Aircraft direct current arc fault detection method, system, medium and equipment

Abstract

The invention discloses an aircraft direct-current arc fault detection method, system, medium and equipment based on current spectrum Euclidean distance, and the method comprises the steps: measuring current data of a time window of an aircraft direct-current electrical loop; calculating a current spectrum Euclidean 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 Euclidean 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; setting a fault threshold according to the fault characteristics of different types of arcs and the change condition of the Euclidean distance of the current spectrum under the load shedding condition, comparing the characteristic value ratio with the fault threshold, when the characteristic value ratio reaches the fault threshold, adding 1 to a fault accumulated value, if the accumulated value exceeds a preset value, determining that a fault exists in a plurality of time windows, and if the accumulated value does not exceed the preset value, determining that the fault exists in the plurality of time windows. If so, determining that an arc fault occurs.

Description

Technical Field

[0001] The present invention relates to the technical field of aircraft DC electrical systems, and particularly to an aircraft DC arc fault detection method, system, medium and device based on the Euclidean distance of current spectra. Background Art

[0002] When an arc fault occurs in an aircraft DC electrical system, due to the combustion of the arc generating a high temperature of thousands of degrees, and the DC arc having no zero-crossing point and not extinguishing naturally, a long-term arc fault will further cause an electrical fire, seriously affecting the safety of on-board equipment and personnel. 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 aircraft DC arc fault detection method, system, medium and device based on the Euclidean distance of current spectra. By measuring the current signal of the loop, calculating the Euclidean distance of the spectrum within the frequency band range, and comparing the eigenvalue obtained by calculating each time window with the eigenvalue obtained at an earlier time to eliminate the numerical differences brought by different working conditions. By setting a fault determination threshold, accurate and reliable detection of aircraft DC arc faults can be achieved, providing safety support for the steady development of more-electric aircraft and all-electric aircraft.

[0005] An aircraft DC arc fault detection method based on the Euclidean distance of current spectra includes:

[0006] The first step is to measure the current data of an aircraft DC electrical loop in a time window;

[0007] The second step is to calculate the Euclidean distance of the current spectra between the current data of the time window and the current data of the time window before a predetermined moment;

[0008] The third step is to calculate the eigenvalue ratio of the Euclidean 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;

[0009] The fourth step is to set a fault threshold according to the fault characteristics of different types of arcs and the change of the Euclidean distance of the current spectrum under the load-shedding condition, compare the eigenvalue ratio with the fault threshold. When the eigenvalue ratio reaches the fault threshold, the fault cumulative value is incremented by 1. If the cumulative value exceeds a predetermined value, indicating that faults are determined in multiple time windows, then it is determined that an arc fault has occurred.

[0010] In the described aircraft DC arc fault detection method based on the Euclidean distance of current spectrum, a fifth step is further included. If no arc fault is detected, the first step to the fourth step are repeated to monitor the aircraft DC electrical circuit.

[0011] In the described aircraft DC arc fault detection method based on the Euclidean distance of current spectrum, in the first step, the current data is filtered by a high-pass filter with a cut-off frequency of 100 Hz.

[0012] In the described aircraft DC arc fault detection method based on the Euclidean distance of current spectrum, the time window is 10 ms, the time window moving step is 5 ms, and the predetermined time is 0.5 s.

[0013] In the described aircraft DC arc fault detection method based on the Euclidean distance of current spectrum, the calculation formula of the current spectrum Euclidean distance is shown in Equation (1):

[0014] (1)

[0015] Where I 1 (F) and I 1 (F) are the spectra obtained after the fast Fourier transform (FFT) of the current data in the current time window and the current data in the time window before the predetermined time. n and m are the serial numbers of the data points closest to the starting frequency and ending frequency of the selected frequency band, and ED is the current spectrum Euclidean distance between the two calculated spectra.

[0016] In the described aircraft DC arc fault detection method based on the Euclidean distance of current spectrum, the fault characteristics of different types of arcs include series arc faults, parallel arc faults, and vibrating arc faults. The load switching conditions include resistive loads, capacitive loads, and inductive loads. The capacitive load includes a simulated circuit built according to the actual working load characteristics of the aircraft, and the inductive load uses the motors actually used in the aircraft.

[0017] An aircraft DC arc fault detection system includes

[0018] A current data measurement unit for measuring the current data of a time window of the aircraft DC electrical circuit;

[0019] A Euclidean distance calculation unit for calculating the current spectrum Euclidean distance between the current data of the current time window and the current data of the time window before the predetermined time;

[0020] A comparison unit for calculating the eigenvalue ratio of the Euclidean 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 the predetermined time;

[0021] A determination unit, which is configured to set a fault threshold according to the fault characteristics of different types of arcs and the change of the Euclidean distance of the current spectrum under the load shedding condition, compare the eigenvalue ratio with the fault threshold, when the eigenvalue ratio reaches the fault threshold, the fault accumulation value is incremented by 1, and if the accumulation value exceeds a predetermined value, indicating that faults are determined in multiple time windows, then it is determined that an arc fault has occurred.

[0022] In the system described above, the aircraft DC electrical circuit includes a DC power source, a solid state power controller, an arc generating device, and a load.

[0023] A computer storage medium, the storage medium includes computer instructions, when it runs on a computer, it causes the computer to execute the method described above.

[0024] An electronic device, the electronic device includes:

[0025] A memory, a processor, and a computer program stored on the memory and executable on the processor, wherein,

[0026] When the processor executes the program, it implements the method described above.

[0027] Compared with the prior art, the present invention has the following advantages: The present invention proposes the Euclidean distance of the current spectrum as a key index for realizing arc fault detection; the current eigenvalue is compared with the historical value to eliminate the numerical differences brought about by different working conditions, and fault detection is realized by means of threshold comparison. It has been verified for three different types of arc faults, namely series, parallel, and vibrating arcs, and a load switching experiment is designed, which can well simulate the special environment and corresponding working conditions of on-board arc faults, and can achieve accurate and reliable detection of aircraft DC arc faults. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] By reading the following detailed description of the preferred specific embodiments, various other advantages and benefits of the present invention will become clear to those of ordinary skill in the art. The accompanying drawings of 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 following described drawings are only some embodiments of the present invention, and those of ordinary skill in the art can obtain other drawings according to these drawings without creative efforts. Moreover, throughout the drawings, the same reference numerals are used to represent the same components.

[0029] In the drawings:

[0030] Figure 1 is a schematic flow chart of a method for detecting aircraft DC arc faults based on the Euclidean distance of the current spectrum provided by an embodiment of the present disclosure;

[0031] Figure 2It is a schematic diagram of an arc fault experiment circuit provided by an embodiment of the present disclosure. Figure 2 Among them, (a) is a series and vibrating arc experiment circuit. Figure 2 Among them, (b) is a parallel arc experiment circuit.

[0032] Figure 3 It is a capacitive load circuit diagram provided by an embodiment of the present disclosure.

[0033] Figure 4 It is a schematic diagram of the Euclidean distance between arc current and spectrum provided by an embodiment of the present disclosure. Figure 4 Among them, (a) is a schematic diagram of a series arc waveform. Figure 4 Among them, (b) is a schematic diagram of the calculation result of the spectrum Euclidean distance.

[0034] The present invention will be further explained below in conjunction with the drawings and embodiments. Specific embodiments

[0035] The specific embodiments of the present invention will be described in more detail below with reference to the drawings. Although 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 fully conveyed to those skilled in the art.

[0036] It should be noted that certain terms are used in the specification and claims 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 use the difference in nouns as a way to distinguish components, but use the difference in the functions of components as the criterion for distinction. As mentioned throughout the specification and claims, "comprising" or "including" is an open-ended term and should be interpreted as "including but not limited to". The subsequent description of the specification is the preferred implementation mode for implementing the present invention, but the description is for the purpose of the general principle 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 what is defined by the appended claims.

[0037] For the convenience of understanding the embodiments of the present invention, the following will further explain with specific embodiments as examples in conjunction with the drawings, and each drawing does not constitute a limitation on the embodiments of the present invention.

[0038] As Figures 1 to 4 shown, the aircraft DC arc fault detection method based on the Euclidean distance of current spectrum includes the following steps:

[0039] The first step is to measure the current data of a time window of the aircraft DC electrical circuit.

[0040] In the second step, calculate the Euclidean distance of the current spectrum between the current data in the current time window and the current data in the time window before a predetermined moment; further, by comparing the spectra of the normal current and the arc fault current, select a section with a relatively large difference between the two spectra as the frequency band range for calculating the Euclidean distance. Further, the frequency band range includes the 200 Hz - 15 kHz and 130 kHz - 150 kHz frequency bands.

[0041] In the third step, calculate the eigenvalue ratio of the Euclidean 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;

[0042] In the fourth step, set a fault threshold according to the fault characteristics of different types of arcs and the change of the Euclidean distance of the current spectrum under the load - shedding condition, compare the eigenvalue ratio with the fault threshold, when the eigenvalue ratio reaches the fault threshold, the fault cumulative value is incremented by 1, if the cumulative value exceeds a predetermined value, indicating that faults are determined in multiple time windows, then it is determined that an arc fault has occurred.

[0043] In a preferred embodiment of the aircraft DC arc fault detection method based on the Euclidean distance of the current spectrum, a fifth step is further included. If no arc fault is detected, repeat the first step to the fourth step to monitor the aircraft DC electrical circuit.

[0044] In a preferred embodiment of the aircraft DC arc fault detection method based on the Euclidean distance of the current spectrum, in the first step, the current data is filtered by a high - pass filter with a cut - off frequency of 100 Hz.

[0045] In a preferred embodiment of the aircraft DC arc fault detection method based on the Euclidean distance of the current spectrum, the time window is 10 ms, the time window moving step size is 5 ms, and the predetermined moment is 0.5 s.

[0046] In a preferred embodiment of the aircraft DC arc fault detection method based on the Euclidean distance of the current spectrum, the calculation formula of the Euclidean distance of the current spectrum is as shown in formula (1):

[0047] (1)

[0048] where I 1 (F) and I 1 (F) are the spectra obtained after the fast Fourier transform (FFT) of the current data in the current time window and the current data in the time window before a predetermined moment, n and m are the data point numbers corresponding to the starting frequency and the ending frequency of the selected frequency band, and ED is the Euclidean distance of the current spectrum between the two spectra calculated.

[0049] In a preferred embodiment of the described aircraft DC arc fault detection method based on the Euclidean distance of current spectra, the fault characteristics of different types of arcs include series arc faults, parallel arc faults, and vibrating arc faults. The load switching conditions include resistive loads, capacitive loads, and inductive loads. The capacitive load includes a simulated circuit built according to the actual working load characteristics of the aircraft, and the inductive load uses the motors actually used in the aircraft.

[0050] An aircraft DC arc fault detection system includes

[0051] a current data measurement unit for measuring the current data of an aircraft DC electrical circuit in a time window;

[0052] a Euclidean distance calculation unit for calculating the Euclidean distance of the current spectra between the current data of the current time window and the current data of the time window before a predetermined moment;

[0053] a comparison unit for calculating the eigenvalue ratio of the Euclidean distance to the historical value, where the eigenvalue ratio is calculated by comparing the eigenvalue of the latest time window obtained over time with the historical average of the eigenvalues of a plurality of consecutive time windows before a predetermined moment;

[0054] a determination unit for setting a fault threshold according to the fault characteristics of different types of arcs and the change of the Euclidean distance of the current spectra under load switching conditions, comparing the eigenvalue ratio with the fault threshold, when the eigenvalue ratio reaches the fault threshold, the fault cumulative value is incremented by 1, and if the cumulative value exceeds a predetermined value, indicating that faults are determined in multiple time windows, then it is determined that an arc fault has occurred.

[0055] In a preferred embodiment of the described system, the aircraft DC electrical circuit includes a DC power source, a solid-state power controller, an arc generating device, and a load.

[0056] A computer storage medium includes computer instructions that, when running on a computer, cause the computer to execute the described method.

[0057] An electronic device includes:

[0058] a memory, a processor, and a computer program stored on the memory and executable on the processor, where

[0059] when the processor executes the program, the described method is implemented.

[0060] In one embodiment, the method includes

[0061] 1. Measure the current data of a time window of the measurement circuit. The size of the time window is selected as 10 ms, and the moving step of the time window is selected as 5 ms. 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;

[0062] 2. Calculate the Euclidean distance between the current time window and the time window 0.5 s ago;

[0063] 3. Calculate the ratio of the Euclidean distance to the historical value. The calculation method is to take the ratio of the eigenvalue of the latest time window obtained as time flows to the historical average value of the eigenvalues of 5 consecutive time windows 0.5 s ago;

[0064] 4. According to the fault characteristics of different types of arcs and combined with the change of the Euclidean distance under the condition of load shedding, set a fault threshold, and compare the obtained ratio data with the fault threshold. When the eigenvalue ratio reaches the requirements of the fault threshold setting, the fault cumulative value is incremented by 1. If the cumulative value exceeds a certain value, indicating that multiple time windows determine the existence of a fault, then it is determined that an arc fault has occurred;

[0065] 5. If the algorithm does not detect the occurrence of an arc fault, repeat steps 1 to 4.

[0066] In one embodiment, as Figure 2 shown is the experimental circuit structure of series, vibration, and parallel arc faults. The Solid-State Power Controller (SSPC) is an intelligent switching device that integrates the conversion function of a relay and the circuit protection function of a circuit breaker in an aircraft and is connected in series into the circuit to simulate the actual electrical system of the aircraft. The series and vibration arc generating devices are connected in series with the load. To ensure that the loop current size does not exceed the maximum current that the experimental equipment can withstand after the 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. 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 vibration arcs. Two voltage levels of 28 V and 270 V are set, and the maximum current range is 2 - 40 A. The load types include pure resistive load, capacitive load, and inductive load. The capacitive load is a simulated circuit built according to the actual working load characteristics of the aircraft, and the inductive load uses the actual motor used in the aircraft. The capacitive load circuit diagram of the 270 V current level is as Figure 3 shown. The current size can be adjusted by replacing the resistor R2. The DC / DC module is connected after the 270 V power supply, and its function is to convert the 270 V voltage into 28 V. Select the Euclidean distance of the current spectrum as the criterion feature quantity. The calculation formula of the Euclidean distance is as shown in formula (1):

[0067] (1)

[0068] Among which I 1 (F) and I 1 (F) are the spectra obtained after performing fast Fourier transform (FFT) on the current time window and the time window 0.5 s ago. n and m are the numbers of the data points corresponding to the starting frequency and the ending frequency of the selected frequency band that are closest to each other. ED is the Euclidean distance between the two spectra calculated. This characteristic quantity can reflect the difference between different spectral vectors, thereby realizing the distinction between arc faults and normal operating conditions. Comparing the latest value of the obtained Euclidean distance with the historical average value can eliminate the numerical differences brought by different operating conditions and improve the applicable range of the algorithm. When no arc fault occurs, the current is relatively stable and the Euclidean distance ratio is close to 1. As Figure 4 shown in the calculation effect of the DC series arc waveform and the Euclidean distance of the spectrum before and after the fault occurs. The moment of arc occurrence is at time 0. After normalizing by taking the ratio, the value of the Euclidean distance of the spectrum before the arc occurs is about 1 and is relatively stable. After the arc fault occurs, the Euclidean distance of the spectrum increases significantly. By reasonably setting the threshold interval, the occurrence of arc faults can be identified.

[0069] 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. These all fall within the scope of protection of the present invention.

Claims

1. A method for detecting aircraft DC arc faults based on Euclidean distance of current spectrum, characterized in that: The steps include: The first step is to measure the current data of a time window of the aircraft DC electrical circuit; The second step is to calculate the Euclidean distance of the current spectrum between the current data of the current window and the current data of the time window before the predetermined moment; The third step is to calculate the characteristic value ratio of the Euclidean distance and the historical value, wherein the characteristic value of the latest time window obtained over time is compared with the historical average of the characteristic values ​​of multiple consecutive time windows before the predetermined time. The fourth step is to set a fault threshold according to the fault characteristics of different types of arcs and the change in the Euclidean distance of the current spectrum under load shedding conditions, and compare the characteristic value ratio with the fault threshold. When the characteristic value ratio reaches the fault threshold, the fault cumulative value is increased by 1. If the cumulative value exceeds a predetermined value, indicating that a fault exists in multiple time windows, it is determined that an arc fault has occurred.

2. The aircraft DC arc fault detection method based on current spectrum Euclidean distance according to claim 1, characterized in that: Preferably, the method further comprises a fifth step, wherein if no arc fault is detected, steps 1 to 4 are repeated to monitor the aircraft DC electrical circuit.

3. The aircraft DC arc fault detection method based on current spectrum Euclidean distance according to claim 1, characterized in that: In the first step, the current data were filtered through a high pass filter with a cutoff frequency of 100 Hz.

4. The aircraft DC arc fault detection method based on current spectrum Euclidean distance according to claim 1, characterized in that: The time window is 10 ms, the time window moving step is 5 ms, and the predetermined time is 0.5 s.

5. The aircraft DC arc fault detection method based on current spectrum Euclidean distance according to claim 1, characterized in that: The calculation formula of the current spectrum Euclidean distance is shown in formula (1): (1) Where I1(F) and I1(F) are the spectra obtained by fast Fourier transform (FFT) of the current data in the current time window and the current data in the time window before the predetermined moment, n and m are the data point numbers corresponding to the starting frequency and the ending frequency of the selected frequency band, and ED is the calculated Euclidean distance of the current spectrum between the two spectrum segments.

6. The aircraft DC arc fault detection method based on current spectrum Euclidean distance according to claim 1, characterized in that: The fault characteristics of different types of arcs include series arc fault, parallel arc fault and vibration arc fault. The load cutting conditions include pure resistive load, capacitive load and inductive load. The capacitive load includes a simulation circuit built according to the actual working load characteristics of the aircraft, and the inductive load adopts the motor actually used in the aircraft.

7. An aircraft DC arc fault detection system, characterized in that: These include, A current data measurement unit, which is used to measure the current data of a time window of a DC electrical circuit of the aircraft; A Euclidean distance calculation unit, which is used to calculate the Euclidean distance of the current spectrum of the current data in the current time window and the current data in the time window before the predetermined moment; A comparison unit, which is used to calculate the characteristic value ratio of the Euclidean distance and the historical value, wherein the characteristic value of the latest time window obtained over time is compared with the historical average of the characteristic values ​​of multiple consecutive time windows before a predetermined time; A determination unit is used to set a fault threshold according to the fault characteristics of different types of arcs and the change of the Euclidean distance of the current spectrum under load shedding conditions, and compare the characteristic value ratio with the fault threshold. When the characteristic value ratio reaches the fault threshold, the fault cumulative value is increased by 1. If the cumulative value exceeds a predetermined value, it indicates that a fault is determined to exist in multiple time windows, and then it is determined that an arc fault occurs.

8. The system according to claim 7, characterized in that The aircraft DC electrical circuit includes a DC source, a solid-state power controller, an arc generating device and a load.

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 6.

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 6 is implemented.

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