determination of a risk of the appearance of electric arcs in an electrical circuit of an aeronautical system

Abstract

Method for determining a risk of occurrence of an electric arc in an electrical circuit of an aeronautical system, comprising iterative steps (Pon) of: extraction (S3) of a sample of an electric current corresponding to a first time window, said electric current being continuously measured in said electrical circuit; evaluation (S4) of at least one correlation measurement between said sample and a set of predetermined signals, each signal being representative of an electric arc; prediction (S6), as a function of said at least one correlation measurement, of a risk of occurrence of an electric arc at a time subsequent to said first time window. Figure for the abstract: Fig. 3

Description

Title of the invention: determination of a risk of the appearance of electric arcs in an electrical circuit of an aeronautical system FIELD OF THE INVENTION

[0001] The present invention relates to the determination of a risk of an electric arc occurring in an electrical circuit. It applies in particular to the field of aeronautics and systems embedded in an air vehicle.

[0002] Climate change is a major concern for many legislative and regulatory bodies around the world. Indeed, various restrictions on carbon emissions have been, are being, or will be adopted by various states. In particular, an ambitious standard applies both to new types of aircraft and those in circulation requiring the implementation of technological solutions in order to make them compliant with current regulations. Civil aviation has been mobilizing for several years now to make a contribution to the fight against climate change.

[0003] Technological research efforts have already made it possible to significantly improve the environmental performance of aircraft. The Applicant takes into consideration the impact factors in all phases of design and development to obtain less energy-intensive, more environmentally friendly aeronautical components and products whose integration and use in civil aviation have moderate environmental consequences with the aim of improving the energy efficiency of aircraft.

[0004] Consequently, the Applicant is constantly working to reduce its negative climate impact by using methods and operating virtuous development and manufacturing processes and minimizing greenhouse gas emissions to the minimum possible in order to reduce the environmental footprint of its activity.

[0005] It is in such a context that the problem of determining a risk of the appearance of an electric arc in an electrical circuit on board an aircraft arises, which can in particular cause premature damage to the aircraft and harm its energy efficiency.

[0006] An electric arc is a self-sustaining discharge with high current.

[0007] Two types of electrical arcs that may occur in an aeronautical environment can be distinguished: breaking arcs, present in the contactors when a circuit is opened or closed, and fault arcs that may appear unexpectedly on all the components of the electrical chain. These These can cause severe damage to equipment, systems and even the structure of the aircraft. This is therefore an important point of vigilance.

[0008] Furthermore, fault arcs can be of two types depending on their position on the electrical circuit: parallel arcs and series arcs. A parallel arc is located in parallel with the load (which causes an increase in current because a preferential low-impedance path is created) while a series arc is located in series with the load (which causes, on the contrary, a drop in current because the impedance of the circuit is increased).

[0009] On an electrical distribution network, series arcs are always more complex to detect than parallel arcs.

[0010] Indeed, from the point of view of the electrical signature, parallel arcs generate a strong current draw, which allows overcurrent protection systems to detect them effectively and protect the line. On the other hand, in the case of a series arc, the current is only slightly impacted. This is explained by the fact that an electric arc is a low impedance fault. Consequently, when a series arc is present in the electrical system, the current will only suffer a slight fluctuation, more precisely a small percentage reduction of its nominal value. It is for this main reason that they are more complex to identify by currently existing means.

[0011] In addition, the waveform of the electrical signal from the network is also a factor that can complicate detection. Regarding AC voltage networks, the passage through 0V is the moment in the half-cycle when the electric arc can no longer be maintained. When a series arc appears on such a type of network, this moment can then result in an open circuit leaving the line current at 0A for a short time (called "current shoulders"), promoting the self-extinction of the arc at each half-cycle. On the contrary, when the waveform is continuous (DC network for "direct current" in English), this phenomenon no longer exists and the arc can no longer take advantage of this shoulder to extinguish itself naturally.

[0012] On systems embedded in aircraft, these problems are currently partly resolved, or mitigated, by several factors: - the distributed voltage levels are generally a maximum of 230 V (at 400 Hz in fixed frequency or between 400 and 800 Hz in variable frequency), which reduces the impact of electric arcs; - the distribution of an alternating waveform (AC) also allows the self-extinction of the art to be promoted at each half-period, when the voltage passes through 0 V. - voltage levels are generally lower, around 28 VDC. - passive protections can be used to limit the consequences of possible fault arcs: choice of materials resistant to these phenomena, use of segregation rules for optimal placement of these different elements, etc. - finally, active protections can also be provided, such as for example arc detection mechanisms and line opening in the event of an arc being detected. The active protections currently used can detect most parallel arcs but not series arcs for which no active protection has been deployed to date.

[0013] However, recent work on aircraft electrification proposes a distribution of continuous waveforms (DC) for high voltage levels, which can reach kilovolts. These are called HVDC (High Voltage Direct Current) networks. This paradigm shift obviously calls into question the passive protection strategy previously mentioned.

[0014] Furthermore, the series electric arc must also be taken into account, in the same way as the parallel arc, because the damage associated with the generation of higher power faults subjected to direct voltage risks damaging the aircraft and its on-board systems, and could even impact the safety of passengers and crew.

[0015] There are some proposals aimed at detecting an electric arc on a power line in order to isolate it (by opening the circuit). However, these proposals must respect constraints of: - Reliability: systematic detection in all circumstances of dangerous electrical phenomena, more often called “feared phenomena”. In other words, it is a question of having a high “true positive” rate, close to 100%. - Robustness: the active protection mechanism must be immune to any event other than the one for which it was designed. In other words, the rate of "false positives" must be as low as possible, i.e. close to 0%.

[0016] So far, these proposals show shortcomings either in terms of reliability or in terms of robustness.

[0017] In an aerial vehicle (airplane, helicopter, drone, etc.), the electrical distribution is carried out by cables and interconnection bars (or "busbars" according to the usual English terminology).

[0018] The connection between separate distribution means, or vectors, is made via connectors or terminal blocks.

[0019] An example of a terminal block is illustrated in Figures 1A and 1B.

[0020] [Fig.1A] represents a "top" view of a terminal block 10 in which a cable 20 is connected by means of lugs 11. The cable is held in contact with the lug by tightening a nut 12 on a stud secured to a base of the terminal block, or to a screw rod.

[0021] [Fig.lB] shows a cross-sectional view of a connection B1 of the same terminal block 10, in which are also shown an insulator 14 enclosing the connections in the form, for example, of a box, and a support 15 which can be integral and rigidly connected to the aerial vehicle. The view of [Fig.lB] shows the stud 13 onto which the nut 12 is tightened to hold the cable 20 in place.

[0022] The vibrations generated by the aerial vehicle in operation (in flight or while taxiing) are transmitted to the terminal block 10 via the support 15. Due to these vibrations, it is possible for a connector or a terminal block to become loose.

[0023] If, at a given moment, even very short, the physical connection between two distribution means (cables) is no longer ensured by the initial tightening, a series arc can occur, between the terminal 11 and the nut 12.

[0024] The length and / or repetition of the serial arcs can cause damage to the junction, or even other elements of the aerial vehicle.

[0025] These connections via terminal blocks are a major source of series arc generation within aerial vehicles.

[0026] It is therefore important to avoid series arcs, or at least substantially reduce their occurrence, within electrical circuits and in particular within terminal blocks and other types of connections present in electrical distribution. Summary of the invention

[0027] The invention aims to improve the state of the art. In particular, it makes it possible to avoid or reduce the occurrence of series arcs in the electrical circuits on board an air vehicle, which makes it possible to improve both the safety of the vehicle and its crew, and the longevity of the various circuits and devices on board. The invention thus has a virtuous effect of reducing the environmental impact of aircraft.

[0028] According to a first aspect, the present invention can be implemented by a method for determining a risk of an electric arc appearing in an electrical circuit of an aeronautical system, comprising iterative steps of: - extraction of a sample of an electric current corresponding to a first time window, said electric current being measured continuously in said electric circuit; - evaluation of at least one correlation measurement between said sample and a set of predetermined signals, each signal being representative of an electric arc; - prediction, based on said at least one correlation measurement, of a risk of an electric arc appearing at an instant subsequent to said first time window.

[0029] According to preferred embodiments, the invention comprises one or more of the following features which can be used separately or in partial combination with each other or in total combination with each other: - said at least one correlation measurement comprises a measurement of temporal correlation between values ​​of said sample and values ​​of said set of predetermined signals. - said at least one correlation measurement comprises a measurement of frequency correlation between values ​​of the frequency transforms, respectively, of said sample and of said set of predetermined signals. - said at least one correlation measure is determined by a Pearson correlation measure and / or by a Spearman correlation measure. - the prediction of a risk of an electric arc occurring generates a cut in said electrical circuit. - said set of predetermined signals is previously obtained by data acquisition steps comprising an identification of a voltage measurement corresponding to said electrical circuit exceeding a threshold value representative of the presence of an electric arc; and a storage of a signal corresponding to intensity measurements in a second time window corresponding to said identification. - said data acquisition steps are carried out on a remote platform, and all of the signals stored by said data acquisition steps are stored within an aerial vehicle for the implementation of a method for determining a risk of the occurrence of an electric arc as previously described.

[0030] Another aspect of the invention relates to a computer program comprising instructions for implementing a method as previously described when executed on an information processing platform.

[0031] Another aspect of the invention relates to a device for determining a risk of an electric arc appearing in an electrical circuit of an aeronautical system, suitable for - extracting a sample of an electric current corresponding to a first time window, said electric current being measured continuously in said electric circuit; - evaluating at least one correlation measurement between said sample and a set of predetermined signals, each signal being representative of an electric arc; and - predicting, based on said at least one correlation measurement, a risk of the appearance of an electric arc at an instant subsequent to said first time window.

[0032] Another aspect of the invention relates to an aerial vehicle comprising at least one device as previously defined.

[0033] The invention thus makes it possible to improve the safety of on-board electrical circuits, in particular by avoiding the appearance of faulty electrical arcs, or at least by substantially reducing their appearance.

[0034] In particular, it makes it possible to predict the occurrence of an electric arc (i.e. to determine a risk of such an occurrence) in order to anticipate, if necessary, an action intended to prevent their actual occurrence. In this way, the various disadvantages linked to the occurrence and recurrence of electric arcs can be eliminated or considerably reduced.

[0035] Other characteristics and advantages of the invention will appear on reading the following description of a preferred embodiment of the invention, given by way of example and with reference to the appended drawings. BRIEF DESCRIPTION OF THE FIGURES

[0036] The attached drawings illustrate the invention: Figures 1A and 1B schematically illustrate a terminal block allowing the connection of electrical distribution vectors within an aerial vehicle.

[0037] Figures 2A, 2B, 2C, 2D and 2E illustrate an example of an electrical circuit and current and voltage measurements on this circuit.

[0038] [Fig.3] represents an illustrative flowchart of a method according to a possible implementation.

[0039] [Fig.4] illustrates an example of application of the method, according to one embodiment.

[0040] [Fig.5] illustrates an example of a device for determining a risk of electric arc in an electrical circuit, according to one embodiment.

[0041] DETAILED DESCRIPTION OF EMBODIMENTS OF THE INVENTION

[0042] Studies undertaken by the inventors have made it possible to update the appearance of pre-disruptive phenomena, or “precursors”, prior to the appearance of a series electric arc, at least in the case of series arcs caused by a problem with tightening a connector. These phenomena take the form of short sparks, of much lower power than that of electric arcs, so that they are not perceptible to the naked eye or with conventional instruments.

[0043] This phenomenon was discovered by using a high-speed camera. This camera can be designed to capture 3,500 to 500,000 images per second depending on the resolution to film a time window around an electric arc caused by a loose connector. The film thus produced makes it possible to identify the artifacts of these pre-disruptive phenomena.

[0044] A first idea is to use this phenomenon to predict the appearance of an electric arc. A statistical study has finally made it possible to demonstrate that the appearance of these pre-disruptive phenomena resulted in the subsequent appearance of an electric arc, with a high percentage, of the order of 90% on the basis of the tests carried out. Furthermore, even without the appearance of a subsequent electric arc, the detection of these pre-disruptive phenomena is interesting because they can damage the connectors in the long term.

[0045] [Fig.2A] illustrates an electrical circuit 50 which can be installed on a platform remote from an aerial vehicle (i.e. outside of it), but reproducing a set of main characteristics of the electrical circuit which one seeks to protect within the aerial vehicle.

[0046] This electrical circuit 50 comprises a current source, typically a direct current source, 40, a terminal block 10' similar to the terminal block 10 present in the aerial vehicle, and a load 30 similar to the load connected to the terminal block 10 of the aerial vehicle. This circuit must be sufficiently similar so that the measurements carried out on it are representative of the behavior of the electrical circuit on board the aerial vehicle.

[0047] At least one connection of the terminal block 10' is poorly screwed or poorly adjusted, so as to cause electric arcs.

[0048] [Fig.2C] represents the behavior of the voltage U at the terminals of terminal block 10'.

[0049] The terminal block having a very low impedance, the voltage is nominally zero, but significant voltage peaks (20-30 V) appear during electric arcs. We note, in [Fig.2C], the appearance of a succession of electric arcs over time T.

[0050] [Fig.2E] illustrates the behavior of the voltage U on a smaller scale, in the zone Z.

[0051] We note that the voltage is constant before the appearance of the voltage peak corresponding to the electric arc, at t=0.028 seconds.

[0052] It therefore appears that the measurement of the voltage does not allow pre-disruptive phenomena to appear.

[0053] The inventors were then interested in the behavior of the intensity I of the electric current circulating in the electric circuit, over time t.

[0054] [Fig.2D] illustrates a smaller scale view of the zone Z shown in [Fig.2B], these two figures representing the behavior of the intensity I of the current over time.

[0055] We can then notice that the intensity I experiences a strong variability between 39 and 39.5 A prior to the current drop corresponding to the electric arc at t=0.028 s.

[0056] In other words, it is possible to analyze the intensity I of the electric current in order to detect pre-disruptive phenomena announcing the subsequent appearance of an electric arc.

[0057] Furthermore, a more detailed analysis makes it possible to highlight a correlation between the intensity signal I during these pre-disruptive discharges and during an electric arc, both in the temporal behavior (rapid drop followed by a rapid rise) and in the frequency behavior.

[0058] If a correlation measurement is determined from the behavior of the intensity during a pre-disruptive phenomenon, this will always be higher with the behavior during an electric arc than with the nominal behavior (i.e. without the presence of an electric arc or pre-disruptive phenomena).

[0059] These different observations and analysis results can be used to define a method for determining a risk of an electric arc appearing in an electrical circuit of an aeronautical system.

[0060] Determining a risk of occurrence consists, in other words, in predicting or forecasting, with a high level of probability, the occurrence of an arc before it occurs, so that mechanisms can be implemented to prevent it from occurring.

[0061] [Fig.3] represents an illustrative flowchart of a method according to a possible implementation of this method.

[0062] According to one embodiment, this method consists of two phases. - an “offline” or ground phase, Poff, of data acquisition, - an “on-line” phase, or in operation of the aerial vehicle, Pon, of determination of a risk of an electric arc occurring in an electrical circuit of this aerial vehicle, based on data acquired during the offline phase.

[0063] According to other embodiments, the data may be acquired by other means. In particular, they may be stored in a reference database. which can be used without going through an acquisition phase for the aerial vehicle operator. This database can be shared by different operators.

[0064] The offline phase Poff can be implemented on a platform designed to generate a current behavior similar to that of the electrical circuit considered in the aerial vehicle. It is therefore adapted so that the acquired data can be used for the online phase Pon. In particular, the platform has a load and a terminal block similar to those of the on-board electrical circuit.

[0065] According to one embodiment, this platform makes it possible to constitute a set of signals, or patterns, representative of pre-disruptive phenomena.

[0066] To do this, a terminal block with loosely tightened terminals can be installed on a vibrating structure suitable for simulating the vibrations of an aerial vehicle. By powering the system, the vibrations cause the generation of electric arcs.

[0067] Preferably, the simulation conditions on the platform must reproduce as faithfully as possible the conditions of the aircraft in flight: in particular aeronautical housings, cables, pressure variation, etc.

[0068] This offline phase Poff may in particular include a step of identification, SI, of a voltage measurement corresponding to the electrical circuit, exceeding a threshold value representative of the presence of an electric arc.

[0069] Indeed, as seen previously, electric arcs are associated with voltage peaks. These are easily detectable by carrying out a continuous measurement of the voltage level and comparing it to a threshold value.

[0070] To the extent that the voltage across an electrical connection (of zero or very low impedance) is zero, this threshold value may be a few volts. In order to avoid false alarms due to accidental fluctuations in the voltage, this threshold must not, however, be too close to zero. An optimal value can be determined experimentally, depending on the electrical circuit considered, and in particular the direct current source used. For example, a value close to half the peak value of the voltage can be used (here 15 V).

[0071] The identification of an electric arc can trigger a step S2 of storing a signal corresponding to intensity measurements in a second time window.

[0072] This second time window should preferably contain the current drop. It can be of the order of 1 ms. Since we are looking at a mathematical correlation with the current drop, it must be represented entirely in the window. Its exact position is not decisive.

[0073] The storage may include sampling a continuous measurement of the intensity to provide a set of discrete values ​​which may then be stored. The sampling frequency of the signals can be 500 kHz (current sensor at 1 MHz bandwidth.

[0074] As pre-disruptive phenomena are difficult to detect directly, the off-line phase provides a step SI for identifying electric arcs (or more precisely for identifying a voltage measurement exceeding a threshold value representative of the presence of an electric arc) and a step S2 allowing the storage of a signal in a (second) time window corresponding to the identification, i.e. in which this electric arc is identified. As seen previously, a correlation is observed between the electrical behavior during the occurrence of an electric arc and a pre-disruptive phenomenon. Therefore, the signals, or patterns, corresponding to these detected arcs can then be used to determine the presence of pre-disruptive phenomena during the on-line phase Pon.

[0075] This allows us to circumvent the difficulty of directly detecting disruptive phenomena.

[0076] It is possible to store a set of signals, or patterns, each corresponding to the behavior of the electric current when an electric arc appears for the electrical circuit in question.

[0077] These sets of stored signals can be transferred into a memory associated with a device for monitoring an electrical circuit on board the aerial vehicle. This transfer can be done by any means, conventional or not.

[0078] This monitoring device is adapted to enable the determination of a risk of an electric arc appearing in an electrical circuit of an aeronautical system of the air vehicle.

[0079] [Fig.5] illustrates an embodiment of a determination device 60 of a risk of an electric arc appearing in an electrical circuit 50a. In this example, the device 60 comprises a sensor 61 making it possible to continuously measure the electrical intensity and voltage within the monitored electrical circuit 50a, a calculator 62 and a memory 63.

[0080] The computer 62 has computing power enabling calculations of correlation measurements to be carried out, including frequency correlation (involving a Fourier transform) on an ongoing basis.

[0081] The memory 63 is adapted to contain predetermined signals, or patterns, which can come from a remote platform (outside the aerial vehicle) 70. The transfer of data can be carried out by any means of communication, typically during an initialization or updating phase of the various electronic circuits of the vehicle.

[0082] This on-board device 60 for determining a risk of an electric arc appearing in the associated electronic circuit is configured to implement the online phase, Pon, previously mentioned and illustrated in the embodiment of [Fig.3]. This Pon phase comprises iterative steps allowing continuous monitoring of the electric current and detection at any time of a risk of an electric arc occurring in order to allow, if necessary, anticipated action to prevent this occurrence. In the embodiment illustrated in [Fig.3], this iterative aspect is represented by the loop connecting step S6 to step S3.

[0083] Step S3 comprises extracting a sample of an electric current corresponding to a (first) time window, said electric current being continuously measured in said electric circuit.

[0084] This extraction is preferably carried out with a current sensor having the same characteristics as that used, where appropriate, for the offline phase of Poff data acquisition.

[0085] The first time window corresponding to a current measurement corresponding to the sample preferably has the same size (i.e. the same number of sampled discrete values) as the second time window, i.e. the one corresponding to the signals, or patterns, stored during the offline phase of acquisition of the Poff data. This makes it possible to facilitate and accelerate subsequent correlation calculations.

[0086] This sample consists of, or includes, measurements of the intensity I of the electric current. Thus, according to one embodiment, the extracted sample includes a series of intensity measurements, the number of which depends on the size of the time window and the sampling frequency.

[0087] For each extracted sample, a step S4 is triggered consisting of evaluating at least one correlation measurement between this sample and all of the predetermined signals, or patterns, stored in a memory. These stored signals may typically be those provided during the data acquisition phase. As seen previously, these signals, or patterns, are representative of an electric arc, due to the data acquisition process corresponding to the off-line phase Poff.

[0088] The extracted sample can also be stored to allow correlation calculation. It can then be deleted, or overwritten by storing a subsequent sample.

[0089] A possible correlation measurement is a temporal correlation measurement, between values ​​of the sample and values ​​of the set of stored signals. In particular, a correlation measurement can be determined between the sample and each of the signals available in the stored set. This temporal correlation measurement corresponds to step S41 in the example of [Fig.3].

[0090] According to one embodiment, this temporal correlation measure r^y is a Pearson correlation measure.

[0091] In the preferred case where the sample and the stored patterns have the same size, i.e. they comprise the same number n of discrete values, this Pearson correlation measure can be written:

[0092] i\~'^ 2 1 x^L^-yy-

[0093] x represents the sample. x; is the ith intensity value of that sample. Similarly y represents a predetermined signal, or pattern, and y; is the ith intensity value of that pattern. * and represent the average values ​​of the intensities of, respectively, sample x and pattern y.

[0094] According to another embodiment, this temporal correlation measure is a Spearman correlation measure.

[0095] Spearman correlation is the non-parametric equivalent of Pearson correlation. It also evaluates the relationship between two sequences of values, but it does not use the data values ​​but their rank, Rx, Ry respectively, for the sample and a pattern.

[0096] Before calculating the Spearman correlation, the data must be transformed into ranks. To do this, the data are sorted in ascending order and the values ​​are replaced by their ranks. When values ​​are identical, the average of their ranks is used. Once the data has been transformed into ranks, the Spearman correlation measure can be calculated using the same formula as that used to calculate the Pearson correlation measure rx>y but using the ranks.

[0097] Thus, we can write:

[0098] t _

[0099] Another possible correlation measure is a frequency correlation measure based on the values ​​of the frequency transforms, respectively, of the sample and the set of predetermined signals. In particular, a correlation measure can be determined between the sample and each of the signals available in the stored set. This frequency correlation measure corresponds to step S42 in the example of [Fig.3].

[0100] This frequency transform is typically a Fourier transform. According to this embodiment, we can therefore calculate the modulus of the Fourier transform of the sample x, noted x , and of the patterns stored in the memory, noted y , and then calculate the Pearson or Spearman correlation, r^, between these two quantities.

[0101] For the Pearson correlation, we can then write, with p the number of frequencies:

[0102]

[0103] And for the Spearman correlation, we can write, with p the number of frequencies:

[0104] f r ' y ~

[0105] According to one embodiment, in a step S5, an aggregated correlation measurement can be determined from a plurality of correlation measurements, for example from a time correlation measurement and a frequency correlation measurement.

[0106] For example, we can write:

[0107]

[0108] These correlation measures can be determined for each stored pattern. Each electric arc can indeed have several different characteristics, and the constitution of a set of patterns of substantial size makes it possible to maximize the probability of detecting pre-disruptive phenomena.

[0109] From a set of correlation measurements rx^' determined for a set of predetermined signals, or patterns, a single correlation measurement can be derived, for example by calculating the maximum value obtained, or the average value, etc.

[0110] The method then provides a step S6 of predicting a risk of an electric arc appearing at a time subsequent to the time window corresponding to the extracted sample (on which the correlation measurement was calculated) as a function of this correlation measurement.

[0111] To do this, one possible implementation consists of predicting the appearance of an electric arc as soon as a correlation measurement exceeds a given threshold.

[0112] Another possible implementation consists of subjecting the prediction of the appearance of an electric arc to a plurality of exceedances of a given threshold. For example, if the value of the correlation measurement exceeds this threshold for example 3 times, then the appearance of a fault arc can be predicted.

[0113] The threshold may, for example, correspond to the median value of a correlation rate, i.e. 0.5.

[0114] The number of overshoots taken into account must not be too high since this mechanically delays the moment when the prediction can be made and therefore the proximity of the moment when the electric arc can actually occur. The figure of 3 given previously seems to be a good compromise between the optimization of the risk estimation and the need to estimate this risk sufficiently early and, at a minimum, before the occurrence of the electric arc.

[0115] According to one embodiment, step S6 makes it possible to predict a risk of occurrence which is not binary, but a probability value. This probability can be linked to the value, or values, of the correlation measurement, without going through thresholding. In the case where a single correlation measurement is taken into account, the risk of occurrence can be equal to the correlation measurement. If several correlation measurements are taken into account (for example 3), the risk of occurrence can be the average of these measurements.

[0116] When in step S6 no risk is predicted, the method loops back to step S3 to extract a new sample, to which the same steps will be applied. Thus, continuous monitoring of the electric current can be carried out.

[0117] When in step S6, a risk (non-zero) is predicted, then a step S7 of triggering a preventive action can be carried out.

[0118] This step S7 may comprise the automatic sending of an instruction to cut off the electric current to a cut-off system associated with the monitored electric circuit.

[0119] Thus, the electric arc whose imminent occurrence was predicted can be prevented from actually appearing in said circuit. It is therefore possible to suppress the appearance of electric arcs, and in particular series arcs which are difficult to detect as previously explained.

[0120] Also, an alert message can be retransmitted to an interface allowing an operator to be informed of an anomaly. A human operator can then intervene to remedy this fault (activation of a possible redundant system following the shutdown of the faulty system, interventions to repair the fault, etc.)

[0121] It may also be noted that the method for determining a risk of occurrence proposed, based on a correlation measurement, also makes it possible to detect the presence of an electric arc. Indeed, in the case where an electric arc occurs (for example because it was not preceded by pre-disruptive phenomena), it will be detected according to the same mechanism as for a pre-disruptive phenomenon because it presents a high correlation with a stored pattern.

[0122] However, as an electric arc denotes abnormal behavior, the appearance of an electric arc is associated with a high probability of the appearance of new arcs in the future. The method described therefore makes it possible to anticipate the appearance of future arcs as soon as one or more “first” electric arcs appear. Thus, according to the same mechanism as for a pre-disruptive phenomenon, detections of electric arc(s) will generate the determination of a risk of the appearance of an electric arc.

[0123] [Fig.4] illustrates an example enabling certain aspects of the proposed method and its advantages to be highlighted.

[0124] This figure illustrates from top to bottom the intensity I and the voltage U measured for a monitored electrical circuit, typically comprising a connection (terminal block, etc.), then a time correlation measure r', a frequency correlation measure rf, and an aggregate correlation measure r.

[0125] In zone Zl, no arc is present because the voltage U does not exceed the threshold (for example 15V). However, it is noted that the time correlations r' and frequency correlations rf are higher than the nominal values ​​(close to zero). As a result, the aggregated correlation r exceeds the threshold rs 3 times. According to one implementation, this triple exceedance generates the prediction of a risk of electric arc in the future.

[0126] Normally, according to the proposed method, in the online step Pon, the prediction of such a risk should generate the cutting of the electric current. In the example illustrated, for explanatory purposes, no cut is made, and the electric circuit remains powered.

[0127] This makes it possible to show that a first electric arc appears in zone Z2, thus confirming the prediction previously made. This example clearly demonstrates the effectiveness of the proposed method, which makes it possible to predict the appearance of electric arcs and to avoid their appearance by anticipating their occurrence by cutting the electrical circuit.

[0128] Of course, the present invention is not limited to the examples and the embodiment described and shown, but is defined by the claims. It is in particular susceptible of numerous variants accessible to those skilled in the art.

Claims

Claims

1. Method for determining a risk of occurrence of an electric arc in an electrical circuit of an aeronautical system, comprising iterative steps (Pon) of: extraction (S3) of a sample of an electric current corresponding to a first time window, said electric current being continuously measured in said electrical circuit; evaluation (S4) of at least one correlation measurement between said sample and a set of predetermined signals, each signal being representative of an electric arc; prediction (S6), as a function of said at least one correlation measurement, of a risk of occurrence of an electric arc at an instant subsequent to said first time window.

2. Method according to the preceding claim, wherein said at least one correlation measurement comprises a measurement of temporal correlation between values ​​of said sample and values ​​of said set of predetermined signals.

3. Method according to one of the preceding claims, wherein said at least one correlation measurement comprises a measurement of frequency correlation between values ​​of the frequency transforms, respectively, of said sample and of said set of predetermined signals.

4. Method according to one of claims 2 or 3, wherein said at least one correlation measure is determined by a Pearson correlation measure and / or by a Spearman correlation measure.

5. Method according to one of the preceding claims, in which the prediction of a risk of the appearance of an electric arc generates a cut (S7) of said electric circuit.

6. Method according to one of the preceding claims, in which said set of predetermined signals is previously obtained by data acquisition steps (Poff) comprising: - identification (SI) of a voltage measurement corresponding to said electrical circuit exceeding a threshold value representative of the presence of an electric arc; - storage (S2) of a signal corresponding to intensity measurements in a second time window corresponding to said identification.

7. Method according to the preceding claim, in which said data acquisition steps are carried out on a remote platform, and all of the signals stored by said data acquisition steps are stored within an aerial vehicle for the implementation of a method for determining a risk of the appearance of an electric arc according to one of claims 1 to 5.

8. Computer program comprising instructions for implementing a method according to one of claims 1 to 5, when executed on an information processing platform.

9. Device for determining a risk of an electric arc occurring in an electrical circuit of an aeronautical system, adapted to extract a sample of an electric current corresponding to a first time window, said electric current being continuously measured in said electrical circuit; evaluate at least one correlation measurement between said sample and a set of predetermined signals, each signal being representative of an electric arc; and predict, as a function of said at least one correlation measurement, a risk of an electric arc occurring at a time subsequent to said first time window.

10. Aerial vehicle comprising at least one device according to the preceding claim.

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