Detection and analysis of partial discharges in an electrical signal generated by pulse width modulation (PWM)

Abstract

The invention relates to a method for detecting and analysing a partial discharge (DP) in an electrical signal (1) to be analysed, generated by PWM and originating from an electrical device (10) in an aeronautical environment, the method comprising - a detection phase (S1) comprising a step (E10) of detecting, by means of a sensor (91), the electrical signal (1) to be analysed, and a step (E1) of identifying a possible partial discharge by comparing this electrical signal with at least one signature signal (2) representative of a partial discharge (DP); and - an analysis phase (S2) comprising a step (E4) of decomposing the electrical signal (1) into a sequence of patterns, and a step (E5) of assigning the detected partial discharges (DP) to these patterns.

Description

DESCRIPTION TITLE: Detection and analysis of partial discharges in an electrical signal created by pulse width modulation (PWM) TECHNICAL FIELD

[0001] The present invention relates to the identification of partial discharges under a voltage synthesized by pulse width modulation, PWM. It applies in particular to assisting in the identification of a type of fault in an electrical chain, and in an aeronautical environment.

[0002] A partial discharge, referred to as PD in the following, is a localized electrical discharge which only partially short-circuits the insulating gap separating conductors or electrodes.

[0003] The presence of these discharges leads to accelerated degradation of the insulation, whether liquid, by oxidation, or solid, by erosion, and can lead to significant reliability problems. Beyond even premature wear of the on-board equipment, the recurrence of partial discharges can cause breakdowns that can be critical in the case of an aerial vehicle in flight.

[0004] Until recently, the voltage levels used in aeronautics were not high enough to cause great concern about the existence of these partial discharges, which were unlikely to occur and therefore did little damage to the equipment. Commonly used voltage levels were, for example, in the order of 230 to 400 volts maximum.

[0005] Furthermore, various carbon emissions restrictions have been, are being, or will be adopted by various states. In particular, an ambitious standard applies to both new aircraft types and those currently in operation, requiring the implementation of technological solutions to bring them into compliance with current regulations. Civil aviation has been mobilizing for several years now to contribute to the fight against climate change.

[0006] Technological research efforts have already made it possible to significantly improve the environmental performance of aircraft. The Applicant takes into account consideration of factors impacting 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 impacts with the aim of improving the energy efficiency of aircraft.

[0007] Consequently, the Applicant is constantly working to reduce its 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.

[0008] This ongoing research and development work focuses in particular on the use of electrical technologies to provide propulsion.

[0009] This trend towards hybridization and / or electrification of propulsion systems leads to a growing demand for electrical energy and consequently to an increase in voltage levels. Thus, the voltage levels used on the aircraft electrical network can now exceed 400 volts or even reach one kilovolt. This increase in voltage, accompanied by severe pressure and temperature conditions, increases the risk of these partial discharges occurring.

[0010] Additionally, in some applications, voltages are generated by pulse width modulation (PWM); these voltages are characterized by steep rising and falling edges (high dV / dt derivative), further increasing the probability of partial discharges occurring.

[0011] Where possible, the various components are designed to avoid the occurrence of such partial discharges. However, it is impossible to prevent the occurrence of this phenomenon in the long term, due to the natural wear of components which, in the aeronautical field, are subject to severe constraints, particularly in terms of temperature and pressure.

[0012] Due to the increased risk of partial discharges occurring in harsh environments, and their significant impact on the reliability of on-board equipment, it is necessary to be able to detect and recognize these partial discharges as soon as they appear, reliably and without requiring excessive computing power. important. This last point is all the more important in an embedded system and in an aeronautical context where computing resources may be limited.

[0013] Furthermore, while under sinusoidal voltage the detection of partial discharge is relatively simple, under pulse stress or generated by Pulse Width Modulation (PWM), the noise generated tends to be superimposed on the partial discharge signals, thereby complicating the detection of partial discharges.

[0014] Since discharges have very low charge values, complex and robust measuring devices must be implemented.

[0015] Detection methods exist but are not very easy to implement because they require suitable electronics and high requirements in terms of acquisition frequency, for example. Verification by an expert is also often necessary to confirm whether or not partial discharge is present.

[0016] An aim of the invention is therefore to improve the current proposals of the state of the art by allowing, in particular, the detection then the identification (i.e. the characterization) of a partial discharge in an electrical voltage signal, in particular when it is generated by pulse width modulation, PWM.

[0017] This characterization may notably include a phase-amplitude-frequency analysis, of the PRPD type (“Phase Resolved Partial Discharge”). STATEMENT OF THE INVENTION

[0018] In order to overcome the shortcomings of the state of the art concerning the detection of partial discharges, in particular with regard to voltage signals generated by pulse width modulation (PWM), according to a first aspect, the present invention can be implemented by a method for detecting and analyzing a partial discharge, DP, in an electrical signal to be analyzed originating from electrical equipment in an aeronautical environment, comprising: a detection phase, comprising a step of detecting by means of a sensor the electrical signal to be analyzed generated by pulse width modulation, PWM, and a step of recognizing a possible discharge partial by comparing said electrical signal to be analyzed with at least one signature signal representative of a partial discharge, and, an analysis phase comprising a step of decomposing said electrical signal to be analyzed into a sequence of patterns, and a step of assigning the detected partial discharges to said patterns.

[0019] 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: the method further comprises a step of associating each of said patterns with information relating to the partial discharges previously assigned to said pattern; said association step comprises the superposition of a plurality of partial discharges detected for a plurality of periods of said electrical signal to be analyzed for the same pattern; said decomposition step comprises a determination of a number of patterns in said electrical signal to be analyzed from parameters of a control signal used to generate said electrical signal by pulse width modulation; said number of patterns is determined as a function of the frequency of a modulating signal and the frequency of a carrier.said decomposition step comprises an identification of patterns by comparison with a signature pattern; an amplitude-phase-frequency diagram, of the PRPD type, is associated with the patterns; said recognition step comprises a step of calculating at least one value of a distance parameter between said electrical signal to be analyzed and said at least one signature signal, said distance parameter being a function of a difference between said electrical signal to be analyzed and said at least one signature signal, and a step of comparing the value of said distance parameter with a detection threshold, and. detection of said possible partial discharge based on a result of said comparison.

[0020] Another subject of the invention relates to a computer program comprising instructions for implementing a method as previously described when said instructions are executed by a processor of a detection and analysis device.

[0021] Another object of the invention relates to a detection and analysis device, suitable for implementing the steps of the method as previously described.

[0022] Another subject of the invention relates to an aircraft comprising at least one such detection and analysis device.

[0023] 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 DRAWINGS

[0024] Other aspects, aims, advantages and characteristics of the invention will appear better on reading the following detailed description of preferred embodiments thereof, given by way of non-limiting example, and made with reference to the appended drawings in which: Figure 1 represents a flowchart of the steps of a method for detecting and recognizing partial discharges according to one embodiment of the invention, Figure 2 illustrates the technical principle behind the recognition of partial discharges according to embodiments of the invention, Figure 3 illustrates a partial discharge detection system for obtaining signatures according to an embodiment of the present invention, Figure 4 illustrates a possible construction of an MLI electrical signal, Figure 5 illustrates an example of a decomposition of an electrical signal into two patterns, Figures 6A-6D illustrate simplified examples of PRPD schemes in the context of sinusoidal signals, Figure 7 illustrates a simplified example of PRPD-type diagrams for a PWM-type electrical signal. DETAILED DESCRIPTION OF SPECIFIC EMBODIMENTS

[0025] An electrical insulator, by preventing the passage of electric current, allows the proper functioning of electrical systems. In power electronics, these materials are found either in passive components, for which the aim is rather to exploit the dielectric properties of the material (and its storage aspects), or as insulation. In electrical engineering, it is mainly the function of insulating parts brought to different potentials that is sought.

[0026] Insulating materials, whether solid, liquid or gaseous, are often the weak link in electrical systems; in particular, beyond a certain voltage, the phenomenon of Partial Discharges (PD) and its consequences (such as the appearance of short circuits or fault electric arcs) are likely to occur.

[0027] Until now, the existence of these partial discharges had been little taken into account in the design of aircraft equipment, given the low voltage levels used. However, and in the aeronautical field in particular, the hybridization and electrification of high-power propulsion systems leads to an increase in operating voltages; in fact, no current system can claim to be either exempt from or resistant to PDs.

[0028] Subsequently, partial discharge (PD) will be understood to mean a localized electrical discharge generated, under the effect of a high voltage or voltage variation, in an insulating gap separating conductors. Electrical network will also be understood to mean any type of network that can be found in an aeronautical environment, for example in any aircraft: plane or helicopter, etc.

[0029] Figure 1 is the flowchart of the steps of a method for detecting and recognizing partial discharges DP, the main steps of which are illustrated in Figure 2.

[0030] The proposed method comprises a detection phase SI, and an analysis phase S2. This method is implemented here by computer.

[0031] In the detection phase SI, the method comprises a step E10 of detecting an electrical signal to be analyzed 1.

[0032] Pulse width modulation (or PWM) is a technique commonly used to synthesize pseudo-analog signals using digital circuits (all or nothing, 1 or 0), or more generally discrete states. The general principle is that by applying a rapid succession of discrete states with well-chosen duration ratios, any intermediate value can be obtained by looking only at the average value of the signal.

[0033] Different techniques exist for generating an electrical signal by PWM.

[0034] A classic technique is the so-called intersective method.

[0035] With reference to Figure 4, this method consists of carrying out a comparison, at each instant, between the values ​​of a modulating signal 42 and a carrier 41, and of assigning a discrete value to the modulated electrical signal 1 according to the result of this comparison.

[0036] The carrier can be a triangular signal, as in Figure 4, but other waveforms (sinusoids...) are also possible.

[0037] Figure 4 illustrates a possible construction of an electrical PWM signal from the triangular carrier 41 of the modulating signal 42, here sinusoidal.

[0038] When the modulating signal 42 is greater than the carrier 41, as in zone 43, the electrical signal 1 at the output takes a first discrete value, corresponding for example to a logic “1”. In the opposite case, as in zone 44, for example, the electrical signal 1 takes a second discrete value, corresponding for example to a logic “0”. In this way, an output signal is obtained which forms an alternation of values discrete (typically two) depending on the comparison of the modulating signals 42 and carrier 41.

[0039] Carrier 41 can also be sinusoidal, or sawtooth, etc.

[0040] Another method of generating a PWM signal is the third-order harmonic injection method. This method was first described in Buja's article, "Improvement of pulse width modulation techniques," Archiv fur Elektrotechnik, vol. 57, no. 5, 1975, pp. 281-289.

[0041] This method can be seen as a variant of the intersective method, but includes a preliminary step of modifying the modulating signal by adding a factor in y ■ sin(3 <Dt), c'est-à-dire en insérant un harmonique d'ordre 3 dans le signal modulant 42. La valeur m est un paramètre du procédé et t représente le temps.

[0042] Another method for generating a PWM signal is the space vector modulation (SVM) method. It was first described in G. Pfaff, et al., "Design and experimental results of a brushless ac servo drive", IEEE Transactions on Industry Applications, vol. IA-20, no. 4, pp. 814-21, July / August 1984, and is also widely described in the scientific literature on the subject, for example in reference books such as M.P. Kazmierkowski; R. Krishnan & F. Blaabjerg (2002). "Control in Power Electronics: Selected Problems", San Diego: Academie Press. ISBN 978-0-12-402772-5.

[0043] Another technique is the precalculated method, also called offline PWM or "Optimal Pulse Pattern" (OPP). The pattern of the output electrical signal, 1, is predetermined (offline) and stored in tables that are then read in real time. The method has for example been described in A.D. Birda, J. Reuss, and C. Hackl, "Synchronous optimal pulse-width modulation with differently modulated waveform symmetry properties for feeding synchronous motor with high magnetic anisotropy", in 2017 19th European Conference on Power Electronics and Applications (EPE'17 ECCE Europe), pages 1-10, Sept 2017, doi:10.23919 / EPE17ECCEEurope.2017.8098963.

[0044] Another technique is full-wave control. In this type of operation, the switches used to generate the PWM signals operate at the frequency of the output electrical quantities. The conduction time of a switch is T / 2, where T is the electrical period. The signal generated is then a periodic square wave of period T.

[0045] Other methods have been proposed for generating electrical signals by pulse width modulation, PWM, and are described in the technical literature. As will be seen later, the described method can be adapted to PWM signals generated by different methods.

[0046] Once detected, the electrical signal to be analyzed 1 is advantageously preprocessed. The detection step is accompanied by a filtering Eli of the electrical signal to be analyzed 1 by means of a filter. The filter is preferably a high-pass filter, in order to reduce as much as possible the noise level present in the electrical signal to be analyzed 1. The cutoff frequency of the high-pass filter is of the order of magnitude of a hundred MHz and beyond, for example around approximately 300 MHz.

[0047] The method then comprises a step E12 of acquiring an electrical signal to be analyzed 1. The electrical signal to be analyzed 1 is preferably acquired by means of the acquisition device (described below).

[0048] Once the electrical signal to be analyzed 1 is processed, a recognition step, E1, of a possible partial discharge is carried out. This step can be based on a comparison between this electrical signal to be analyzed and one or more signature signals, 2, representative of a partial discharge, DP.

[0049] Different embodiments of this recognition step E1 can be implemented, within the framework of the proposed method.

[0050] According to one embodiment, this recognition step E1 comprises a calculation step E2 of a value of a distance parameter 3. The distance parameter 3 is a function of a difference between two signals or portions of signals.

[0051] The calculation E2 of a value of the distance parameter 3 is carried out between the electrical signal to be analyzed 1 and a signature signal 2. The signature signal 2 is a signal representative of the signal of a partial discharge DP. The value of the distance parameter 3 is therefore calculated between the electrical signal to be analyzed 1 and a signal representative of a partial discharge DP.

[0052] According to one implementation, the value of the distance parameter 3 is calculated as a normalized Euclidean distance. That is to say, for each point of the electrical signal to be analyzed 1 whose magnitude is centered and reduced, its distance from the point of the corresponding signature signal 2, and whose magnitude is centered and reduced, is determined. In other words, the value of the distance parameter 3 is the result of the equation:

[0053] With N the number of points of the signature signal 2, x a magnitude of the point of the signature signal 2 and y a magnitude of the point of the electrical signal to be analyzed 1. The magnitudes of the points x and y are advantageously voltages. Preferably, the magnitudes are centered and reduced to obtain magnitudes independent of the unit or the chosen scale and having the same mean and the same dispersion.

[0054] According to another implementation mode, the value of the distance parameter 3 is calculated by means of a dynamic time warping function (or "Dynamic Time Warping" in English terminology). Such a function makes it possible to calculate the value of the distance parameter 3 between the electrical signal to be analyzed 1 and the signature signal 2 in a more robust manner in the face of time and amplitude expansion / contraction.

[0055] According to another mode of implementation, it is possible to calculate the value of the distance parameter 3 by means of any function suitable for evaluating a difference between two signals.

[0056] Furthermore, the calculation step E2 advantageously comprises the calculation of a series, 8, of values ​​of the distance parameter 3. The series 8 of values ​​is obtained by implementing the following steps: a selection E21 of a portion 7 of the electrical signal to be analyzed 1 in an analysis window 6, the analysis window 6 having a predefined width 61; a calculation E22 of a value of the distance parameter 3 between the portion 7 selected by the analysis window 6 of the electrical signal to be analyzed 1 and the signature signal 2; the shift E23 of the analysis window 6 by a predefined step 62; and the renewal E24 of these selection steps E21, calculation E22 and shift E23 in order to obtain the series 8 of values ​​of the distance parameter 3.

[0057] In other words, the analysis window 6 which selects a portion 7 of the electrical signal to be analyzed 1 is moved temporally onto the electrical signal to be analyzed 1 and, for each of its positions, the calculation E22 of the distance parameter 3 is carried out. In this way, the series 8 of values ​​of the distance parameter 3 represents the difference between the electrical signal to be analyzed and the signature signal for each of the portions 7 of this electrical signal to be analyzed 1.

[0058] Advantageously, the width 61 of the analysis window 6 represents a time interval corresponding to the duration of the partial discharge DP represented on the signature signal 2.

[0059] Advantageously, the step 62 of shift of the analysis window 6 along the time scale of the electrical signal to be analyzed 1 is equal to an acquisition period of the electrical signal to be analyzed 1. It is however possible to choose a step 62 different from this acquisition period such as for example a multiple of the acquisition period or any other time period.

[0060] Furthermore, it is advantageously possible to calculate E22 a value of a distance parameter 3 between a portion 7 of the electrical signal to be analyzed 1 and a plurality of signature signals 2 representative of different types of partial discharges DP.

[0061] According to one embodiment, the plurality of signature signals 2 comes from a database. A detection device C, described below, makes it possible to generate, in an optional step E0, a database comprising a plurality of signature signals 2 representative of partial discharges DP. It is indeed possible to identify the signature signals and to record them in the database prior to the implementation of the other steps of the detection and recognition method. The signal signatures 2 can evolve according to the conditions in which the electrical network 10 is found during its use. It is therefore possible to generate, in the laboratory, signal signatures 2 representative of partial discharges DP as they would be under these conditions.In order to be able to monitor the state of the insulation of the electrical network 10, it is advantageous to implement the detection and recognition method comprising the use of the database 10 comprising a plurality of signature signals 2 representative of partial discharges DP.

[0062] Furthermore, different signature signals 2 can be collected for the same type of partial discharge, depending in particular on the location at which the measurement is carried out. Thus, the same partial discharge phenomenon will generate a different signal depending on whether it is measured by the probe 91 or the probe 92, both located on the same line 10 but at a certain distance from each other (for example 1 or 2 meters), in Figure 3, described later.

[0063] After the calculation step E2, the detection and recognition method comprises a comparison step E3. During this step, the value of the distance parameter 3 resulting from the calculation step E2 is compared with a detection threshold 4. The comparison E3 is suitable for detecting a possible partial discharge DP depending on the results obtained, and therefore on the distance between the electrical signal to be analyzed 1 and the signature signal 2. Indeed, the lower the value of the distance parameter 3, the smaller the difference between the electrical signal to be analyzed 1 and the signature signal 2. A small difference between the electrical signal to be analyzed 1 and the signature signal 2 implies a significant similarity and a detection of a partial discharge DP is then probable.

[0064] In the embodiment according to which a series 8 of values ​​of the distance parameter 3 is calculated, the comparison step E3 compares the series 8 with the detection threshold 4 in order to detect one or more possible partial discharges DP and their position in the electrical signal to be analyzed 1.

[0065] The detection threshold 4 is advantageously determined as a function of the average of the series 8 of values ​​of the distance parameter 3 from which we subtract n times the value of the standard deviation of the series 8 of values ​​of the distance parameter 3. The number n is a real number, advantageously an integer greater than or equal to 1.

[0066] According to one embodiment, the detection and recognition method presented above can be coupled with other methods in order to guarantee even more precise recognition. For example, the method can be combined with a partial discharge DP recognition method implementing a wavelet transform of the electrical signal to be analyzed 1.

[0067] Figure 3 schematically illustrates a device C making it possible to detect beforehand and in the laboratory, signature signals 2 making it possible to generate E0 the database of signature signals 2, and / or to obtain the electrical signal to be analyzed 1 in order to be able to implement the detection and recognition method as described previously.

[0068] Furthermore, a source S of an electrical signal to be analyzed and a motor M are represented, the motor M being able to be replaced by any device consuming electrical energy.

[0069] The source is adapted to generate an electrical signal by pulse width modulation. To do this, it can receive an instruction from a control device, not shown, forming a modulating signal. It can then modulate a source of a carrier signal, or "carrier" (typically forming a pure sinusoid), to form an electrical signal of the PWM type.

[0070] The device C is for example a test bench comprising an acquisition device 9 and a sensor 91. The sensor 9 is for example a sensor 91 of type capacitive coupling. The sensor 91 advantageously comprises a metal tip which touches a part 11 of an electrical network 10. The part 11 of the electrical network 10 is advantageously covered with a layer 12 of copper to amplify the detected electrical signal.

[0071] However, sensors other than capacitive sensors can also be used to implement step E10 of detecting an electrical signal.

[0072] The device C makes it possible both to generate the database E0 in advance, but also to obtain the electrical signal to be analyzed 1. To this end, the sensor 9 acquires the electrical signal, for example in millivolts, image of an electrical quantity varying in the electrical network 10, for example the electric current.

[0073] Eli filtering, for example filtering using a high-pass filter, is applied to the electrical signal in order to reduce the noise level present as much as possible. The cut-off frequency of the filter used is advantageously around a hundred megahertz or higher, for example around 300 MHz. Finally, the acquisition step E12 is necessary to obtain the electrical signal to be analyzed 1 or the signature signal 2.

[0074] Once detected, filtered and acquired, the signal is either recorded in the database if it is a measurement aimed at enriching E0 the laboratory database, or used as an electrical signal to be analyzed 1 to implement the detection and recognition method as described previously.

[0075] An analysis phase S2 of the proposed method comprises a decomposition step E4 of the electrical signal to be analyzed 1 into a sequence of patterns.

[0076] Indeed, the generation of the electrical signal by pulse width modulation, PWM, is carried out from two periodic signals, a modulating signal and a carrier. Necessarily, the signal produced 1 is also periodic.

[0077] However, its period may be longer than that of the input signals and may not correspond to the period of the sinusoid corresponding to the PWM signal. Therefore, at each period of the sinusoid, we can have a different PWM pattern.

[0078] Figure 5 illustrates a decomposition of an electrical signal 1 into two patterns M1, M2. These two patterns follow one another and thus compose signal 1.

[0079] There are several possible methods for determining the patterns into which the electrical signal 1 can decompose. These methods may depend on the method that was used to generate the PWM signal.

[0080] According to one embodiment, a frequency method is used. This method is based on a priori knowledge of the frequencies of the carrier f p and the modulating signal f m. We can then deduce the number of patterns that can be generated. This information is sufficient to fully characterize the output signal since it is necessarily a succession of these different patterns. Knowing the number N of patterns, we can therefore deduce that the output signal is a succession modulo N of patterns mi, m2... mN.

[0081] In the case of an electrical signal 1 generated by the intersective method, we can determine this number of patterns by the expression:

[0082] The LCM() notation denoting the least common multiple.

[0083] In the case of an electrical signal generated by other methods, this number of patterns can be determined in different ways.

[0084] In the case of an electrical signal generated by harmonic injection or SVM, the frequency method can also be used. Indeed, these methods are derivatives of the intersective method but with a modulating form. From a priori knowledge of the frequencies of the carrier fp and the modulating signal fm, we can then deduce the number of patterns that can be generated.

[0085] In the pre-calculated method, the waveforms are preferably determined a priori by calculating switching angles to optimize the frequency spectrum of the generated signal. Knowing the value of these angles makes it possible to determine the number of patterns in the input electrical signal.

[0086] Finally, in the case of full-wave control, the switches operate at the frequency of the output electrical quantities. The pattern of the generated PWM signal is therefore unique and is a square signal of period T, where T is the electrical period of the signal.

[0087] According to another embodiment, the patterns composing the electrical signal 1 can be determined by an identification of these patterns within the signal.

[0088] In particular, a similar approach to that previously described for the detection and recognition of a partial discharge in the signal can be used. Indeed, in the same way as previously, a dictionary of signature patterns can be constituted, and one can then calculate a value of a distance parameter between the electrical signal 1 and the signature patterns, compare this value with a threshold and then identify a pattern based on this comparison.

[0089] The analysis phase S2 of the proposed method then includes a step E5 of assigning the detected partial discharges DP to the previously identified patterns.

[0090] Indeed, since the electrical signal 1 is decomposed into a succession of patterns, each detected partial discharge can be positioned temporally in relation to a pattern resulting from the decomposition of the signal. This DP / pattern assignment can therefore be easily carried out.

[0091] It is then possible, subsequently or in parallel, to associate information relating to these partial discharges for each pattern: as the electrical signal 1 is analyzed and partial discharges are detected, they can be assigned to the corresponding pattern. The information associated with this pattern is thus progressively enriched with data relating to the detected PDs.

[0092] The method therefore comprises a step E6 of associating with each pattern, information relating to the partial discharges (PD) assigned to this pattern.

[0093] This information can be structured in different ways. According to a preferred embodiment, this information can comprise an amplitude-phase- frequency, of the PRPD type (“Phase Resolved Partial Discharge”).

[0094] On this type of PRPD diagram, the DPs are represented by a cloud of points characterized by a phase (allowing it to be positioned in relation to the analyzed signal), an amplitude (allowing it to be positioned on the ordinate axis), and a frequency (corresponding to the number of DPs for this phase and this amplitude).

[0095] More generally, the information generated and associated with the patterns can be used to produce PRPD visual diagrams on a human-machine interface, but the information can also be used in other ways, notably for digital processing without going through a display phase.

[0096] In particular, digital processing can automate a diagnostic step to attribute information to one or more probable faults causing partial discharges.

[0097] The recognition of patterns associated with each type of fault can be carried out as in the case of PRPD in the form of a sinusoidal wave (Figures 6A-6D), with the objective of constructing a dictionary of patterns / faults in the case of voltage signals generated by PWM.

[0098] With the use of supervised artificial learning tools, in particular, it is possible to classify these different patterns and associate them with each type of defect causing partial discharges.

[0099] Figures 6A-6D illustrate simplified examples of PRPD patterns in the context of sinusoidal signals.

[0100] Each figure represents a period (360°) of the sinusoidal signal, on which the (majority) distribution of the detected partial discharges is plotted.

[0101] Figure 6A illustrates the presence of partial discharges in a cavity created due to an abrasion phenomenon of a semiconductor paint.

[0102] Figure 6B illustrates the presence of partial discharges in cavities resulting from a delamination phenomenon of layers of insulating tape.

[0103] Figure 6C illustrates the presence of surface discharges at the coil heads of an electrical machine, due to a surface contamination phenomenon.

[0104] Finally, Figure 6D illustrates the presence of internal partial discharges in microcavities present in an insulator.

[0105] As can be seen from the various examples in Figures 6A to 6D, the PRPD pattern forms a characteristic signature of a type of defect.

[0106] The proposed method makes it possible to obtain information enabling the generation of such a PRPD pattern within the framework of an electrical signal generated by MLI, i.e. by associating the DPs not with the overall signal but with the constituent patterns of this signal.

[0107] This contribution is important since it is the waveforms constituting the patterns themselves that can help identify defects. It is therefore interesting to be able to compare the PDs of the different patterns constituting an electrical signal.

[0108] Figure 7 illustrates a simplified example of PRPD type diagrams for an MLI type electrical signal, which can be derived from the implementation of a detection and analysis method as described previously.

[0109] This figure shows two patterns M1, M2 constituting an electrical signal. The information generated in step E6 and associated with each pattern therefore makes it possible to generate a PRPD diagram for each of the two patterns.

[0110] This diagram can be obtained by superimposing the detected partial discharges DPs according to their temporal phase and their amplitude in the same reference frame as the patterns, and opposite the pattern corresponding to their detection. Preferably, said superposition is carried out in the form of point clouds.

[0111] The distribution of points corresponding to the DPs within the patterns M1, M2 can form a signature of a defect at the origin of the DPs.

[0112] Thus, to summarize, the proposed method allows to carry out a PRPD under PWM voltage by indicating the presence of Partial Discharges in the different phases of the analyzed electrical signal. It thus proposes a solution to the problem of analyzing DPs under PWM voltage.

[0113] The method therefore allows the current or future use of PRPD type schemes for signals generated by pulse width modulation.

[0114] In general, the method described allows: to reliably and easily trace the PRPD under PWM voltage. to identify the occurrence of partial discharges (if any). to enable fault identification as well as analysis of critical flight phases, for which the frequency of PDs would potentially be higher. to avoid more complex processing. to distinguish all PDs from other high-frequency noise such as that of PWM converters.

[0115] This described process is compatible with all types of electrical systems operating under PWM voltage, regardless of their power and use, as long as sensors are available that can provide the signal that contains the signature of the phenomenon and the dictionary of signatures to be searched for.

[0116] The proposed method is also compatible with all the different techniques for generating a PWM signal (PWM by intersection, PWM by harmonic injection, etc.).

[0117] Of course, the present invention is not limited to the examples and the embodiment described and shown. It is in particular susceptible to numerous variants accessible to those skilled in the art.

Claims

CLAIMS 1. Method for detecting and analyzing a partial discharge (PD) in an electrical signal to be analyzed (1) generated by pulse width modulation known as PWM, originating from electrical equipment (10) in an aeronautical environment, comprising: - a detection phase (SI), comprising a step of detection (E10) by means of a sensor (91) of the electrical signal to be analyzed (1), and a step of recognition (El) of a possible partial discharge by comparison of said electrical signal to be analyzed (1) with at least one signature signal (2) representative of a partial discharge (DP), and, - an analysis phase (S2), comprising a step of decomposition (E4) of said electrical signal to be analyzed (1) into a sequence of patterns, and a step of allocation (E5) of the partial discharges (DP) detected to said patterns:

2. Method according to claim 1, further comprising a step (E6) of associating each of said patterns with information relating to the partial discharges (DP) previously assigned to said pattern.

3. Method according to the preceding claim, in which said information comprises an amplitude-phase-frequency diagram, of the PRPD type.

4. Method according to claim 3, in which said amplitude-phase-frequency pattern is obtained by the superposition of a plurality of partial discharges detected for a plurality of periods of said electrical signal to be analyzed (1) for the same pattern.

5. Method according to one of the preceding claims, in which said decomposition step (E4) comprises a determination of a number of patterns in said electrical signal to be analyzed (1) from parameters of a control signal used to generate said electrical signal by pulse width modulation, said number of patterns preferably being determined as a function of the frequency of a modulating signal and the frequency of a carrier.

6. Method according to one of claims 1 to 4, in which said decomposition step (E4) comprises an identification of patterns by comparison with a signature pattern).

7. Method according to one of the preceding claims, in which said recognition step (El) comprises a step of calculating (E2) at least one value of a distance parameter (3) between said electrical signal to be analyzed (1) and said at least one signature signal (2), said distance parameter being a function of a difference between said electrical signal to be analyzed (1) and said at least one signature signal (2), and a step of comparing (E3) the value of said distance parameter (3) with a detection threshold (4), and of detecting said possible partial discharge (DP) as a function of a result of said comparison.

8. Computer program comprising instructions for implementing a method according to one of the preceding claims when said instructions are executed by a processor of a detection and analysis device (C) 9. Detection and analysis device (C), comprising at least one sensor (91) and an acquisition device (9) adapted to, in collaboration with a database, implement the steps of the method according to one of claims 1 to 7.

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

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