Aircraft direct current electrical system arc fault monitoring method, system, medium and equipment

Abstract

The invention relates to an arc fault monitoring method, system, medium and device for an aircraft direct current electrical system, and the method comprises the steps: processing filtered current data based on a CUSUM change point detection algorithm, and obtaining a current sudden change moment used for determining a sudden change point of current; calculating a current spectrum cosine distance between the current data of the current time window and the current data of the time window before the preset moment; the characteristic value ratio of the cosine distance to the historical value is calculated, and the characteristic value ratio of the characteristic value of the latest time window obtained along with time flow to the historical average value of the characteristic values of multiple continuous time windows before the preset moment is calculated; and when a sudden change point is detected, comparing the sudden change point of the frequency spectrum cosine distance of the plurality of time windows behind the sudden change point with a preset threshold value so as to judge that an arc fault occurs.

Description

Technical Field

[0001] The present invention relates to the technical field of aircraft DC electrical systems, and particularly relates to an arc fault monitoring method, system, medium and device for an aircraft DC electrical system. Background Art

[0002] Since DC arcs do not have a zero-crossing point, it is very difficult for them to extinguish themselves after an arc fault occurs. With the development of more-electric aircraft and all-electric aircraft, DC is widely used in aircraft power distribution systems due to its advantages such as high transmission efficiency. However, due to factors such as limited space on the aircraft, the in-aircraft power distribution lines are very dense. Once a line arc fault occurs, the high temperature of the arc will quickly ignite the surrounding substances, seriously threatening the safe operation of the aircraft. Existing aircraft arc fault detection methods are difficult to accurately identify faults.

[0003] The above information disclosed in the background art section is only used to enhance the understanding of the background of the present invention, and thus may include information that does not constitute the prior art known to those of ordinary skill in the art. Summary of the Invention

[0004] The present invention provides an arc fault monitoring method, system, medium and device for an aircraft DC electrical system. By measuring the current signal of the loop, using the CUSUM change point detection algorithm to identify the moment of arc initiation, and then comparing the cosine distance after the change point with the cosine distance of the historical time window before the change point. By comparing the cosine distance ratio with a predetermined threshold for fault determination, accurate and reliable detection of aircraft DC arc faults can be achieved, solving the problem that existing aircraft arc fault detection methods are difficult to accurately identify faults.

[0005] An arc fault monitoring method for an aircraft DC electrical system includes:

[0006] The first step, measuring the current data of a time window of the aircraft DC electrical loop and filtering it;

[0007] The second step, processing the filtered current data based on the CUSUM change point detection algorithm to obtain the current mutation moment for determining the mutation point of the current;

[0008] The third step, calculating the current spectrum cosine distance between the current data of the current time window and the current data of the time window before a predetermined moment;

[0009] The fourth step, calculating the eigenvalue ratio of the cosine distance to the historical value, wherein the eigenvalue of the latest time window obtained as time flows is used as the eigenvalue ratio with the historical average value of the eigenvalues of a plurality of consecutive time windows before a predetermined moment;

[0010] In the fifth step, after detecting the mutation point, compare the mutation points of the spectral cosine distances in multiple time windows after the mutation point with a predetermined threshold to determine whether an arc fault has occurred.

[0011] In the arc fault monitoring method for an aircraft DC electrical system described above, it further includes a sixth step. If no arc fault is detected, repeat the first step to the fifth step to monitor the aircraft DC electrical circuit.

[0012] In the arc fault monitoring method for an aircraft DC electrical system described above, in the first step, the current data is filtered by a high-pass filter with a cut-off frequency of 100 Hz, the time window is 10 ms, the time window moving step size is 5 ms, and the predetermined time is 0.5 s.

[0013] In the arc fault monitoring method for an aircraft DC electrical system described above, if the eigenvalue ratio of the spectral cosine distances in more than a predetermined proportion of the consecutive multiple time windows after the mutation point is greater than a predetermined threshold, it is considered that an arc fault has occurred.

[0014] In the arc fault monitoring method for an aircraft DC electrical system described above, the calculation formula for the current spectral cosine distance is:

[0015]

[0016] where u and v are the vectors formed by splicing the spectra obtained after the fast Fourier transform (FFT) of the current time window and the time window before the predetermined time at the selected frequency band.

[0017] In the arc fault monitoring method for an aircraft DC electrical system described above, the frequency bands of 200 Hz to 15 kHz and 130 kHz to 150 kHz in the current spectrum are selected as the selected frequency bands.

[0018] In the arc fault monitoring method for an aircraft DC electrical system described above, the formulas for calculating the forward and backward cumulative sums by the CUSUM change point detection algorithm include:

[0019]

[0020] x i is the value of the i-th discrete current signal, δ is the set allowable deviation size, k is the offset value, S i + and S i - are the cumulative sums at the previous moment of the forward CUSUM and the backward CUSUM. If S i + exceeds a certain threshold h+, or S i -If it exceeds a certain threshold h-, it is considered that the signal has mutated. h+ and h- correspond to the step sizes set for positive and negative mutations respectively.

[0021] An aircraft DC arc fault monitoring system includes

[0022] A current data measurement unit, which is used to measure the current data of an aircraft DC electrical circuit in a time window and filter it;

[0023] A CUSUM change point detection unit, which is used to process the filtered current data based on the CUSUM change point detection algorithm to obtain the current mutation moment for determining the mutation point of the current;

[0024] A cosine distance calculation unit, which is used to calculate the cosine distance of the current spectrum between the current data of the current time window and the current data of the time window before a predetermined moment;

[0025] A comparison unit, which is used to calculate the eigenvalue ratio of the cosine distance to the historical value. Among them, the eigenvalue of the latest time window obtained as time flows is used as the eigenvalue ratio with the historical average value of the eigenvalues of multiple consecutive time windows before a predetermined moment;

[0026] A determination unit, which is used to compare the mutation point of the spectrum cosine distance of multiple time windows after the mutation point with a predetermined threshold when a mutation point is detected to determine whether an arc fault has occurred.

[0027] A computer storage medium, the storage medium includes computer instructions, when it runs on a computer, it causes the computer to execute the described method.

[0028] An electronic device, the electronic device includes:

[0029] A memory, a processor, and a computer program stored on the memory and executable on the processor. Among them,

[0030] When the processor executes the program, it implements the described method.

[0031] Compared with the prior art, the present invention has the following advantages: The present invention realizes arc fault detection based on CUSUM (Cumulative Sum Control Chart) and spectrum cosine distance. The CUSUM algorithm is used to detect the current mutation moment and obtain the current mutation information, which provides effective information for comparing the differences before and after the mutation point in the next step and identifying the arc fault; The spectrum cosine distance is used to distinguish the arc fault. The spectrum cosine distance can distinguish the spectrum difference between the arc fault current and the normal current. When an arc fault occurs, the high-frequency components of the current spectrum increase significantly, making the spectrum cosine distance between the normal current and the fault current increase significantly. Using this eigenvalue can capture the fault information and realize the monitoring of the arc fault. Brief Description of the Drawings

[0032] By reading the following detailed description of the preferred embodiments, various other advantages and benefits of the present invention will become clear to those of ordinary skill in the art. The drawings in the specification are only for the purpose of showing the preferred embodiments and are not considered to be a limitation of the present invention. Obviously, the drawings described below are only some embodiments of the present invention, and those of ordinary skill in the art can obtain other drawings based on these drawings without creative efforts. Moreover, throughout the drawings, the same reference numerals are used to represent the same components.

[0033] In the drawings:

[0034] Figure 1 is a schematic flowchart of an arc fault monitoring method for an aircraft DC electrical system provided by an embodiment of the present disclosure;

[0035] Figure 2 is a schematic diagram of an arc fault experiment circuit provided by an embodiment of the present disclosure, Figure 2 where (a) is a series and vibrating arc experiment circuit, Figure 2 and (b) is a parallel arc experiment circuit;

[0036] Figure 3 is a capacitive load circuit diagram provided by an embodiment of the present disclosure;

[0037] Figure 4 is a spectrum waveform diagram of a load shedding condition with a DC / DC module load provided by an embodiment of the present disclosure;

[0038] Figure 5 is a schematic diagram of the comparison of the cosine distance effect before and after selecting the spectrum range provided by an embodiment of the present disclosure, Figure 5 where (a) is the schematic diagram before selecting the spectrum range, Figure 5 and (b) is the schematic diagram after selecting the spectrum range.

[0039] The present invention will be further explained below in conjunction with the drawings and embodiments. Detailed Embodiments

[0040] The specific embodiments of the present invention will be described in more detail below with reference to the drawings. Although the specific embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided so that the present invention can be more thoroughly understood and the scope of the present invention can be completely conveyed to those skilled in the art.

[0041] It should be noted that in the specification and claims, certain terms are used to refer to specific components. Those skilled in the art should understand that technicians may use different nouns to refer to the same component. The specification and claims do not distinguish components by the difference in nouns, but by the difference in the functions of the components. As mentioned throughout the specification and claims, the term "comprising" or "including" is an open-ended term and should be interpreted as "including but not limited to". The following description in the specification is the preferred implementation mode for implementing the present invention, but the description is for the purpose of the general principles of the specification and is not used to limit the scope of the present invention. The protection scope of the present invention shall be subject to that defined by the appended claims.

[0042] To facilitate the understanding of the embodiments of the present invention, the following will further explain with specific embodiments in conjunction with the accompanying drawings, and the accompanying drawings do not constitute a limitation to the embodiments of the present invention.

[0043] As Figures 1 to 5 shown, the arc fault monitoring method for an aircraft DC electrical system includes the following steps:

[0044] The first step is to measure the current data of a time window of the aircraft DC electrical circuit and filter it;

[0045] The second step is to process the filtered current data based on the CUSUM change point detection algorithm to obtain the current mutation moment for determining the mutation point of the current;

[0046] The third step is to calculate the current spectrum cosine distance between the current data of the current time window and the current data of the time window before a predetermined moment;

[0047] The fourth step is to calculate the eigenvalue ratio of the cosine distance to the historical value, where the eigenvalue of the latest time window obtained as time flows is used as the eigenvalue ratio with the historical average value of the eigenvalues of a plurality of consecutive time windows before a predetermined moment;

[0048] The fifth step is to, after detecting the mutation point, compare the mutation point of the spectrum cosine distance of multiple time windows after the mutation point with a predetermined threshold to determine whether an arc fault has occurred.

[0049] In the preferred implementation mode of the arc fault monitoring method for an aircraft DC electrical system described above, a sixth step is further included. If no arc fault is detected, the first step to the fifth step are repeated to monitor the aircraft DC electrical circuit.

[0050] In the preferred embodiment of the arc fault monitoring method for an aircraft DC electrical system, in the first step, the current data is filtered by a high-pass filter with a cut-off frequency of 100 Hz, the time window is 10 ms, the time window moving step is 5 ms, and the predetermined time is 0.5 s.

[0051] In the preferred embodiment of the arc fault monitoring method for an aircraft DC electrical system, if the eigenvalue ratio of the spectral cosine distance of more than a predetermined proportion of the time windows in a plurality of consecutive time windows after the mutation point is greater than a predetermined threshold, it is considered that an arc fault has occurred.

[0052] In the preferred embodiment of the arc fault monitoring method for an aircraft DC electrical system, the calculation formula for the current spectral cosine distance is:

[0053]

[0054] where u and v are the vectors spliced from the spectra obtained after the fast Fourier transform (FFT) of the current time window and the time window before the predetermined time in the selected frequency band.

[0055] In the preferred embodiment of the arc fault monitoring method for an aircraft DC electrical system, the frequency bands of 200 Hz to 15 kHz and 130 kHz to 150 kHz in the current spectrum are selected as the selected frequency bands.

[0056] In the preferred embodiment of the arc fault monitoring method for an aircraft DC electrical system, the formulas for calculating the forward and backward cumulative sums by the CUSUM change point detection algorithm include:

[0057]

[0058] x i is the value of the i-th discrete current signal, δ is the set allowable deviation size, k is the deviation value, S i + and S i - are the cumulative sums at the previous moment of the forward CUSUM and the backward CUSUM. If S i + exceeds a certain threshold h+, or S i - exceeds a certain threshold h-, it is considered that the signal has mutated. h+ and h- respectively correspond to the step sizes set for the forward mutation and the backward mutation.

[0059] An aircraft DC arc fault monitoring system includes,

[0060] A current data measurement unit for measuring and filtering the current data of a time window of the aircraft DC electrical circuit;

[0061] CUSUM change point detection unit, which is used to process the filtered current data based on the CUSUM change point detection algorithm to obtain the current mutation moment for determining the mutation point of the current;

[0062] Cosine distance calculation unit, which is used to calculate the cosine distance of the current spectrum between the current data of the current time window and the current data of the time window before a predetermined moment;

[0063] Comparison unit, which is used to calculate the eigenvalue ratio of the cosine distance to the historical value, wherein the eigenvalue of the latest time window obtained as time flows is used as the eigenvalue ratio with the historical average value of the eigenvalues of a plurality of consecutive time windows before a predetermined moment;

[0064] Determination unit, which is used to compare the mutation point of the spectrum cosine distance of multiple time windows after the mutation point with a predetermined threshold when a mutation point is detected to determine whether an arc fault occurs.

[0065] A computer storage medium, the storage medium includes computer instructions, when it runs on a computer, it causes the computer to execute the described method.

[0066] An electronic device, the electronic device includes:

[0067] A memory, a processor, and a computer program stored on the memory and executable on the processor, wherein when the processor executes the program, it implements the described method.

[0068] In one embodiment, the arc fault monitoring method for an aircraft DC electrical system includes,

[0069] 1. Measure the current data of a time window of the loop. The size of the time window is selected as 10 ms and the step size is 5 ms. In order to exclude the influence of the DC component on the eigenvalue, the current data is passed through a high-pass filter with a cut-off frequency of 100 Hz;

[0070] 2. Use the CUSUM change point detection algorithm to process the filtered arc current to obtain the current mutation moment, providing mutation point information for the next step of comparing spectrum cosine calculation to identify the arc;

[0071] 3. In order to exclude the influence of the switching frequency of special loads on the algorithm, select the frequency bands of 200 Hz - 15 kHz and 130 kHz - 150 kHz in the current spectrum as the characteristic frequency bands, and then calculate the spectrum cosine distance between the current time window and the time window 0.5 s ago;

[0072] 4. Calculate the ratio of the cosine distance to the historical value. The calculation method is to use the eigenvalue of the latest time window obtained as time flows as the ratio with the historical average value of the eigenvalues of 5 consecutive time windows 0.5 s ago;

[0073] 5. After detecting a mutation point, compare the spectral cosine distance ratio of the 10 time windows after the mutation point with a threshold. If there is no arc fault, the spectral cosine distance ratio is close to 1. When an arc fault occurs, the spectral cosine distance ratio increases significantly. By reasonably setting the threshold, arc fault detection is achieved;

[0074] 6. If the spectral cosine distance ratios of 7 out of 10 consecutive time windows after the mutation point are greater than the set threshold, it is considered that an arc fault has occurred;

[0075] 7. If the algorithm does not detect the occurrence of an arc fault, repeat steps 1 - 6.

[0076] DC arc faults include three types: series arc faults, parallel arc faults, and vibrating arc faults. This method is not affected by the load - switching condition.

[0077] As Figure 2 shown in the figure is the experimental circuit structure of series, vibrating, and parallel arc faults. The Solid - State Power Controller (SSPC) is an intelligent switching device that integrates the switching function of a relay and the circuit protection function of a circuit breaker in an aircraft. It is connected in series in the circuit to simulate the actual electrical system of the aircraft. The series and vibrating arc - generating devices are connected in series with the load. To ensure that the loop current does not exceed the maximum current that the experimental equipment can withstand after a parallel arc occurs, the parallel arc - generating device is connected in parallel with part of the load 2, and the load 1 plays a current - limiting role.

[0078] According to the actual voltage level, current range, and load type of the on - board DC system, the arc fault types include series, parallel, and vibrating arcs. Two voltage levels of 28V and 270V are set, the test current range is 2 - 40A, and the load types include resistive loads, capacitive loads, and inductive loads. The capacitive load is composed of a capacitor in parallel with a resistor, simulating the situation of power supply switching and capacitor voltage stabilization on an aircraft. The inductive load uses an actual motor used on an aircraft. Since the conversion between the two voltage levels of 270V and 28V in the aircraft DC system is achieved through a DC / DC conversion module, a DC / DC module that converts 270V voltage to 28V is also connected in some test loads.

[0079] As shown in equations (1) and (2), the formulas for calculating the forward and reverse cumulative sums in CUSUM change - point detection include:

[0080]

[0081] x i is the value of the i - th discrete current signal, δ is the set allowable deviation size, k is the deviation value (usually set to 0, or selected according to the actual situation), Si + and S i - are the cumulative sums at the previous moment of the positive CUSUM and the negative CUSUM. If S i + exceeds a certain threshold h+, or S i - exceeds a certain threshold h-, it is considered that a mutation has occurred in the signal. h+ and h- correspond to the step sizes set for positive and negative mutations respectively.

[0082] As Figure 3 shown in the figure is the recognition result of the filtered arc current through the CUSUM change point detection. In the figure, the moment 0 is the instant when the arc occurs. A pulse will be generated at the instant when the arc occurs after filtering, and the red dots in the figure are the CUSUM change point detection results, indicating that the CUSUM has successfully identified the time point of the instant when the arc occurs.

[0083] Select the cosine distance of the current spectrum as the criterion feature quantity. The calculation formula of the cosine distance is shown in Equation (3):

[0084]

[0085] where u and v are the vectors obtained by splicing the spectra in the frequency bands of 200 Hz to 15 kHz and 130 kHz to 150 kHz after the fast Fourier transform (FFT) of the current time window and the time window 0.5 s ago. Compare the latest value of the spectral cosine distance with the historical average value to eliminate the numerical differences brought by different working conditions. When the arc fault does not occur, the current is relatively stable, and the ratio of the spectral cosine distance is close to 1. After the arc fault occurs, due to the obvious increase in the high-frequency components in the arc spectrum, the ratio of the spectral cosine distance after the change point is greater than 1. When there are power electronic devices in the load, switching frequencies will be introduced into the current spectrum, affecting the stability of the algorithm. As Figure 4 shown in the figure is the spectral waveform of the load with a DC / DC module during the load switching experiment. Although there is no arc fault, the huge difference in the spectrum before and after switching the load will cause false alarms.

[0086] In order to eliminate the influence of the switching frequency of the DC / DC module in the load on the algorithm, after analyzing the switching frequency of the DC / DC module, select the frequency bands of 200 Hz to 15 kHz and 130 kHz to 150 kHz, splice the vectors, and then calculate the cosine distance. As Figure 5 shown in the figure is the comparison of the calculation effects of the cosine distance under the load switching conditions before and after selecting the spectral range. After selecting the spectral range, the difference before and after is significantly reduced, and the fault can be distinguished by setting a threshold.

[0087] Although the embodiments of the present invention have been described above in conjunction with the accompanying drawings, the present invention is not limited to the above specific embodiments and application fields. The above specific embodiments are merely illustrative and guiding, rather than restrictive. Those of ordinary skill in the art can also make many forms under the inspiration of this specification and without departing from the scope protected by the claims of the present invention, and these all fall within the scope of protection of the present invention.

Claims

1. A method for monitoring arc faults in a DC electrical system of an aircraft, characterized in that: The steps include: In the first step, current data of a time window of the aircraft DC electrical circuit is measured and filtered; The second step is to process the filtered current data based on the CUSUM change point detection algorithm to obtain the current mutation moment for determining the current mutation point; The third step is to calculate the current spectrum cosine distance between the current data of the current window and the current data of the time window before the predetermined moment; The fourth step is to calculate the eigenvalue ratio of the cosine distance and the historical value, wherein the eigenvalue of the latest time window obtained over time is compared with the historical average of the eigenvalues ​​of multiple consecutive time windows before the predetermined time. The fifth step is to compare the mutation point of the frequency spectrum cosine distance of multiple time windows after the mutation point with a predetermined threshold value after the mutation point is detected to determine whether an arc fault occurs.

2. The arc fault monitoring method of an aircraft DC electrical system according to claim 1, characterized in that: Preferably, the method further includes a sixth step, in which if no arc fault is detected, steps 1 to 5 are repeated to monitor the aircraft DC electrical circuit.

3. The arc fault monitoring method of an aircraft DC electrical system according to claim 1, characterized in that: In the first step, the current data is filtered by a high-pass filter with a cut-off frequency of 100 Hz, the time window is 10 ms, the time window moving step is 5 ms, and the predetermined time is 0.5 s.

4. The arc fault monitoring method of an aircraft DC electrical system according to claim 1, characterized in that: If the eigenvalue ratio of the frequency spectrum cosine distance of the time windows greater than a predetermined proportion in a plurality of consecutive time windows after the mutation point is greater than a predetermined threshold, it is considered that an arc fault has occurred.

5. The arc fault monitoring method of an aircraft DC electrical system according to claim 1, characterized in that: The calculation formula of the current spectrum cosine distance is: Wherein u and v are vectors of the frequency spectra obtained by fast Fourier transform (FFT) of the current time window and the time window before the predetermined time in the selected frequency band.

6. The arc fault monitoring method of an aircraft DC electrical system according to claim 5, characterized in that: The frequency bands of 200 Hz to 15 kHz and 130 kHz to 150 kHz in the current spectrum are selected as the selected frequency bands.

7. The arc fault monitoring method of an aircraft DC electrical system according to claim 1, characterized in that: The formulas for calculating the positive and negative cumulative sums by the CUSUM change point detection algorithm include: x i is the value of the i-th discrete current signal, δ is the size of the set allowable offset, k is the offset value, S i + and S i - is the cumulative sum of the positive CUSUM and the negative CUSUM of the previous moment. If S i + Exceeding a certain threshold h+, or S i - If the signal exceeds a certain threshold h-, it is considered that a mutation has occurred. h+ and h- correspond to the step sizes set for positive mutation and negative mutation, respectively.

8. An aircraft DC arc fault monitoring system, characterized in that: These include, A current data measurement unit, which is used to measure and filter the current data of a time window of a DC electrical circuit of the aircraft; A CUSUM change point detection unit, which is used to process the filtered current data based on the CUSUM change point detection algorithm to obtain a current mutation moment for determining a current mutation point; A cosine distance calculation unit, which is used to calculate the current spectrum cosine distance between the current data of the current window and the current data between the time windows before the predetermined moment; A comparison unit, which is used to calculate the eigenvalue ratio of the cosine distance and the historical value, wherein the eigenvalue of the latest time window obtained over time is compared with the historical average of the eigenvalues ​​of multiple consecutive time windows before a predetermined time; The determination unit is used for comparing the mutation point of the frequency spectrum cosine distance of multiple time windows after the mutation point with a predetermined threshold value after detecting the mutation point, so as to determine the occurrence of an arc fault.

9. A computer storage medium, characterized in that: The storage medium includes computer instructions, which, when executed on a computer, enable the computer to execute the method according to any one of claims 1 to 7.

10. An electronic device, characterized in that: The electronic device comprises: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method according to any one of claims 1 to 7 is implemented.

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