Non-power-frequency periodic signal detection method, device, equipment, medium and program product

Abstract

The embodiment of the invention discloses a non-power-frequency periodic signal detection method, device and equipment, a medium and a program product. Comprises: obtaining a first signal sampling sequence; the sampling length of the first signal sampling sequence is greater than or equal to a multi-frequency-point disturbance signal injection period; according to the first signal sampling sequence, determining a window length and a window overlapping rate corresponding to each to-be-detected frequency; the to-be-detected frequency is a disturbance signal frequency corresponding to the multi-frequency-point disturbance signal; acquiring a to-be-processed signal sampling sequence, performing parallel frequency spectrum information extraction on the to-be-processed signal sampling sequence through each window length and each window overlapping rate, and determining frequency spectrum information corresponding to each to-be-detected frequency; and according to the frequency spectrum information corresponding to each to-be-detected frequency, signal reconstruction is carried out on each to-be-detected frequency, and a reconstruction waveform corresponding to each to-be-detected frequency is determined. The requirement of a novel power system for quick response is better met, and the precision and efficiency of non-power-frequency periodic signal detection reconstruction of the power system are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of signal processing, and in particular to a non-power frequency periodic signal detection method, device, equipment, medium and program product. BACKGROUND

[0002] With the rapid development of power networks, new power systems characterized by high proportion of energy generation and high proportion of power electronic equipment are accelerating the formation. This transformation brings unprecedented challenges to the stable and reliable operation of the power grid, and the fault characteristics, load fluctuations and dynamic behavior of the power grid are becoming increasingly complex. Traditional passive detection and protection methods have been difficult to meet the timeliness, accuracy and reliability requirements of current system state perception. Actively injecting known disturbance signals and analyzing their response characteristics in the power grid provides a new idea for improving the timeliness and accuracy of state perception, for example, based on the injection of log-distributed or uniformly distributed multi-frequency point disturbance signals, the real-time perception of the system state can be identified by detecting the response signal.

[0003] The current signal detection method is mainly based on the Fourier transform theory, which performs well in the steady state working condition, that is, in the power system working at the power frequency. However, it is difficult to adapt to the dynamic operation environment of the new power system. The fixed window length sampling mechanism makes it difficult for the system to balance the frequency resolution and real-time requirements, especially when detecting non-power frequency periodic multi-frequency interharmonics. In addition, the existing multi-frequency point detection scheme has a time accumulation delay problem, and the algorithm parameters and data buffer need to be reinitialized when switching between different frequency points, which greatly reduces the detection real-time performance and makes it difficult to realize multi-frequency point and continuous fast scanning. Even if the Goertzel algorithm is used to process a single frequency point, the single frequency point detection logic, the empirical fixed window length and the overlap rate cannot meet the demand of synchronous extraction of multi-dimensional state information under complex working conditions. SUMMARY

[0004] The present application provides a non-power frequency periodic signal detection method, device, equipment, medium and program product, which dynamically sets window parameters for different non-power frequency periodic signals during signal detection, so that the corresponding window parameters can be adaptively used to complete the parallel detection and acquisition of the necessary information for signal reconstruction when reconstructing different signals, thereby improving the accuracy and efficiency of non-power frequency periodic signal detection and reconstruction of the power system.

[0005] In a first aspect, an embodiment of the present application provides a non-power frequency periodic signal detection method, comprising:

[0006] obtaining a first signal sampling sequence; the sampling length of the first signal sampling sequence is greater than or equal to the injection period of the multi-frequency point disturbance signal;

[0007] According to the first signal sample sequence, the window length and the window overlap rate corresponding to each to-be-detected frequency are determined; the to-be-detected frequency is a disturbance signal frequency corresponding to the multi-frequency point disturbance signal;

[0008] The to-be-processed signal sample sequence is acquired, parallel spectrum information extraction is performed on the to-be-processed signal sample sequence through the window lengths and the window overlap rates, and the spectrum information corresponding to each to-be-detected frequency is determined;

[0009] According to the spectrum information corresponding to each to-be-detected frequency, signal reconstruction is performed on each to-be-detected frequency respectively, and the reconstructed waveform corresponding to each to-be-detected frequency is determined.

[0010] In a second aspect, an embodiment of the present application further provides a non-power frequency periodic signal detection device, which comprises:

[0011] A sequence acquisition module is configured to acquire a first signal sample sequence; the sampling length of the first signal sample sequence is greater than or equal to a multi-frequency point disturbance signal injection period;

[0012] A window information determination module is configured to determine, according to the first signal sample sequence, the window length and the window overlap rate corresponding to each to-be-detected frequency; the to-be-detected frequency is a disturbance signal frequency corresponding to the multi-frequency point disturbance signal;

[0013] A spectrum information determination module is configured to acquire a to-be-processed signal sample sequence, perform parallel spectrum information extraction on the to-be-processed signal sample sequence through the window lengths and the window overlap rates, and determine the spectrum information corresponding to each to-be-detected frequency;

[0014] A signal reconstruction module is configured to perform signal reconstruction on each to-be-detected frequency according to the spectrum information corresponding to each to-be-detected frequency, and determine the reconstructed waveform corresponding to each to-be-detected frequency.

[0015] In a third aspect, an embodiment of the present application further provides a non-power frequency periodic signal detection device, which comprises:

[0016] At least one processor; and a memory connected with the at least one processor in communication;

[0017] The memory stores a computer program which can be executed by the at least one processor, and the computer program is executed by the at least one processor, so that the at least one processor can implement the non-power frequency periodic signal detection method of any embodiment of the present application.

[0018] In a fourth aspect, an embodiment of the present application further provides a storage medium containing computer executable instructions, which are used to execute the non-power frequency periodic signal detection method of any embodiment of the present application when executed by a computer processor.

[0019] In a fifth aspect, the embodiments of the present application further provide a computer program product comprising a computer program, which, when executed by a processor, is configured to perform the non-power frequency periodic signal detection method of any of the embodiments of the present application.

[0020] The non-power frequency periodic signal detection method, device, equipment, medium and program product provided by the embodiments of the present application comprise the following steps: obtaining a first signal sampling sequence; the sampling length of the first signal sampling sequence is greater than or equal to the injection period of a multi-frequency point disturbance signal; determining the window length and the window overlap rate corresponding to each to-be-detected frequency according to the first signal sampling sequence; the to-be-detected frequency is the disturbance signal frequency corresponding to the multi-frequency point disturbance signal; obtaining a to-be-processed signal sampling sequence; performing parallel spectrum information extraction on the to-be-processed signal sampling sequence through the window length and the window overlap rate, and determining the spectrum information corresponding to each to-be-detected frequency; and performing signal reconstruction on each to-be-detected frequency respectively according to the spectrum information corresponding to each to-be-detected frequency, and determining the reconstructed waveform corresponding to each to-be-detected frequency. Through the above technical solutions, before the to-be-processed signal containing superimposed signals of different frequencies obtained is detected and reconstructed for different frequencies, the window length and the window overlap rate are determined for different frequencies of the non-power frequency period that needs to be detected in the power system, the dynamic window parameter setting for different frequency signals is realized, the corresponding window parameter setting can be adaptively used to complete the detection and acquisition of the necessary information for the reconstruction of the multi-frequency point inter-harmonic signal of the non-power frequency period when the different frequency signals are detected. At the same time, since different window parameters are maintained for different frequency signals, the spectrum information extraction of the frequency signals can be performed in parallel, the non-power frequency periodic signal detection efficiency is greatly improved, the demand for fast response of the new power system is better met, and the accuracy and efficiency of the non-power frequency periodic signal detection of the power system are improved.

[0021] It should be understood that the content described in this part is not intended to identify key or important features of the embodiments of the present application, nor is it used to limit the scope of the present application. Other features of the present application will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0023] Figure 1 A flowchart of a non-power frequency periodic signal detection method provided for the first embodiment of the present application;

[0024] Figure 2An application architecture example diagram of a non-power frequency periodic signal detection method provided for the first embodiment of the present application is shown in Figure 1.

[0025] Figure 3 A flow chart of a non-power frequency periodic signal detection method provided for the second embodiment of the present application is shown in Figure 2.

[0026] Figure 4 A flow chart example diagram of substituting the first signal sampling sequence, each to-be-detected frequency, the window length adjustment factor value range, the window overlap rate value range, and the sampling frequency of the first signal sampling sequence into the pre-constructed multi-target reward function, and solving in the algorithm state space with the maximum reward value as the target to determine the window length and window overlap rate corresponding to each to-be-detected frequency provided for the second embodiment of the present application is shown in Figure 3.

[0027] Figure 5 A structural schematic diagram of a non-power frequency periodic signal detection device provided for the third embodiment of the present application is shown in Figure 4.

[0028] Figure 6 A structural schematic diagram of a non-power frequency periodic signal detection device provided for the fourth embodiment of the present application is shown in Figure 5. DETAILED DESCRIPTION

[0029] In order to make the personnel in the technical field better understand the present application scheme, the technical scheme in the embodiments of the present application will be described clearly and completely below in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by the personnel in the field without creative labor should belong to the protection scope of the present application.

[0030] It should be noted that the terms "first", "second", and the like in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily have to be used to describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0031] Embodiment one

[0032] Figure 1A flowchart of a non-power frequency cycle signal detection method provided for the embodiment one of the present application, the embodiment of the present application can be applicable to the single frequency point interharmonic signal detection reconstruction of the composite signal affected by the different frequency disturbance signals of the non-power frequency cycle in the power network, the non-power frequency cycle signal detection method can be executed by a non-power frequency cycle signal detection device, the non-power frequency cycle signal detection device can be realized by software and / or hardware, and the non-power frequency cycle signal detection device can be configured in a non-power frequency cycle signal detection equipment. Optionally, the non-power frequency cycle signal detection equipment can be a notebook, a desktop computer, and a smart tablet, etc., and the embodiment of the present application does not limit this.

[0033] In order to better understand the non-power frequency cycle signal detection method proposed in the embodiment of the present application, the application scenario of the non-power frequency cycle signal detection method is first introduced herein. Figure 2 An application architecture example diagram of the non-power frequency cycle signal detection method provided for the embodiment one of the present application. For the scheme proposed in the power network, the response characteristics of the known disturbance signal are analyzed by actively injecting the known disturbance signal, and the timeliness and accuracy of the power grid state perception are improved, which can be realized by the architecture as shown in Figure 2 , which includes an AC bus, a distributed power source grid connection module, a multi-frequency point signal injection device, a distribution terminal unit (DTU) sampling device, and a non-power frequency cycle signal detection equipment.

[0034] Among the distributed power source grid connection module, the direct current voltage U dc generated by the new energy power generation system (such as photovoltaic power generation, etc.) is connected to the direct current side of the direct current / alternating current (DC / AC) inverter; the AC side of the DC / AC inverter is connected to the load and the AC bus. The multi-frequency point disturbance signal injection device realizes the injection of the multi-frequency point disturbance signal by using the grid-connected converter in the new power system, and outputs three-phase disturbance currents i ha , i hb , and i hc ; the measurement position of the DTU sampling device is the connection position of the distributed power source grid connection module and the AC power grid; the DTU sampling device is used to collect the signal of the grid connection point of the distributed power source grid connection module, which can be understood as the signal of the distributed power source grid connection module affected by the multi-frequency point disturbance signal injected by the multi-frequency point disturbance signal injection device. Since the signal collected by the DTU sampling device is simultaneously affected by the disturbance signals of multiple frequency points, in order to better distinguish the influence of different frequency disturbance signals on the distributed power source grid connection module, the embodiment of the present application proposes a non-power frequency cycle signal detection method to realize the detection and reconstruction of different frequency point disturbance signals in a parallel processing manner.

[0035] As Figure 1 shown, the non-power frequency cycle signal detection method provided by the embodiment of the application specifically comprises the following steps:

[0036] S101, acquiring a first signal sampling sequence.

[0037] The sampling length of the first signal sampling sequence is greater than or equal to a multi-frequency point disturbance signal injection period.

[0038] In the embodiment, the first signal sampling sequence can be specifically understood as a sequence formed by signals affected by the multi-frequency point disturbance signal in the sampling order, which is collected by the DTU sampling device in the above-mentioned Figure 2 It can be understood that the first signal sampling sequence is not a sequence directly used for signal reconstruction, but a signal acquired in the initial stage of signal sampling, which is used for dynamic window parameter setting of the multi-frequency point disturbance signal corresponding to the multi-disturbance signal frequency. It can be understood that the first signal sampling sequence contains the multi-frequency point inter-harmonic signal of the non-power frequency cycle caused by the injection of the multi-frequency point disturbance signal of the non-power frequency cycle.

[0039] In the embodiment, the multi-frequency point disturbance signal injection period can be specifically understood as the time required for the multi-frequency point disturbance signal injection device in the above-mentioned Figure 2 to complete at least one cycle of injection of disturbance signals of all different frequencies. It can be understood that in order to enable dynamic window parameter setting of all disturbance signal frequencies in the multi-frequency point disturbance signal according to the first signal sampling sequence, the signals in the first signal sampling sequence should contain the disturbance of all disturbance signal frequencies, that is, at least one multi-frequency point disturbance signal injection period of the multi-frequency point disturbance signal injection device needs to be collected, and therefore, the sampling length of the first signal sampling sequence needs to be greater than or equal to the multi-frequency point disturbance signal injection period.

[0040] Specifically, when it is necessary to perceive the state of the power network, the multi-frequency point disturbance signal can be injected into the power network, and the corresponding sampling device can complete signal sampling at the sampling measurement position. The signal sequence collected initially for at least one multi-frequency point disturbance signal injection period is determined as the first signal sampling sequence.

[0041] S102, determining the window length and the window overlap rate corresponding to each to-be-detected frequency according to the first signal sampling sequence.

[0042] The to-be-detected frequency is the disturbance signal frequency corresponding to the multi-frequency point disturbance signal.

[0043] In the embodiment, the disturbance signal frequency can be specifically understood as the frequency of the disturbance signal corresponding to different frequency points in the multi-frequency point disturbance signal. The window length can be specifically understood as the time window length required for accurately detecting the frequency signal to be detected. The window overlap rate can be specifically understood as the proportion of the overlapping part between two consecutive windows.

[0044] It can be understood that, in the process of signal detection of each frequency to be detected, the window function is used to traverse the signal to be separated, and appropriate window length is set to better distinguish the target frequency from the interference frequency. The time window length can be selected based on the requirement of frequency domain resolution. In order to ensure the integrity of the signal information, there is a part of overlap between adjacent two windows, and the appropriate window overlap rate can be selected based on the balance of information integrity, spectral smoothness and calculation efficiency.

[0045] Specifically, after obtaining the first signal sampling sequence, the influence of the disturbance signal corresponding to each frequency to be detected on the first signal sampling sequence is determined, the window length and the window overlap rate corresponding to different frequencies to be detected are dynamically solved, and the solved window length and window overlap rate are applied to the process of detecting and reconstructing the multi-frequency point interharmonic signal in the non-power frequency cycle of the actual power network sampling.

[0046] Compared with the prior art in which the window length is fixed as half a cycle or a full cycle, and the window overlap rate is set as 0.5-0.75 according to experience, the technical scheme of the embodiment of the present application can better adapt to dynamic scenarios such as power grid noise mutation and frequency point drift. The situation that the fixed window length leads to insufficient signal-to-noise ratio and increased amplitude detection error when the background noise is enhanced is effectively avoided. While ensuring the detection accuracy, the calculation delay is minimized by setting the appropriate window overlap rate, and the balance between accuracy and real-time performance is achieved.

[0047] S103, obtaining a signal sampling sequence to be processed, performing parallel spectrum information extraction on the signal sampling sequence to be processed through the window lengths and the window overlap rates, and determining the spectrum information corresponding to each frequency to be detected.

[0048] In the embodiment, the signal sampling sequence to be processed can be specifically understood as the signal sampling sequence obtained by the above Figure 2The signal affected by the multi-frequency point disturbance signals and requiring single-frequency point signal detection and reconstruction is collected by the middle DTU sampling device and forms a sequence according to the sampling order. It can be understood that the sampling time of the signal sampling sequence to be processed should be after the first signal sampling sequence, but the sampling position and sampling frequency should be consistent with the first signal sampling sequence, so that the window length and window overlap rate corresponding to each detection frequency determined based on the first signal sampling sequence can be adapted to the processing of the signal sampling sequence to be processed. It can be understood that the signal sampling sequence to be processed is consistent with the first signal sampling sequence, and contains the non-power frequency period multi-frequency point interharmonic signals generated by the injection of non-power frequency period multi-frequency point disturbance signals.

[0049] In the embodiment, the spectrum information can be specifically understood as a characteristic used to describe the signal in the frequency domain, such as can include the amplitude and phase of the signal, and the like, and the embodiment of the application does not limit this. It can be understood that since the non-power frequency period multi-frequency point interharmonic signal detection and reconstruction for the signal sampling sequence to be processed is performed by using a window function, the spectrum information extraction processing can be performed once for each window when the spectrum information is extracted, that is, after the signal sampling sequence to be processed is processed, the spectrum information corresponding to each detection frequency can have multiple.

[0050] Specifically, the signal sampling sequence to be processed requiring signal reconstruction processing is obtained, the window length and window overlap rate are substituted into the algorithm corresponding to the single-frequency point signal spectrum information extraction, the spectrum information of the signal sampling sequence to be processed can be extracted in parallel by the algorithm after the window length and window overlap rate are substituted for each detection frequency, and after the spectrum information extraction of the entire signal sampling sequence to be processed is completed, the spectrum information corresponding to each detection frequency is obtained.

[0051] For example, the algorithm for extracting the single-frequency point interharmonic signal spectrum information of the signal sampling sequence to be processed can include Goertzel algorithm, improved Goertzel algorithm, and the like, and the embodiment of the application does not limit this.

[0052] In S104, according to the spectrum information corresponding to each detection frequency, the signal reconstruction is performed on each detection frequency respectively, and the reconstructed waveform corresponding to each detection frequency is determined.

[0053] In the embodiment, the signal reconstruction can be specifically understood as a process of restoring the signal corresponding to each detection frequency mixed with other signals based on the known frequency domain signal characteristics.

[0054] Specifically, according to the frequency domain signal characteristics contained in the spectrum information corresponding to each detection frequency, the signal corresponding to each detection frequency is restored and reconstructed respectively, and the reconstructed waveform corresponding to each detection frequency is obtained.

[0055] It can be understood that, since the spectrum information is detected in a window function traversal manner, and there is an overlapping part between different windows, when reconstructing the signal of each to-be-detected frequency, the spectrum information obtained by processing each window can be reconstructed, and then the waveforms obtained by reconstructing each window are spliced to obtain a complete reconstructed waveform corresponding to the to-be-detected frequency. The overlapping part between the waveforms caused by the window overlap can be normalized to ensure the accuracy of the complete reconstructed waveform. The normalization processing can be performed when each waveform is spliced, or can be performed when the reconstructed waveform is generated after all waveforms are processed, and the embodiments of the present application do not limit this.

[0056] The technical scheme of the embodiment, by obtaining a first signal sampling sequence; the sampling length of the first signal sampling sequence is greater than or equal to the multi-frequency point disturbance signal injection period; according to the first signal sampling sequence, the window length and the window overlap rate corresponding to each to-be-detected frequency are determined; the to-be-detected frequency is the disturbance signal frequency corresponding to the multi-frequency point disturbance signal; obtaining a to-be-processed signal sampling sequence, performing parallel spectrum information extraction on the to-be-processed signal sampling sequence through the window length and the window overlap rate, and determining the spectrum information corresponding to each to-be-detected frequency; according to the spectrum information corresponding to each to-be-detected frequency, the signal of each to-be-detected frequency is reconstructed respectively, and the reconstructed waveform corresponding to each to-be-detected frequency is determined. By using the above technical scheme, before detecting the to-be-processed signal containing different frequency signals, the window length and the window overlap rate corresponding to the different frequencies of the non-power frequency period in the power system are determined, which realizes the dynamic window parameter setting for different frequency signals, so that the corresponding window parameter setting can be adaptively used to detect the necessary information of the multi-frequency point interharmonic signal reconstruction of the non-power frequency period. At the same time, since different window parameters are maintained for different frequency signals, the spectrum information of each frequency signal can be extracted in parallel, which greatly improves the non-power frequency period signal detection efficiency, better meets the demand of new power system for fast response, and improves the accuracy and efficiency of non-power frequency period signal detection of the power system.

[0057] Embodiment two

[0058] Figure 3A flowchart of a non-power frequency periodic signal detection method provided for the second embodiment of the present application, the technical scheme of the second embodiment of the present application is further optimized on the basis of the above-mentioned optional technical schemes, after obtaining the first signal sampling sequence, the algorithm state space used for window length and window overlap rate calculation is initialized based on the first signal sampling sequence and each to-be-detected frequency which needs to be separately processed, and then in the initialized algorithm state space, the window length and window overlap rate applicable to each to-be-detected frequency are calculated and solved with the maximum reward value as the target according to the first signal sampling sequence, each to-be-detected frequency, the window length adjustment factor value range, the window overlap rate value range, the sampling frequency of the first signal sampling sequence and the pre-constructed multi-target reward function, realizing dynamic window parameter setting for different to-be-detected frequencies. When obtaining the to-be-processed signal sequence, not only is it directly obtained from the DTU sampling device in the circuit, but also a filter is pre-set based on the sampling frequency of the second signal sampling sequence directly sampled from the circuit, and after the second signal sampling sequence is filtered by the filter, the to-be-processed signal sequence is obtained which suppresses integer harmonic interference. Then, based on the dynamically determined window length and window overlap rate corresponding to each to-be-detected frequency, the window shift step corresponding to each to-be-detected frequency is determined, and the window length and window shift step are used as configuration parameters of the frequency spectrum information extraction algorithm for each to-be-detected frequency, so that when each to-be-processed signal in the to-be-processed signal sampling sequence is processed, each to-be-detected frequency can perform parallel frequency spectrum information extraction on the to-be-processed signal based on the configured frequency spectrum information extraction algorithm, greatly improving the non-power frequency periodic signal detection efficiency, more quickly and accurately realizing waveform reconstruction of the inter-harmonic signal corresponding to the to-be-detected frequency, and better meeting the demand of the new power system for fast response, improving the accuracy and efficiency of the power system for non-power frequency periodic signal detection and signal detection reconstruction.

[0059] As shown in Figure 3 , the non-power frequency periodic signal detection method provided by the second embodiment of the present application specifically comprises the following steps:

[0060] S201, obtaining a first signal sampling sequence.

[0061] Among them, the sampling length of the first signal sampling sequence is greater than or equal to the multi-frequency point disturbance signal injection period.

[0062] S202, initializing the algorithm state space according to the first signal sampling sequence and each to-be-detected frequency.

[0063] In this embodiment, the algorithm state space can be specifically understood as the sum of all possible situations when calculating the window length and window overlap rate corresponding to each to-be-detected frequency.

[0064] Exemplarily, the determination of the window length and the window overlap rate in the embodiment of the present application can be implemented based on a Proximal Policy Optimization (PPO) algorithm, and the initialized algorithm state space can be the PPO algorithm state space. The normalized to-be-detected frequency, the to-be-detected signal variance, the normalized to-be-detected signal fundamental amplitude, and the normalized to-be-detected signal harmonic interference intensity can be included. Since the sampling position, sampling object, and sampling frequency of the first signal sampling sequence are the same as those of the to-be-processed signal sampling sequence actually needed to be processed, each first signal in the first signal sampling sequence can also be regarded as a plurality of to-be-detected signals, so that the initialized algorithm state space can meet the processing requirements of the to-be-processed signal sampling sequence.

[0065] wherein the normalized to-be-detected frequency can be understood as a frequency value obtained by performing normalization processing on a plurality of disturbance signal frequencies corresponding to the multi-frequency point disturbance signal, that is, a frequency value obtained by performing normalization processing on the plurality of to-be-detected frequencies, and can be specifically represented by the following formula:

[0066]

[0067] wherein, is the normalized to-be-detected frequency; is the kth to-be-detected frequency; K is the total number of to-be-detected frequencies; is the minimum to-be-detected frequency in the to-be-detected frequencies; is the maximum to-be-detected frequency in the to-be-detected frequencies.

[0068] wherein the to-be-detected signal variance can be understood as the variance of a plurality of first signals contained in the first signal sampling sequence. Since the first signal sampling sequence is a signal sequence obtained by short-term sampling through the DTU acquisition device, assuming that the sampling length is M, the to-be-detected signal variance can be understood as the variance of the first signal values of the M sampling points.

[0069] wherein for the M first signals, the improved Goertzel algorithm or other algorithms based on Fourier transform can be used to calculate the amplitudes of the fundamental wave and each integer harmonic, and the amplitude can be represented as A h , , and H represents the highest order of the detected integer harmonic. When h = 1, A1 can represent the to-be-detected signal fundamental amplitude, and the obtained normalized to-be-detected signal fundamental amplitude can be represented as wherein A n represents the rated value of the to-be-detected signal.

[0070] wherein under the condition that each amplitude is known, the normalized to-be-detected signal harmonic interference intensity can be represented by the following formula:

[0071]

[0072] S203, the first signal sample sequence, each to be detected frequency, window length adjustment factor value range, window overlap rate value range and the sampling frequency of the first signal sample sequence are substituted into the pre-constructed multi-objective reward function to solve the maximum reward value in the algorithm state space, and the window length and window overlap rate corresponding to each to be detected frequency are determined.

[0073] In the embodiment, the window length adjustment factor can be specifically understood as a preset parameter for constructing an adaptive time-varying window length to adapt to the signal frequency characteristics. The window length adjustment factor value range can be specifically understood as a range of values that the window length adjustment factor of the window used when extracting the spectrum information of each to be detected frequency can take according to the actual situation. The window overlap rate value range can be specifically understood as a range of values that the window overlap rate in the window sliding process when extracting the spectrum information of each to be detected frequency can take according to the actual situation. The multi-objective reward function can be specifically understood as a function that quantifies the benefits and / or costs of multiple objectives as a unified reward signal to guide the algorithm to find the optimal solution, according to the existence of the inconsistent objectives of balancing detection accuracy and delay in the window length and window overlap rate determination process.

[0074] Specifically, for each to be detected frequency, different window length adjustment factors and window overlap rates are randomly selected from the window length adjustment factor value range and the window overlap rate value range, which are combined with the first signal sample sequence, the sampling frequency of the first signal sample sequence and the to be detected frequency as the algorithm state space initialized by the pre-constructed multi-objective reward function. The reward value corresponding to the selected window length adjustment factor and window overlap rate combination can be obtained by solving the algorithm state space, and then different combinations are substituted into the multi-objective reward function for calculation. The algorithm state space can be solved with the maximum reward value as the target for different combinations, and the most suitable window length adjustment factor and window overlap rate for the to be detected frequency are obtained. Since the window length can be determined based on the window length adjustment factor, after determining the most suitable window length adjustment factor for the to be detected frequency, the window length corresponding to the to be detected frequency can be determined. After solving the multi-objective reward function for all to be detected frequencies, the window length and window overlap rate corresponding to each to be detected frequency can be obtained.

[0075] For example, after the window length adjustment factor of the to be detected frequency is determined, the window length of the to be detected frequency can be determined based on the window length adjustment factor, the sampling frequency of the first signal sample sequence and the to be detected frequency. Specifically, it can be realized by the following formula: ​​​​​​

[0076]

[0077] It can be understood that, in order to enable the signals of different to-be-detected frequencies in the first signal sampling sequence to be completely and sufficiently collected, the sampling frequency of the first signal sampling sequence should be satisfy the Nyquist sampling theorem, that is, After the disturbance signal frequencies contained in the multi-frequency point disturbance signal are determined, the determination of the sampling frequency is completed.

[0078] Optionally, Figure 4 A flowchart for determining the window length and the window overlap rate corresponding to each to-be-detected frequency is provided for the second embodiment of the present application, which is shown in Figure 4 , and specifically includes the following steps:

[0079] S2031. For each to-be-detected frequency, at least one window length adjustment combination is determined according to the window length adjustment factor value range and the window overlap rate value range.

[0080] Specifically, for each to-be-detected frequency, random extraction is performed in the window length adjustment factor value range and the window overlap rate value range, respectively, and the window length adjustment factor and the window overlap rate obtained by random extraction are combined without repetition to obtain at least one window length adjustment combination.

[0081] It can be understood that the determined window length adjustment combinations can cover all possibilities of dynamic window parameter setting for the to-be-detected frequencies, that is, after the window length adjustment combinations are substituted into the subsequent multi-objective reward function calculation, one combination can be determined from them as the most suitable for use as the setting of the window parameters of the to-be-detected frequencies.

[0082] S2032. According to the first signal sampling sequence, the to-be-detected frequencies, the sampling frequency of the first signal sampling sequence, and each window length adjustment combination, the window length corresponding to each window length adjustment combination, the calculated amplitude, and the calculated phase are determined.

[0083] Specifically, according to the window length adjustment factor , the sampling frequency of the first signal sampling sequence , and the to-be-detected frequencies , the window length of the to-be-detected frequencies ​The window length adjustment factor in each window length adjustment combination, the first signal sample sequence, the sampling frequency of the first signal sample sequence, and the to-be-detected frequency are determined in a determined manner to determine the window length corresponding to each window length adjustment combination. Then, for each window length adjustment combination with a determined window length, the amplitude and phase corresponding to the to-be-detected frequency are calculated based on the window length, the window overlap rate in the window length adjustment combination, and the first signal sample sequence by using an improved Goertzel algorithm or other Fourier transform-based spectrum information extraction algorithm, and the calculation results are determined as the calculation amplitude and the calculation phase, respectively.

[0084] In S2033, each window length adjustment combination, and the calculation amplitude and the calculation phase corresponding to each window length adjustment combination are substituted into a pre-constructed multi-objective reward function to determine the reward value corresponding to each window length adjustment combination, and the window length adjustment combination with the largest reward value is determined as the target window length adjustment combination.

[0085] Optionally, the multi-objective reward function comprises:

[0086]

[0087] wherein, is a precision reward sub-function; is a delay penalty sub-function; is a stability reward sub-function; , and are fixed constants;

[0088] wherein, the precision reward sub-function is wherein, the theoretical amplitude can be specifically understood as the amplitude that the signal corresponding to the to-be-detected frequency should theoretically have; the theoretical phase can be specifically understood as the phase that the signal corresponding to the to-be-detected frequency should theoretically have; the delay penalty sub-function is wherein, the processing delay can be specifically understood as the delay value caused by the processing of repeated signals in different windows due to the window overlap rate; the stability reward sub-function is , is the window length adjustment factor in the window length adjustment combination, is the last window length adjustment factor.

[0089] Specifically, the calculation amplitude and the calculation phase corresponding to each window length adjustment combination are substituted into the above-mentioned precision reward sub-function respectively to determine the precision reward value corresponding to each window length adjustment combination; the window length and the window overlap rate corresponding to each window length adjustment combination are substituted into the above-mentioned delay penalty sub-function respectively to determine the delay penalty value corresponding to each window length adjustment combination; the window overlap rate corresponding to each window length adjustment combination is substituted into the above-mentioned stability reward sub-function to determine the stability reward value corresponding to each window length adjustment combination; and then the precision reward value, the delay penalty value and the stability reward value corresponding to each window length adjustment combination are substituted into the above-mentioned multi-objective reward function, so that the reward value corresponding to each window length adjustment combination can be obtained. At this time, the window length adjustment combination corresponding to the maximum reward value in the reward values can be determined as the target window length adjustment combination to be selected.

[0090] S2034, determining the window length and the window overlap rate of the to-be-detected frequency according to the target window length adjustment combination.

[0091] Specifically, after the target window length adjustment combination is determined, the window length of the to-be-detected frequency can be calculated in the same way as the above-mentioned window length calculation based on the window length adjustment factor in the target window length adjustment combination, the to-be-detected frequency and the sampling frequency corresponding to the first signal sampling sequence, and the window overlap rate in the target window length adjustment combination can be directly determined as the window overlap rate corresponding to the to-be-detected frequency.

[0092] S204, acquiring a second signal sampling sequence.

[0093] In the embodiment, the second signal sampling sequence can be specifically understood as a sequence composed of a plurality of signals affected by multi-frequency point disturbance signals and needing to be detected and reconstructed in a single frequency point, which are collected by the above-mentioned DTU sampling device and arranged in a sampling order. Figure 2 It can be understood that the second signal sampling sequence is consistent with the first signal sampling sequence, and contains multi-frequency point inter-harmonic signals of non-working frequency periods generated by the injection of multi-frequency point disturbance signals of non-working frequency periods.

[0094] The sampling frequency of the second signal sampling sequence is consistent with that of the first signal sampling sequence, and the sampling frequency is determined according to each to-be-detected frequency.

[0095] It can be understood that the above-mentioned determination method of the sampling frequency for the first signal sampling sequence has been described, and will not be repeated here.

[0096] S205, filtering the second signal sampling sequence by a preset filter to suppress integer harmonic interference and determining a to-be-processed signal sequence.

[0097] The preset filter is a filter set according to the sampling frequency of the second signal sampling sequence. For example, the preset filter can be a digital trap filter, or other types of filters that can suppress integer harmonic interference; this embodiment of the invention does not limit this. Taking the power system scenario targeted by this embodiment of the invention as an example, this filter will be used to filter signals in the second signal sampling sequence that are integer multiples of the power frequency period, so as to extract and detect signals that are not part of the power frequency period. Taking a digital trap filter as an example, the center frequency f of the trap filter can be set according to the power network usage scenario targeted by this embodiment of the invention. notch The settings, such as f notch The frequency is set to 50Hz, but the non-power frequency periodic signal to be extracted in this embodiment of the invention can be a signal such as 75Hz or 85Hz. A trap filter can be used to filter signals that are integer multiples of the power frequency period. Based on the known sampling frequencies of the first and second signal sampling sequences, the bandwidth BW of the trap filter can be set to... Furthermore, the filter coefficients (b, a) can be obtained by calling the iirnotch function using tools such as MATLAB, specifically as follows: .

[0098] It is understandable that the trap filter can also be used to filter the first signal sampling sequence to improve the accuracy of determining the window length and window overlap rate of each frequency to be detected based on the first signal sampling sequence. Since the sampling frequencies of the first signal sampling sequence and the second signal sampling sequence are the same, the configuration of the trap filter is also the same. The filtering process for the first signal sampling sequence will not be limited or explained here.

[0099] S206. Determine the window shift step size corresponding to each detection frequency by using the window length and window overlap rate.

[0100] Specifically, for each frequency to be detected, the difference between 1 and the window overlap rate is determined as the window non-overlap rate. The window length is multiplied by the window non-overlap rate and the nearest integer is taken. The determined integer is then used as the window shift step size.

[0101] Following the example above, let's assume the frequency to be detected... The corresponding window length is Window overlap rate The window shift step size corresponding to the frequency to be detected is... Possible forms: .

[0102] S207. For each frequency to be detected, pre-allocate a sliding buffer with a length corresponding to the window length of the frequency to be detected, and initialize the spectrum information extraction algorithm corresponding to the frequency to be detected.

[0103] Specifically, in order to achieve parallel spectrum information extraction and signal reconstruction for each frequency to be detected, a sliding buffer needs to be allocated for each frequency to be detected to store the signal required for spectrum information extraction before spectrum information extraction. Since the window lengths corresponding to different frequencies to be detected are different, when allocating the sliding buffer, a sliding buffer corresponding to its window length can be allocated for each frequency to be detected, and the spectrum information extraction algorithm that will be used to extract spectrum information from the signal in the sliding buffer corresponding to the frequency to be detected is initialized.

[0104] For example, assuming that the spectrum information extraction algorithm used in the embodiments of the present invention is the improved Goertzel algorithm, then when processing the sampled sequence of the signal to be processed, each frequency to be detected will first be... Pre-allocated length is the window length Yes, used to store the latest A sliding buffer for each signal to be processed Initialize the intermediate state of Goertzel. The global reconstruction buffer recon[m] and the weight accumulation array are used for... Initialization is performed. It's further important to clarify that, since the signal sampling sequence to be processed is not the initial sampling sequence obtained by the DTU sampling device, the global sampling counter will be reset to zero before the DTU sampling device performs the current sampling, meaning that... The global sample count will be used in the subsequent Goertzel algorithm calculation process.

[0105] S208. When the sliding buffer and window shift step size of any frequency to be detected meet the preset spectrum information extraction conditions, perform a spectrum information extraction on the frequency to be detected that meets the conditions, and update the sliding buffer of the frequency to be detected that meets the conditions according to the window shift step size, until all signals to be processed in the sampling sequence of the signal to be processed are written, and determine the spectrum information corresponding to each frequency to be detected.

[0106] In this embodiment, the preset spectrum information extraction condition can be understood as a condition pre-set according to actual conditions to trigger the extraction of spectrum information of the signal contained in the sliding buffer corresponding to the frequency to be detected. For example, the preset spectrum information extraction condition can be the sliding buffer of the frequency to be detected. China has accumulated at least One signal to be processed, and .

[0107] Specifically, when the sequence of to-be-processed signals is acquired, each to-be-processed signal is added to the end of the sliding buffer corresponding to each to-be-detected frequency when the to-be-processed signal is acquired. If the sliding buffer is full, the oldest window in the sliding buffer is removed by the window shift step, and the cycle coverage of the sliding buffer is realized. When any one of the sliding buffers in each to-be-processed frequency and the window shift step meet the preset spectrum information extraction condition, the amplitude and phase of the to-be-processed signal in the sliding window corresponding to the to-be-detected frequency are calculated by the spectrum information extraction algorithm, and the calculated amplitude and phase are taken as the spectrum information extracted in the window this time. At this time, the sliding buffer update will be triggered because the sliding buffer is full, that is, the sliding buffer of the to-be-detected frequency meeting the condition is updated according to the window shift step, and the state iteration of the spectrum information extraction algorithm is performed based on the updated sliding buffer. When the updated sliding buffer and the window shift step meet the preset spectrum information extraction condition again, the spectrum information extraction is performed on the to-be-processed signal in the sliding buffer again. In this process, each to-be-detected frequency can obtain one or more spectrum information, until all to-be-processed signals in the sequence of to-be-processed signals are written, and the spectrum information extraction of each to-be-detected frequency is stopped.

[0108] Based on the above example, a method for extracting spectrum information when the sliding buffer of a to-be-detected frequency and the window shift step meet the preset spectrum information extraction condition is shown. Taking the improvement of the Goertzel algorithm as an example, the method used when the sliding buffers of each to-be-detected frequency perform parallel spectrum information extraction is consistent, so only one description is given here:

[0109] First, extract the latest to-be-processed signal, multiply it by the Hanning window , and obtain ; wherein is:

[0110] Then, based on the intermediate state and of the Goertzel, the real part and the imaginary part are calculated:

[0111]

[0112] wherein is the angular frequency: .

[0113] Further, the amplitude and the phase are calculated:

[0114]

[0115] It should be noted that in the improved Goertzel algorithm, the phase of the target frequency component is obtained by calculating the real part and the imaginary part and using the arctangent function. However, since the position of the sampling window may not be aligned with the period of the signal, the calculated phase value is deviated. Therefore, phase compensation is needed to eliminate this deviation. That is, the calculated phase needs to be compensated, and at this time, the time when the center of the current window is calculated, and the compensated phase is obtained, which is realized by the following formula:

[0116]

[0117] Finally, the calculated amplitude and the compensated are determined as the spectral information corresponding to the frequency to be detected.

[0118] Based on the above example, the processing mode of state iteration of the spectral information extraction algorithm when the sliding buffer of the frequency to be detected satisfying the condition is updated according to the window shift step is given as follows:

[0119] Based on the updated , the improved Goertzel algorithm can accumulate the signal features of the frequency point in real time, calculate the angular frequency and the iteration coefficient , and update the intermediate state of Goertzel according to the following formula:

[0120]

[0121] Where y is the new input to the signal to be processed .

[0122] S209, according to the spectral information corresponding to each frequency to be detected, respectively, the signal reconstruction is performed on each frequency to be detected, and the reconstruction waveform corresponding to each frequency to be detected is determined.

[0123] Based on the above example, for each frequency to be detected, after the determination of the spectral information is completed, the signal reconstruction can be performed according to the spectral information to generate the reconstruction segment sample; and after the next reconstruction segment sample is generated based on the spectral information, since there is an overlapping part between the reconstruction segment sample and the previously generated reconstruction segment sample, when the two are spliced, the overlapping part needs to be normalized to ensure the accuracy of the spliced reconstruction waveform. After all the spectral information is reconstructed and spliced, the reconstruction waveform corresponding to the frequency to be detected is obtained.

[0124] Wherein, the processing mode of signal reconstruction according to the spectrum information to generate the reconstructed segment sample can be as follows:

[0125]

[0126] Wherein, is the reconstructed segment sample.

[0127] The technical scheme of the embodiment, after obtaining the first signal sampling sequence, initializes the algorithm state space for window length and window overlap rate calculation based on the first signal sampling sequence and each to-be-detected frequency which needs to be processed separately, and then in the initialized algorithm state space, the window length and window overlap rate applicable to each to-be-detected frequency are calculated and solved with the maximum reward value as the target according to the first signal sampling sequence, each to-be-detected frequency, the window length adjustment factor value range, the window overlap rate value range, the sampling frequency of the first signal sampling sequence, and the pre-constructed multi-objective reward function, realizing dynamic window parameter setting for different to-be-detected frequencies. When obtaining the to-be-processed signal sequence, not only is it directly obtained from the DTU sampling device in the circuit, but also the filter is pre-set based on the sampling frequency of the second signal sampling sequence directly sampled from the circuit. After the second signal sampling sequence is filtered by the filter, the to-be-processed signal sequence is obtained which suppresses integer harmonic interference. Then, based on the dynamically determined window length and window overlap rate corresponding to each to-be-detected frequency, the window shift step corresponding to each to-be-detected frequency is determined, and the window length and window shift step are used as configuration parameters of the spectrum information extraction algorithm for each to-be-detected frequency. When processing each to-be-processed signal in the to-be-processed signal sampling sequence, each to-be-detected frequency can perform parallel spectrum information extraction on the to-be-processed signal based on the configured spectrum information extraction algorithm, greatly improving the non-power frequency periodic signal detection efficiency, more quickly and accurately reconstructing the waveform of the to-be-detected frequency corresponding harmonic signal, and better meeting the demand of new power system for fast response, improving the accuracy and efficiency of non-power frequency periodic signal detection and signal detection reconstruction of the power system.

[0128] Embodiment three

[0129] Figure 5 The structure diagram of a non-power frequency periodic signal detection device provided by the embodiment three of the present application is shown in Figure 5 The non-power frequency periodic signal detection device includes a sequence acquisition module 31, a window information determination module 32, a spectrum information determination module 33, and a signal reconstruction module 34.

[0130] The sequence acquisition module 31 is configured to acquire a first signal sampling sequence; the sampling length of the first signal sampling sequence is greater than or equal to a multi-frequency point disturbance signal injection period; the window information determination module 32 is configured to determine a window length and a window overlap rate corresponding to each to-be-detected frequency according to the first signal sampling sequence; the to-be-detected frequency is a disturbance signal frequency corresponding to the multi-frequency point disturbance signal; the spectrum information determination module 33 is configured to acquire a to-be-processed signal sampling sequence, perform parallel spectrum information extraction on the to-be-processed signal sampling sequence through the window length and the window overlap rate, and determine spectrum information corresponding to each to-be-detected frequency; and the signal reconstruction module 34 is configured to perform signal reconstruction on each to-be-detected frequency according to the spectrum information corresponding to each to-be-detected frequency, and determine a reconstructed waveform corresponding to each to-be-detected frequency.

[0131] The technical scheme of the embodiment of the application first determines the window length and the window overlap rate corresponding to different frequencies of a non-power frequency period that needs to be detected in the power system before detecting and reconstructing the to-be-processed signal containing different frequency signals, realizes dynamic window parameter setting for different frequency signals, and enables adaptive use of the corresponding window parameter setting to complete the detection and acquisition of the necessary information for the reconstruction of the multi-frequency point interharmonic signal of the non-power frequency period when detecting different frequency signals. At the same time, because different window parameters are maintained for different frequency signals, the spectrum information of each frequency signal can be extracted in parallel, the efficiency of non-power frequency period signal detection is greatly improved, the demand of the new power system for fast response is better met, and the accuracy and efficiency of non-power frequency period signal detection of the power system are improved.

[0132] Optionally, the window information determination module 32 is specifically configured to:

[0133] initialize an algorithm state space according to the first signal sampling sequence and each to-be-detected frequency;

[0134] substitute the first signal sampling sequence, each to-be-detected frequency, a window length adjustment factor value range, a window overlap rate value range, and a sampling frequency of the first signal sampling sequence into a pre-constructed multi-objective reward function, and perform solving in the algorithm state space with the maximum reward value as the target to determine the window length and the window overlap rate corresponding to each to-be-detected frequency.

[0135] Optionally, the window information determination module 32 is specifically configured to:

[0136] For each to-be-detected frequency, at least one window length adjustment combination is determined according to the value range of the window length adjustment factor and the value range of the window overlap rate;

[0137] According to the first signal sample sequence, the to-be-detected frequency, the sampling frequency of the first signal sample sequence, and each window length adjustment combination, a window length corresponding to each window length adjustment combination is determined, and a calculation amplitude and a calculation phase are calculated;

[0138] Each window length adjustment combination, and the calculation amplitude and the calculation phase corresponding to each window length adjustment combination are substituted into a pre-constructed multi-objective reward function to determine a reward value corresponding to each window length adjustment combination, and a window length adjustment combination with the largest reward value is determined as a target window length adjustment combination;

[0139] The window length and the window overlap rate of the to-be-detected frequency are determined according to the target window length adjustment combination.

[0140] Optionally, the multi-objective reward function comprises:

[0141]

[0142] wherein, is a precision reward sub-function; is a delay penalty sub-function; is a stability reward sub-function; , and are fixed constants;

[0143] wherein, the precision reward sub-function is , the delay penalty sub-function is , and the stability reward sub-function is , is a window length adjustment factor in the window length adjustment combination, is a previous window length adjustment factor.

[0144] Optionally, the spectrum information determination module 33 is specifically configured to:

[0145] obtain a second signal sample sequence;

[0146] filter the second signal sample sequence through a preset filter to suppress integer harmonic interference to determine a to-be-processed signal sequence;

[0147] wherein, the preset filter is a filter set according to the sampling frequency of the second signal sample sequence; the sampling frequency of the second signal sample sequence is consistent with that of the first signal sample sequence, and the sampling frequency is determined according to each to-be-detected frequency;

[0148] determine a window shift step corresponding to each to-be-detected frequency through each window length and each window overlap rate;

[0149] For each to-be-detected frequency, a sliding buffer with a length corresponding to a window length of the to-be-detected frequency is pre-allocated, and a spectrum information extraction algorithm corresponding to the to-be-detected frequency is initialized;

[0150] For each to-be-processed signal in the to-be-processed signal sample sequence, the to-be-processed signal is added into the sliding buffer corresponding to each to-be-detected frequency respectively;

[0151] When the sliding buffer of any to-be-detected frequency and the window shift step meet a preset spectrum information extraction condition, spectrum information extraction is performed on the to-be-detected frequency meeting the condition, and the sliding buffer of the to-be-detected frequency meeting the condition is updated according to the window shift step, until all to-be-processed signals in the to-be-processed signal sample sequence are written, and the spectrum information corresponding to each to-be-detected frequency is determined.

[0152] The non-power frequency periodic signal detection device provided by the embodiment of the present application can execute the non-power frequency periodic signal detection method provided by any embodiment of the present application, and has the corresponding function modules and beneficial effects of the execution method.

[0153] Embodiment Four

[0154] Figure 6 A structural schematic diagram of a non-power frequency periodic signal detection device provided by Embodiment Four of the present application. The non-power frequency periodic signal detection device 40 can be intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, communication base stations, and other suitable computers. The non-power frequency periodic signal detection device 40 can also represent various forms of mobile devices, such as personal digital assistants, cellular telephones, smart phones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are merely examples, and are not intended to limit the implementation of the present application described and / or claimed herein.

[0155] As Figure 6As shown, the non-power frequency periodic signal detection device 40 includes at least one processor 41, and a memory, such as a read-only memory (ROM) 42, a random access memory (RAM) 43, etc., communicatively connected to the at least one processor 41, where the memory stores a computer program executable by the at least one processor. The processor 41 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 42 or loaded from the storage unit 48 into the random access memory (RAM) 43. In the RAM 43, various programs and data required for the operation of the non-power frequency periodic signal detection device 40 can also be stored. The processor 41, the ROM 42, and the RAM 43 are connected to each other through a bus 44. An input / output (I / O) interface 45 is also connected to the bus 44.

[0156] Various components in the non-power frequency periodic signal detection device 40 are connected to the I / O interface 45, including an input unit 46, such as a keyboard, a mouse, etc., an output unit 47, such as various types of displays, speakers, etc., a storage unit 48, such as a magnetic disk, an optical disk, etc., and a communication unit 49, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 49 allows the non-power frequency periodic signal detection device 40 to exchange information / data with other devices through a computer network, such as the Internet, and / or various telecommunication networks.

[0157] The processor 41 can be various general and / or special purpose processing components with processing and computing capabilities. Some examples of the processor 41 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 41 performs various methods and processes described above, such as the non-power frequency periodic signal detection method.

[0158] In some embodiments, the non-power frequency periodic signal detection method can be implemented as a computer program tangibly embodied in a computer readable storage medium, such as the storage unit 48. In some embodiments, part or all of the computer program can be loaded and / or installed onto the non-power frequency periodic signal detection device 40 via the ROM 42 and / or the communication unit 49. When the computer program is loaded into the RAM 43 and executed by the processor 41, one or more steps of the non-power frequency periodic signal detection method described above can be performed. Alternatively, in other embodiments, the processor 41 can be configured to perform the non-power frequency periodic signal detection method by any other appropriate means, such as by means of firmware.

[0159] Optionally, the embodiment of the present application further provides a computer program product, comprising a computer program which, when executed by a processor, implements the non-power frequency periodic signal detection method provided by any embodiment of the present application.

[0160] Various implementations of the systems and techniques described above can be realized in digital electronic circuitry, integrated circuitry, specially designed application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0161] Computer programs used to implement the methods of the present application can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the computer program, when executed by the processor of the machine, implements the functions / acts specified in the flowcharts and / or block diagrams. The computer program can be executed entirely on a machine, partially on a machine, partially on a machine and partially on a remote machine or entirely on a remote machine or server.

[0162] In the context of the present application, a computer-readable storage medium can be a tangible medium that can contain or store computer programs for use by or in connection with an instruction execution system, apparatus, or device. The computer-readable storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer-readable storage medium can be a machine-readable signal medium. More specific examples of the machine-readable storage medium will include one or more lines of a program of instructions in a transitory signal, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0163] To provide for interaction with a user, the systems and techniques described here can be implemented on a non-utility cycle signal detection device having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the non-utility cycle signal detection device. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0164] The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), blockchain network, and the Internet.

[0165] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. A server can be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system, to solve the defects of large management difficulty and weak business scalability in traditional physical host and VPS service.

[0166] It should be understood that the various forms of flow shown above can be re-ordered, added to, or deleted from without departing from the scope of the present application. For example, the steps recited in the present application can be executed in parallel, executed in sequence, or executed in a different order, as long as the desired results of the technical solutions of the present application are achieved, and the present application is not limited herein.

[0167] The above detailed description does not limit the scope of the application. Various modifications, combinations, sub-combinations and alternatives can be made to the detailed description. Any modification, equivalent replacement and improvement etc. made within the spirit and principle of the application shall be included in the scope of the application.

Claims

1. A non-power frequency periodic signal detection method, characterized in that, The method comprises the following steps: obtaining a first signal sample sequence; the sampling length of the first signal sample sequence is greater than or equal to the injection period of a multi-frequency point disturbance signal; determining the window length and the window overlap rate corresponding to each to-be-detected frequency according to the first signal sample sequence; the to-be-detected frequency is the disturbance signal frequency corresponding to the multi-frequency point disturbance signal; obtaining a to-be-processed signal sample sequence, performing parallel spectrum information extraction on the to-be-processed signal sample sequence through the window length and the window overlap rate, and determining the spectrum information corresponding to each to-be-detected frequency; reconstructing the signal of each to-be-detected frequency according to the spectrum information corresponding to each to-be-detected frequency, and determining the reconstructed waveform corresponding to each to-be-detected frequency.

2. The non-power frequency periodic signal detection method of claim 1, wherein, The method comprises the following steps: initializing the algorithm state space according to the first signal sample sequence and each to-be-detected frequency; substituting the first signal sample sequence, each to-be-detected frequency, the window length adjustment factor value range, the window overlap rate value range, and the sampling frequency of the first signal sample sequence into a pre-constructed multi-objective reward function to perform solving in the algorithm state space with the maximum reward value as the target to determine the window length and the window overlap rate corresponding to each to-be-detected frequency.

3. The non-power frequency periodic signal detection method of claim 2, wherein, The method comprises the following steps: for each to-be-detected frequency, determining at least one window length adjustment combination according to the window length adjustment factor value range and the window overlap rate value range; determining the window length, the calculation amplitude, and the calculation phase corresponding to each window length adjustment combination according to the first signal sample sequence, the to-be-detected frequency, the sampling frequency of the first signal sample sequence, and each window length adjustment combination; substituting each window length adjustment combination, the calculation amplitude, and the calculation phase corresponding to each window length adjustment combination into a pre-constructed multi-objective reward function to determine the reward value corresponding to each window length adjustment combination, and determining the window length adjustment combination with the maximum reward value as the target window length adjustment combination; determining the window length and the window overlap rate of the to-be-detected frequency according to the target window length adjustment combination.

4. The non-power frequency periodic signal detection method according to claim 2 or 3, characterized in that, The method comprises the following steps: wherein, is a precision reward sub-function; is a delay penalty sub-function; is a stability reward sub-function; , and are fixed constants; Wherein, the precision reward sub-function is ; the delay penalty sub-function is ; the stability reward sub-function is , the is a window length adjustment factor in a window length adjustment combination, and the is a last window length adjustment factor.

5. The non-power frequency periodic signal detection method of claim 1, wherein, The method comprises the following steps: obtaining a second signal sample sequence; filtering the second signal sample sequence through a preset filter to suppress integer harmonic interference and determining a to-be-processed signal sequence; wherein the preset filter is a filter set according to the sampling frequency of the second signal sample sequence; the sampling frequency of the second signal sample sequence is consistent with that of the first signal sample sequence, and the sampling frequency is determined according to each to-be-detected frequency.

6. The non-power frequency periodic signal detection method of claim 1, wherein, The parallel spectrum information extraction on the to-be-processed signal sample sequence is performed through the window length and the window overlap rate, and spectrum information corresponding to each to-be-detected frequency is determined, including: The window shift step corresponding to each to-be-detected frequency is determined through the window length and the window overlap rate; For each to-be-detected frequency, a sliding buffer with a length corresponding to the window length of the to-be-detected frequency is pre-allocated, and a spectrum information extraction algorithm corresponding to the to-be-detected frequency is initialized; For each to-be-processed signal in the to-be-processed signal sample sequence, the to-be-processed signal is added into the sliding buffer corresponding to each to-be-detected frequency; When the sliding buffer and the window shift step of any to-be-detected frequency meet a preset spectrum information extraction condition, spectrum information extraction is performed on the to-be-detected frequency meeting the condition, and the sliding buffer of the to-be-detected frequency meeting the condition is updated according to the window shift step, until all to-be-processed signals in the to-be-processed signal sample sequence are written, and spectrum information corresponding to each to-be-detected frequency is determined.

7. A non-power frequency cycle signal detection device, characterized in that, Comprising: A sequence acquisition module is configured to acquire a first signal sample sequence; the sampling length of the first signal sample sequence is greater than or equal to a multi-frequency point disturbance signal injection period; A window information determination module is configured to determine a window length and a window overlap rate corresponding to each to-be-detected frequency according to the first signal sample sequence; the to-be-detected frequency is a disturbance signal frequency corresponding to a multi-frequency point disturbance signal; A spectrum information determination module is configured to acquire a to-be-processed signal sample sequence, perform parallel spectrum information extraction on the to-be-processed signal sample sequence through the window length and the window overlap rate, and determine spectrum information corresponding to each to-be-detected frequency; A signal reconstruction module is configured to perform signal reconstruction on each to-be-detected frequency according to the spectrum information corresponding to each to-be-detected frequency, and determine a reconstructed waveform corresponding to each to-be-detected frequency.

8. A non-power frequency cycle signal detection device, characterized in that, Comprising: At least one processor; and a memory connected in communication with the at least one processor; Wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the non-power frequency periodic signal detection method of any one of claims 1-6.

9. A storage medium containing computer-executable instructions, wherein: The computer executable instructions, when executed by a computer processor, are used to execute the non-power frequency periodic signal detection method of any one of claims 1-6.

10. A computer program product, characterised in that, Comprising a computer program, the computer program, when executed by a processor, implements the non-power frequency periodic signal detection method of any one of claims 1-6.

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