantageously at least partially embedded in an aircraft.

[0044] An aircraft is defined as any pilotable machine capable of moving through the air. In particular, an aircraft may be an airplane, a helicopter, or a drone. The aircraft may be piloted by a pilot from its cockpit and / or by any other operator from a remote control center and / or autonomous in its piloting mode.

[0045] With reference to [Fig.1], the aeronautical measurement architecture 10 includes an anemobaroclinometric measurement channel 11 and a monitoring system 16.

[0046] The anemobaroclinometric measurement channel 11 allows several physical quantities relating to the environment in which the aircraft is operating to be measured.

[0047] In particular, the anemobaroclinometric measurement channel 11 comprises a plurality of aeronautical measurement probes 12 and a computer 14.

[0048] Each aeronautical measuring probe 12 is advantageously mounted on an aircraft fuselage and allows the measurement of at least one of the physical values ​​relating to the environment in which this probe 12 is located. Such a value represents, for example, the total pressure, the static pressure, the angle of attack, the temperature, the speed, etc.

[0049] Advantageously, at least some of the probes 12 are of different types. This means that these probes allow for the measurement of different physical quantities.

[0050] For example, each probe 12 is chosen from a Pitot probe allowing to measure a total pressure Pt, an angle of attack probe allowing to measure an angle of attack Alpha, a temperature probe allowing to measure a total temperature TAT, a first static probe allowing to measure a static pressure Ps_r on the right side of the aircraft and a second static probe allowing to measure a static pressure Ps_l on the left side of the aircraft.

[0051] Thus, among these probes 12, the first static probe and the second static probe are of the same nature and the other probes are of different natures.

[0052] The composition and nature of the probes 12 in the anemobaroclinometric measurement channel 11 can vary according to different embodiments of the invention.

[0053] The medium in which each probe 12 is exposed is in particular a freezing medium, that is to say a medium in which frost accretions are likely to form outside or inside the probe 12.

[0054] Thus, each probe 12 is provided with heating means for heating at least one area of ​​interest of that probe, in particular to prevent frost from forming in that area of ​​interest. These heating means are, for example, known per se and include, for example, a heating wire or a conduit for a heat transfer fluid, extending through the area of ​​interest of the probe.

[0055] The computer 14 is for example an embedded computer which is connected to all the probes 12 and which allows to retrieve and process the measurements generated by these probes 12.

[0056] The computer 14 also allows the operation of the probes 12 to be controlled, and in particular the heating means of these probes 12. For example, the computer 14 allows the operation of these means to be activated or deactivated according to external conditions and / or at the request of a pilot or another operator.

[0057] The monitoring system 16 makes it possible to detect an anomaly in the operation of the probes 12 by analyzing in particular consumption data of the heating means of these probes, as will be explained in more detail later.

[0058] In the example of [Fig.1], the monitoring system 16 is fully integrated into the anemobaroclinometric measurement channel 11 and includes in particular an input module 21, a processing module 22 and an output module 23.

[0059] The input module 21 makes it possible to acquire, advantageously in real time, consumption data relating to the electrical consumption of the heating means of each probe 12. To do this, the input module 21 is connected to measuring means allowing the electrical consumption of the heating means of each probe 12 to be measured.

[0060] In the example of [Fig.1], the measuring means are integrated into each probe 12 and the input module 21 is therefore connected to each of these probes 12. According to another embodiment, the measuring means are remote from each probe 12.

[0061] Each consumption data point includes at least one of the elements chosen from the group comprising:

[0062] - the voltage of the current supplying the heating means of the measuring probe corresponding aeronautics;

[0063] - the intensity of the current supplying the heating means of the measuring probe corresponding aeronautics;

[0064] - the power consumed by the heating means of the measuring probe corresponding aeronautics.

[0065] In a particular example, each consumption data point includes the voltage and current supplying the heating means of the corresponding probe. The power consumed can thus be determined, for example, directly by the processing module 22 of the monitoring system 16.

[0066] Advantageously, the input module 21 is further connected to at least one system 25 (for example, a communication system) for providing external data. This external data corresponds, for example, to anemobarometric and / or meteorological information from measuring equipment other than the probes 12 described above. For example, this measuring equipment is installed in the same aircraft providing data to other systems and / or in surrounding aircraft and / or in remote installations, such as ground stations or satellites.

[0067] The processing module 22 allows processing all the data received by the input module 21 in order to determine a malfunction of at least one probe 12, as will be explained in more detail later.

[0068] The output module 23 allows information relating to each anomaly detected by the processing module 22 to be transmitted to any interested system. Such an interested system may correspond to the computer 14 or any other on-board computer, or even to a human-machine interaction system designed to communicate such an anomaly to the pilot or operator.

[0069] Each of these modules 21 to 23 is implemented, for example, at least partially in the form of software.

[0070] In such a case, the monitoring system 16 further includes a memory for storing such software and a processor for executing this software.

[0071] Alternatively or in addition, at least one of these modules 21 to 23 presents at least partially a programmable logic circuit such as an FPGA (Field-Programmable Gate Array) circuit.

[0072] In some embodiments, the monitoring system 16 is embedded, for example in the form of software, in an embedded computer, for example in the computer 14 as described above.

[0073] Fig. 2 illustrates an aeronautical measurement architecture 10 according to a second embodiment of the invention.

[0074] According to this embodiment, the aeronautical measurement architecture 10 comprises three anemobaroclinometric measurement channels 11, each of these channels being analogous to that described previously in relation to [Fig. 1]. According to another embodiment, the number of anemobaroclinometric measurement channels 11 is equal to 2 or is strictly greater than 3.

[0075] In particular, each anemobaroclinometric measurement channel 11 comprises a plurality of aeronautical measurement probes 12 and a computer 14, as explained previously.

[0076] Unlike the previous embodiment, the monitoring system 16 is distributed at least partially between the different anemobaroclinometric measurement channels 11.

[0077] In particular, according to the embodiment of [Fig.2], the monitoring system 16 comprises three input modules 21. Each of the input modules 21 is integrated into one of the channels 11 and allows the receiving of consumption data from the heating means of the probes 12 of this channel 11.

[0078] The monitoring system 16 further includes a centralized processing module 22 and a centralized output module 23. The centralized processing module 22 is similar to the one described previously but allows the consumption data from all the input modules 21 to be received and analyzed.

[0079] The output module 23 is also analogous to that described previously.

[0080] According to this embodiment, the processing module 22 and the output module 23 can be integrated or form a computer independent of each of the input modules 21.

[0081] Furthermore, according to this embodiment, the processing module 22 can be associated with a centralized input module allowing for the centralized acquisition of external data corresponding, for example, to anemobarometric and / or meteorological information.

[0082] The monitoring system 16 as described in relation to each of the embodiments of the architecture 10 makes it possible to implement a monitoring process of the operation of probes 12. This process will henceforth be described with reference to [Fig.3] which presents a flowchart of its steps.

[0083] It is initially assumed that all 12 probes are in operation and that the heating means of these 12 probes are activated. The measuring means associated with these heating means therefore provide consumption data relating to the electrical consumption of these heating means.

[0084] During an initial step 110, the input module or modules 21 acquire all the consumption data, advantageously in real time.

[0085] During this step 110, the input module or each input module 21 can also acquire external data corresponding for example to anemobarometric and / or meteorological information relating to the surroundings of the aircraft.

[0086] At the end of this step, the input module or modules 21 transfers all the acquired data to the processing module 22.

[0087] In a subsequent step 120, the processing module 22 analyzes all the received data in order to determine at least one similarity relationship between the consumption data relating to different probes 12. Such a similarity relationship advantageously has a value calculated based on at least some of the received data.

[0088] In particular, the similarity relation or relations represent at least one of the elements chosen from the group comprising:

[0089] - the difference between the corresponding consumption data;

[0090] - the joint evolution of the corresponding consumption data.

[0091] The similarity relation or relations can take a more complex form, for example one or more mathematical functions and / or an artificial intelligence algorithm.

[0092] More generally, the similarity relationship or relationships present a mathematical model allowing the similarity of at least two consumption data relating to different probes to be characterized.

[0093] Advantageously, each similarity relationship is determined between a pair of consumption data. In other words, each similarity relationship is determined for a pair of probes. However, in other embodiments, at least one similarity relationship is determined for N probes, where N is strictly greater than 2.

[0094] The number of similarity relationships and the consumption data used for their determination depend in particular on the number of probes and anemobaroclinometric measurement channels considered and on the nature of the probes considered.

[0095] Thus, for example, when only one anemobaroclinometric measurement channel 11 is considered (as is for example the case in the embodiment of [Fig.1]), the processing module 22 determines a similarity relationship between the consumption data corresponding to a pair of probes 12 of the same nature and a similarity relationship between the consumption data corresponding to at least one pair of probes 12 of different natures.

[0096] In particular, the processing module 22 can determine a similarity relationship between the consumption data relating to the two static probes explained in relation to [Fig.1].

[0097] This similarity relationship can take the form of a difference between these data. In other words, it can be written as follows:

[0098] I P_Ps_r - P_Ps_l I

[0099] where the values ​​P_Ps_r and P_Ps_l correspond to the power consumed respectively by the first static probe (i.e. probe right side, the index "r" corresponding to the right side of the aircraft) and by the second static probe (i.e. probe left side, the index "1" corresponding to the left side of the aircraft).

[0100] In addition, the processing module 22 can determine a similarity relationship between the consumption data relating to a pair of probes of different natures, such as for example the temperature probe and the Pitot probe.

[0101] This similarity relationship can take the form of a joint evolution between these data. In other words, it can be written as follows:

[0102] I P_Pt / P_Pt_ref - P_TAT / P_TAT_ref I

[0103] and

[0104] dP_Pt / dt * dP_TAT / dt > 0

[0105] where the values ​​P_Pt and P_TAT correspond to the power consumed respectively by the first Pitot probe and the temperature probe and the values ​​P_Pt_ref and P_TAT_ref correspond to reference values.

[0106] A similar joint evolution relationship can be determined for any other pair of probes of different natures, such as for example the angle of incidence probe and the Pitot probe.

[0107] When several anemobaroclinometric measurement channels 11 are considered (as is for example the case in the embodiment of [Fig.2]), the processing module 22 advantageously determines a similarity relationship between the consumption data corresponding to each pair of probes of the same nature from the different channels.

[0108] Thus, in the example of [Fig. 2], it is possible to consider several triplets of probes of the same type and originating from different pathways. For each triplet, it is possible to determine three similarity relations for each pair of probes in that triplet. triplet. Advantageously, in such a case, each similarity relation represents a difference between the corresponding values.

[0109] Alternatively, according to one embodiment, the processing module 22 determines a similarity relationship between consumption data corresponding to probes of different types and from different channels. An example of such a relationship can be analogous to the joint evolution relationship, as explained in relation to a single anemobaroclinometric measurement channel 11.

[0110] In a subsequent step 130, the processing module 22 compares each similarity relationship with a predetermined threshold.

[0111] Each predetermined threshold is advantageously chosen according to the nature of the similarity relationship as well as the nature of the consumption data used to determine it.

[0112] Each threshold can be predetermined, for example, at a stage of aircraft design or at a stage of flight testing.

[0113] Each threshold can also be determined or adjusted according to the anemobarometric and / or meteorological information received by the processing module 22. This determination or adjustment can, for example, be done substantially in real time.

[0114] Furthermore, each threshold can be determined using a mathematical model, for example an artificial intelligence algorithm, such as a machine learning algorithm. The learning can be carried out, for example, using an existing database relating, for example, to the electrical consumption of heating systems during flight tests.

[0115] In the example above, where the similarity relationship represents a difference between the values ​​P_Ps_r and P_Ps_l, the threshold can, for example, be chosen to be equal to 0.05*max(P_Ps_r, P_Ps_l), that is, equal to the coefficient 0.05 multiplied by the maximum value between the two values ​​P_Ps_r and P_Ps_l. Thus, in this example, the difference must be strictly less than this threshold:

[0116] I P_Ps_r - P_Ps_l I < 0.05*max (P_Ps_r, P_Ps_l).

[0117] Similarly, in the example of the joint evolution of the values ​​P_Pt and P_TAT, a threshold S can be chosen so that the corresponding similarity relation is strictly less than this threshold, that is to say:

[0118] I P_Pt / P_Pt_ref - P_TAT / P_TAT_ref I <S.

[0119] In some examples, several threshold levels (for example two) for the same similarity relationship may be chosen in order to avoid inappropriate alerts and alarms.

[0120] In a subsequent step 140, the processing module 22 detects a malfunction of the heating means based on the result of the previous comparison or each previous one.

[0121] For example, when a similarity relationship is outside a range determined by one or more corresponding thresholds, a malfunction of the heating means is detected.

[0122] This anomaly can then be communicated via output module 23 to any interested system.

[0123] Advantageously, in the event of detection of an anomaly, the processing module 22 further determines the probe or each probe 12 or at least the channel or each channel 11, which is the origin of this anomaly.

[0124] For this purpose, the processing module 22 analyzes all the similarity relationships whose values ​​are outside the range determined by one or more corresponding thresholds, and then deduces the probe 12 which led to these anomalies.

[0125] For example, when at least two similarity relationships calculated in relation to two pairs including the same probe have their values ​​outside the range determined by one or more thresholds, it could be considered that this probe and in particular its heating means are faulty.

[0126] In certain cases, to confirm this failure, the processing module 22 verifies that the similarity relationship determined between the two other probes of said pairs has its value within the range defined by one or more corresponding thresholds. Otherwise, it may be considered that the corresponding thresholds are not suitable or that two probes simultaneously exhibit a failure in their heating means.

[0127] Of course, any other technique allowing certain isolation of a probe with faulty heating means can be used, depending in particular on the nature of the corresponding similarity relations.

[0128] During a final step 150, the output module 23 communicates the detected anomaly and possibly the identifier of the probe with the faulty heating means to any interested system.

[0129] It is therefore understood that the present invention has a number of advantages.

[0130] First, the invention makes it possible to detect a fault in the heating means of a probe in a particularly simple way by comparing the consumption data relating to different probes. For this, no additional sensor, such as a temperature sensor, is required within each probe. The electrical consumption data, for its part, can be obtained easily, even using remote measuring means.

[0131] Furthermore, the thresholds for all similarity relationships can be precisely determined using, for example, machine learning algorithms. These thresholds can also be recalculated or readjusted during the operation of the monitoring system, for example in real time using external data. This makes the monitoring system particularly flexible.

Claims

Demands

1. Method for monitoring the operation of a plurality of aeronautical measuring probes (12), each probe (12) comprising heating means, the method comprising the following steps: - acquisition (110) of a plurality of consumption data, each consumption data characterizing an electrical consumption of the heating means of one of the aeronautical measuring probes (12); - determination (120) of at least one similarity relationship between at least two consumption data; - comparison (130) of the or each similarity relationship with a threshold; - detection (140) of an operating anomaly based on the result of the or each comparison.

2. A method according to claim 1, wherein each consumption data comprises at least one of the elements selected from the group comprising: - the voltage of the current supplying the heating means of the corresponding aeronautical measuring probe (12); - the intensity of the current supplying the heating means of the corresponding aeronautical measuring probe (12); - the power consumed by the heating means of the corresponding aeronautical measuring probe (12).

3. Method according to claim 1 or 2, wherein each consumption data characterizes a real-time electrical consumption of the heating means of the corresponding aeronautical measuring probe (12).

4. A method according to any one of the preceding claims, wherein the similarity relationship corresponds to at least one of the elements selected from the group comprising: - the difference between the corresponding consumption data; - the joint evolution of the corresponding consumption data.

5. A method according to any one of the preceding claims, wherein the threshold or each threshold is determined by an artificial intelligence algorithm.

6. A method according to any one of the preceding claims, wherein the threshold or each threshold is determined based on anemobarometric and / or meteorological information, preferably from measuring equipment located in an aircraft carrying said aeronautical measuring probes (12) and / or from surrounding aircraft and / or remote facilities.

7. A method according to any one of the preceding claims, wherein at least one similarity relationship is determined between consumption data from aeronautical measuring probes (12) belonging to the same anemobarometric channel (H).

8. A method according to any one of the preceding claims, wherein at least one similarity relationship is determined between consumption data from aeronautical measuring probes (12) belonging to different anemobarometric channels (11).

9. A method according to any one of the preceding claims, wherein at least one similarity relationship is determined between consumption data from aeronautical measuring probes (12) measuring the same physical quantity or different physical quantities.

10. A method according to any one of the preceding claims, wherein the step of detecting a malfunction includes determining a faulty aeronautical measuring probe (12) based on the results of comparisons of at least two similarity relationships comprising one or more consumption data from this aeronautical measuring probe (12).

11. Monitoring system (16) comprising technical means (21, 22, 23) configured to implement the method according to any one of the preceding claims.

12. Aeronautical measurement architecture (10) comprising: - a plurality of aeronautical measurement probes (12); - a monitoring system (16) according to claim 11.