A frequency-adaptive method for aligning multiple homologous waveforms

Abstract

The present invention discloses a frequency-adaptive alignment method for multiple homologous waveforms, including: collecting relay protection devices and fault recorder waveform files generated by the same system disturbance or fault; the minimum sampling frequency of each waveform is set as the reference frequency, and the waveform of the non-reference frequency is resampled; the analog channel with a change characteristic before and after the zero moment in the reference waveform is selected; the sampling point deviation between the waveform to be aligned and the reference waveform and the required moving angle are obtained according to the absolute value and the minimum difference of the analog channel sampling value between the waveforms as the criterion; all analog channels in the waveform to be aligned perform waveform interception and waveform movement according to the sampling sequence number deviation, and complete the alignment of different waveforms under the same time coordinate. The present invention enhances the adaptability of the waveform alignment method to the system frequency and the adaptability of the waveform morphology, improves the accuracy of waveform alignment under different working conditions of the power grid, and has better engineering application capabilities.

Description

Technical Field

[0001] The invention relates to a frequency-adaptive multiple homologous waveform alignment method, belonging to the technical field of relay protection. Background Art

[0002] At present, with the increasing scale of power grids, relay protection equipment and fault recording devices generate a large amount of waveform data during the daily operation of the power grid. Mining such data can improve the operation and maintenance level of the power system. Among them, comparing the same analog channels in different waveforms generated by the same system disturbance or fault can effectively discover the hidden dangers in the analog quantity acquisition of secondary equipment. Since a certain frequency offset may occur during the operation of the power system, which is not an accurate 50Hz, a frequency-adaptive waveform alignment method needs to be considered to improve the accuracy of waveform alignment. Summary of the invention

[0003] The technical problem to be solved by the present invention is to provide a frequency-adaptive method for aligning multiple homologous waveforms, which can effectively adapt to the alignment of multiple homologous waveforms under different frequency conditions.

[0004] The present invention adopts the following technical solutions to solve the above technical problems:

[0005] A frequency adaptive multiple homologous waveform alignment method, the method comprising the following steps:

[0006] Step 1, collect the waveform Comtrade file of the relay protection device and the fault recorder generated by the same system disturbance or fault;

[0007] Step 2: Get the sampling frequency corresponding to each waveform Comtrade file, and set the minimum sampling frequency in each waveform as the reference sampling frequency f base , the reference sampling frequency f base The corresponding waveform is set as the reference waveform, and other waveforms with non-reference sampling frequencies are interpolated using the Lagrange interpolation algorithm with f base After resampling, it is set as the waveform to be aligned;

[0008] Step 3, for all analog channels of the reference waveform, select an analog channel A having a change characteristic around time zero of the waveform;

[0009] Step 4: intercept the analog channel A described in step 3 of the reference waveform at the waveform zero time before 1 cycle and after 6 cycles to obtain the sampling point array [x base-1 ~x base-N ], N is the number of sampling points;

[0010] Step 5: intercept the analog channel A in step 3 of the waveform to be aligned at the waveform zero time before the 3 cycles and the last 8 cycles to obtain the sampling point array [y1~y M ], M is the number of sampling points, M>N;

[0011] Step 6: From the sampling point array [y1~y M ] to extract N consecutive sampling points to form [y1~y N ]、[y2~y N+1 ], ..., [y M-N ~y M ], a total of MN arrays; the sampling points of each array in the MN arrays are respectively base-1 ~x base-N ] perform point-by-point subtraction and sum the absolute values ​​of the differences of N sampling points;

[0012] Step 7: For the MN absolute value sums obtained in step 6, take the minimum value and store the sampling point arrays [y m ~y m+N ] and [x base-1 ~x base-N ] is taken as the sampling number deviation when the difference between the sampling values ​​of the reference waveform and the waveform to be aligned is the smallest;

[0013] Step 8: In the range of [-α°~α°], the sampling point array [y m ~y m+N Each sampling point in ] is moved by a step of φ° through the Lagrange interpolation algorithm to obtain 2α / φ new arrays;

[0014] Step 9: According to the waveform alignment judgment method of steps 6 and 7, the 2α / φ new arrays obtained in step 8 are aligned with [x base-1 ~x base-N ] to compare, and the absolute value and the minimum corresponding angle are the angles that the waveform to be aligned should move;

[0015] Step 10, all analog channels in the waveform to be aligned are subjected to waveform interception according to the sampling sequence deviation obtained in step 7 and waveform movement according to the movement angle obtained in step 9, so as to complete the alignment of different waveforms at the same time coordinate.

[0016] As a preferred solution of the present invention, the calculation formula of the Lagrangian interpolation algorithm in step 2 is:

[0017]

[0018] Among them, (x0,f(x0)), (x1,f(x1)), (x2,f(x2)) are three consecutive sampling points in the waveform to be aligned, x0, x1, x2 are the times corresponding to the three consecutive sampling points, f(x0), f(x1), f(x2) are the sampling values ​​corresponding to the three consecutive sampling points, and f(x) is the sampling value calculated by the Lagrange interpolation algorithm at time x.

[0019] As a preferred solution of the present invention, the specific process of step 3 is as follows:

[0020] Step 3.1, for one of the analog channels of the reference waveform, calculate the average value A of the effective value of the analog channel waveform before the zero moment of the cycle sampling before And the average value A of the effective value of the next cycle sampling after ;

[0021] Step 3.2, determine the average value A in step 3.1 before or A after Is it greater than the preset amplitude threshold? If A before or A after If the value is greater than the preset amplitude threshold, the average value greater than the preset amplitude threshold is set as the reference value A. base And proceed to step 3.3, otherwise select the next analog channel and proceed to step 3.1;

[0022] Step 3.3, if or When it is greater than the preset change threshold, the analog channel is selected as the analog channel A with change characteristics, otherwise the next analog channel is selected and step 3.1 is performed.

[0023] As a preferred solution of the present invention, the calculation formula for the absolute value sum in step 6 is:

[0024] X abs (n)=|x base-1 -y n |+|x base-2 -y n+1 |+...+|x base-N -y n+N |

[0025] Where n = 1, ..., MN, x base-1 ~x base-N are 1 to N sampling points intercepted from the reference waveform, y n ~y n+N are n to n+N sampling points intercepted from the waveform to be aligned, X abs (n) is the absolute value sum of the difference values ​​of the nth array sampling points.

[0026] As a preferred solution of the present invention, in step 8, the moving angle φ° is converted into time Δt, and the conversion formula is: Among them, the unit of φ is degree, and the unit of Δt is second; then the sampling point array [y m ~y m+N The sampling value of each sampling point in ] after moving φ°.

[0027] As a preferred solution of the present invention, the specific process of step 9 is as follows:

[0028] For the 2α / φ new arrays obtained in step 8, each new array includes N sampling points. The sampling points of each new array are respectively compared with [x base-1 ~x base-N ] are subtracted point by point, and the absolute values ​​of the differences of the N sampling points are summed up to obtain the 2α / φ absolute value sums, among which the minimum value is taken, and the angle corresponding to the absolute value and the minimum value is used as the angle at which the waveform to be aligned should be moved.

[0029] Compared with the prior art, the present invention adopts the above technical solution and has the following technical effects:

[0030] The present invention obtains waveform alignment features by adopting a method of angle step search and summing the absolute values ​​of waveform sampling value differences, thereby enhancing the adaptability of the waveform alignment method to system frequency and waveform morphology, improving the accuracy of waveform alignment under different working conditions of the power grid, and enhancing the engineering application capability of the waveform alignment method. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 The present invention is a flowchart of a frequency-adaptive alignment method for multiple homologous waveforms. DETAILED DESCRIPTION

[0032] The embodiments of the present invention are described in detail below, and examples of the embodiments are shown in the accompanying drawings. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be interpreted as limiting the present invention.

[0033] like Figure 1 FIG. 1 is a flowchart of a frequency adaptive multiple homologous waveform alignment method provided by an embodiment of the present invention, the method comprising the following steps:

[0034] Step 1: Collect the waveform files Wave1 and Wave2 of the relay protection device and the fault recorder generated by the same system disturbance or fault;

[0035] Step 2: Get the sampling frequency in the Comtrade file of each waveform, and set the minimum sampling frequency in each waveform as the reference sampling frequency f base , set the waveform of the reference sampling frequency as the reference waveform, and use the Lagrange interpolation algorithm to interpolate the waveform of the non-reference sampling frequency with f base Resample and set it as the waveform to be aligned. The waveforms used in the following steps are all waveforms at the reference sampling frequency;

[0036] The sampling frequency of Wave1 is 1200Hz, and the sampling frequency of Wave2 is 10000Hz. 1200Hz is set as the base sampling frequency, and Wave2 is resampled at 1200Hz using the Lagrange interpolation algorithm, and Wave1 is set as the base waveform;

[0037] The Lagrange interpolation algorithm formula used is:

[0038]

[0039] Where: (x0,f(x0)), (x1,f(x1)), (x2,f(x2)) are three consecutive sampling points in the waveform, x0, x1, x2 are the times corresponding to the three consecutive sampling points, f(x0), f(x1), f(x2) are the sampling values ​​corresponding to the three consecutive sampling points, and f(x) is the sampling value calculated by the Lagrange interpolation algorithm at time x.

[0040] Step 3: Select the analog channel A in the reference waveform that has a change characteristic around the zero moment of the waveform, the method is:

[0041] Step 3.1: Calculate the average value A of the effective value of the analog channel waveform before the zero moment of the cycle sampling before And the average value A of the effective value of the next cycle sampling after ;

[0042] Step 3.2: Determine A in step 3.1 before or A after Is it greater than the preset amplitude threshold 0.1? If it is greater than the preset amplitude threshold, it will be set as the reference value A base And proceed to the next step, otherwise select the next analog channel and proceed to step 3.1;

[0043] Step 3.3: If or When it is greater than the preset change threshold of 5%, the channel is selected as analog channel A with change characteristics.

[0044] Step 4: Intercept the first and last six cycles of analog channel A in the reference waveform Wave1 at time zero to obtain the sampling point array [x1 to x168 ], a total of N = 168 sampling points;

[0045] Step 5: Intercept the 3 cycles before and 8 cycles after the waveform zero time of analog channel A in the waveform to be aligned Wave2, and obtain the sampling point array [y1~y 264 ], a total of M = 264 sampling points;

[0046] Step 6: From the sampling point array [y1~y 264 ] to extract 168 consecutive sampling points to form [y1~y 168 ]、[y2~y 169 ], ..., [y 96 ~y 264 ], a total of 96 arrays; 96 arrays are respectively related to [x1~x 168 ] to perform point-by-point subtraction, and sum the absolute values ​​of the 96 sampling point differences. The calculation formula is:

[0047] X abs (n) = |x1-y n |+|x2-y n+1 |+...+|x N -y n+N |

[0048] Where: X abs (n) is the absolute value sum of the difference values ​​of the nth sampling point, n=1,...,96.

[0049] Step 7: Obtain 96 absolute values ​​and X through step 6 abs (n), take the absolute value and minimum value:

[0050] X abs (m) = min(X abs (1),X abs (2),...,X abs (MN)

[0051] Among them, X abs (m) is 96 absolute values ​​and X abs The minimum value among (n);

[0052] X abs (m) The corresponding sampling point array [y m ~y m+N ] and [x1~x N ] is taken as the sampling number deviation when the difference between the sampling values ​​of the reference waveform and the waveform to be aligned is the smallest;

[0053] Step 8: Substitute the sampling point array [y m ~y m+N] In the range of [-15°~15°], move in steps of 0.1°, and obtain 2α / φ new arrays through the Lagrange interpolation algorithm, α=15, φ=0.1, and the moving method is:

[0054] Step 8 (A): Convert the moving angle φ to time Δt using the following formula: The unit of φ is degree, and the unit of Δt is second;

[0055] Step 8 (B): Calculate the sampling value of each sampling point after it moves by Δt according to the Lagrange interpolation algorithm of formula (1);

[0056] Step 9: Use the methods of steps 6 and 7 to compare the 300 arrays obtained in step 8 with [x1~x 168 ] to compare, and the absolute value and the minimum corresponding angle are obtained, which is the angle θ that the waveform to be aligned should move;

[0057] The waveform alignment judgment method used in step 6 and step 7 is: the sampling values ​​between the waveforms are subtracted point by point and then the absolute values ​​are taken, and the absolute values ​​of the differences at each sampling point are summed up, and the minimum absolute value is used as the waveform alignment standard.

[0058] Step 10: All analog channels in the waveform to be aligned are intercepted according to the sampling value sequence deviation obtained in step 7 and the waveform is moved according to the moving angle θ obtained in step 9, so that the alignment of different waveforms at the same time coordinate can be completed.

[0059] The above embodiments are only for illustrating the technical idea of ​​the present invention, and cannot be used to limit the protection scope of the present invention. Any changes made on the basis of the technical solution in accordance with the technical idea proposed by the present invention shall fall within the protection scope of the present invention.

Claims

1. A frequency-adaptive alignment method for multiple homologous waveforms, characterized in that: The method comprises the following steps: Step 1, collect the waveform Comtrade file of the relay protection device and the fault recorder generated by the same system disturbance or fault; Step 2: Get the sampling frequency corresponding to each waveform Comtrade file, and set the minimum sampling frequency in each waveform as the reference sampling frequency f base , the reference sampling frequency f base The corresponding waveform is set as the reference waveform, and other waveforms with non-reference sampling frequencies are interpolated using the Lagrange interpolation algorithm with f base After resampling, it is set as the waveform to be aligned; Step 3, for all analog channels of the reference waveform, select an analog channel A having a change characteristic around time zero of the waveform; Step 4: intercept the analog channel A described in step 3 of the reference waveform at the waveform zero time before 1 cycle and after 6 cycles to obtain the sampling point array [x base-1 ~x base-N ], N is the number of sampling points; Step 5: intercept the analog channel A in step 3 of the waveform to be aligned at the waveform zero time before the 3 cycles and the last 8 cycles to obtain the sampling point array [y1~y M ], M is the number of sampling points, M>N; Step 6: From the sampling point array [y1~y M ] to extract N consecutive sampling points to form [y1~y N ]、[y2~y N+1 ], ..., [y M-N ~y M ], a total of MN arrays; the sampling points of each array in the MN arrays are respectively base-1 ~x base-N ] perform point-by-point subtraction and sum the absolute values ​​of the differences of N sampling points; Step 7: For the MN absolute value sums obtained in step 6, take the minimum value and store the sampling point arrays [y m ~y m+N ] and [x base-1 ~x base-N ] is taken as the sampling number deviation when the difference between the sampling values ​​of the reference waveform and the waveform to be aligned is the smallest; Step 8: In the range of [-α°~α°], the sampling point array [y m ~y m+N Each sampling point in ] is moved by a step of φ° through the Lagrange interpolation algorithm to obtain 2α / φ new arrays; Step 9: According to the waveform alignment judgment method of steps 6 and 7, the 2α / φ new arrays obtained in step 8 are aligned with [x base-1 ~x base-N ] to compare, and the absolute value and the minimum corresponding angle are the angles that the waveform to be aligned should move; Step 10, all analog channels in the waveform to be aligned are subjected to waveform interception according to the sampling sequence deviation obtained in step 7 and waveform movement according to the movement angle obtained in step 9, so as to complete the alignment of different waveforms at the same time coordinate.

2. The frequency adaptive alignment method for multiple homologous waveforms according to claim 1, characterized in that: The calculation formula of the Lagrange interpolation algorithm in step 2 is: Among them, (x0,f(x0)), (x1,f(x1)), (x2,f(x2)) are three consecutive sampling points in the waveform to be aligned, x0, x1, x2 are the times corresponding to the three consecutive sampling points, f(x0), f(x1), f(x2) are the sampling values ​​corresponding to the three consecutive sampling points, and f(x) is the sampling value calculated by the Lagrange interpolation algorithm at time x.

3. The frequency adaptive alignment method for multiple homologous waveforms according to claim 1, characterized in that: The specific process of step 3 is as follows: Step 3.1, for one of the analog channels of the reference waveform, calculate the average value A of the effective value of the analog channel waveform before the zero moment of the cycle sampling before And the average value A of the effective value of the next cycle sampling after ; Step 3.2, determine the average value A in step 3.1 before or A after Is it greater than the preset amplitude threshold? If A before or A after If the value is greater than the preset amplitude threshold, the average value greater than the preset amplitude threshold is set as the reference value A. base And proceed to step 3.3, otherwise select the next analog channel and proceed to step 3.1; Step 3.3, if or When it is greater than the preset change threshold, the analog channel is selected as the analog channel A with change characteristics, otherwise the next analog channel is selected and step 3.1 is performed.

4. The frequency adaptive alignment method for multiple homologous waveforms according to claim 1, characterized in that: The calculation formula for the absolute value sum in step 6 is: X abs (n)=|x base-1 -and n |+|x base-2 -and n+1 |+...+|x base-N -and n+N | Where n = 1, ..., MN, x base-1 ~x base-N are 1 to N sampling points intercepted from the reference waveform, y n ~y n+N are n to n+N sampling points intercepted from the waveform to be aligned, X abs (n) is the absolute value sum of the difference values ​​of the nth array sampling points.

5. The frequency adaptive alignment method for multiple homologous waveforms according to claim 1, characterized in that: In step 8, the moving angle φ° is converted into time Δt, and the conversion formula is: Among them, the unit of φ is degree, and the unit of Δt is second; then the sampling point array [y m ~y m+N The sampling value of each sampling point in ] after moving φ°.

6. The frequency adaptive alignment method for multiple homologous waveforms according to claim 1, characterized in that: The specific process of step 9 is as follows: For the 2α / φ new arrays obtained in step 8, each new array includes N sampling points. The sampling points of each new array are respectively compared with [x base-1 ~x base-N ] are subtracted point by point, and the absolute values ​​of the differences of the N sampling points are summed up to obtain the 2α / φ absolute value sums, among which the minimum value is taken, and the angle corresponding to the absolute value and the minimum value is used as the angle at which the waveform to be aligned should be moved.

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