Characteristic current signal identification method and device and phase line identification system

Abstract

The invention relates to a power line characteristic current identification method and device and a phase line identification system. The method comprises the following steps: dividing a current signal and a current signal corresponding to a characteristic frequency based on a preset time window and a preset sliding step length to obtain a first time window array and a second time window array, a first identification sequence based on direct current signal identification and a second identification sequence based on characteristic frequency identification are obtained according to the characteristic sequence; and finally, a characteristic current signal can be judged by comparing the first identification sequence and the second identification sequence with the characteristic sequence. According to the embodiment of the invention, through two modes of direct current signal identification and characteristic frequency current signal identification at the same time, accurate identification in different noise or interference environments can be realized, and the accuracy and robustness of identification are significantly improved.

Description

Technical Field

[0001] The present invention relates to the field of power line communication, and in particular to a power line characteristic current identification method, device and phase line identification system. Background Art

[0002] With the rapid progress of smart grid and power Internet of Things technologies, the automation and intelligence level of power systems has been significantly improved, especially in the field of distribution management and network topology identification. Efficient and accurate topology identification technology is of vital importance to ensuring stable operation of the power grid, optimizing resource allocation and quickly locating faults.

[0003] The topology identification method based on characteristic circuits determines the phase line or the substation to which it belongs based on whether the characteristic current is detected. However, in actual application, especially in complex broadband carrier communication environments, this method faces a series of challenges. Among them, the most prominent problem is the diversity and uncertainty of the noise environment. Due to the complex characteristics of the power line communication (PLC) channel, including line impedance changes, electromagnetic interference, load fluctuations and other factors, the interference or noise level in the communication environment is difficult to predict and varies widely. This inconsistency in noise size and the dynamic changes in the environmental background noise make the characteristic current identification in the prior art very prone to missed identification or misidentification. Therefore, how to accurately identify the characteristic current is still a problem that needs to be solved urgently. Summary of the invention

[0004] In view of this, the embodiments of the present application provide a power line characteristic current identification method, device and phase line identification system to solve at least one problem existing in the background technology.

[0005] In a first aspect, an embodiment of the present application provides a method for identifying a characteristic current of a power line, wherein the characteristic current signal is generated according to a characteristic frequency and a characteristic sequence, wherein the characteristic sequence includes an m-bit characteristic code, and the characteristic code is represented by 1 or 0, and the method includes:

[0006] Acquire the current signal in the power line;

[0007] The current signal is divided into continuous time windows based on a preset time window and a preset sliding step to obtain a first time window array; wherein the time width of the preset time window is equal to the time width of the characteristic current signal; and the time width of the preset sliding step is less than the bit width time of the characteristic code;

[0008] Extracting the current signal corresponding to the characteristic frequency from the current signal, dividing the current signal corresponding to the characteristic frequency into a series of continuous time windows based on the preset time window and the preset sliding step, to obtain a second time window array;

[0009] Obtain a first recognition sequence corresponding to each time window according to the first time window array and the feature sequence, and obtain a second recognition sequence corresponding to each time window according to the second time window array and the feature sequence;

[0010] The first identification sequence corresponding to each time window in the first time window array and the second identification sequence corresponding to each time window in the second time window array are compared with the characteristic sequence, and whether a characteristic current signal exists is determined according to the comparison result.

[0011] In a second aspect, an embodiment of the present application provides a power line characteristic current identification device, wherein the characteristic current signal is generated according to a characteristic frequency and a characteristic sequence, wherein the characteristic sequence includes an m-bit characteristic code, and the characteristic code is represented by 1 or 0, and the identification device includes:

[0012] An acquisition unit, used for acquiring a current signal in the power line;

[0013] A first time window array calculation unit, used to divide the current signal into continuous time windows based on a preset time window and a preset sliding step to obtain a first time window array; wherein the time width of the preset time window is equal to the time width of the characteristic current signal; and the time width of the preset sliding step is less than the bit width time of the characteristic code;

[0014] A second time window array calculation unit is used to extract the current signal corresponding to the characteristic frequency from the current signal, and divide the current signal corresponding to the characteristic frequency into a series of continuous time windows based on the preset time window and the preset sliding step size to obtain a second time window array;

[0015] A first recognition sequence calculation unit, configured to obtain a first recognition sequence corresponding to each time window according to the first time window array and the feature sequence;

[0016] A second recognition sequence calculation unit, configured to obtain a second recognition sequence corresponding to each time window according to the second time window array and the feature sequence;

[0017] A judgment unit is used to compare the first recognition sequence corresponding to each time window in the first time window array and the second recognition sequence corresponding to each time window in the second time window array with the characteristic sequence, and judge whether there is a characteristic current signal according to the comparison result.

[0018] In a third aspect, an embodiment of the present application provides a phase line identification system, the phase line identification system comprising the identification device described in the above embodiment, a collection terminal and a plurality of electric energy meters, the plurality of electric energy meters being arranged at each phase line branch in the collection terminal, the identification device being connected to each phase line in the collection terminal through a plurality of current transformers; the electric energy meter comprising an electric energy meter to be identified;

[0019] The acquisition terminal is used to send a phase line identification signal to the electric energy meter to be identified;

[0020] The electric energy meter to be identified is used to respond to the phase line identification signal and send a characteristic current signal;

[0021] The identification device is used to receive the current signal of each phase line, perform characteristic current signal identification on the current signal, and determine the phase line of the electric energy meter to be identified according to the identification result.

[0022] In a fourth aspect, an embodiment of the present application provides a transformer substation topology structure identification system, the system comprising: a plurality of power line characteristic current identification devices as described in the above embodiments, the identification devices being respectively arranged at each power line branch in the transformer substation, the identification devices determining the electric energy meter on each power line branch, and determining the topology structure of the transformer substation according to the electric energy meter on each power line branch.

[0023] In the embodiment of the present application, the current signal and the current signal corresponding to the characteristic frequency are divided based on the preset time window and the preset sliding step size to obtain the first time window array and the second time window array, and then the first identification sequence based on direct current signal identification and the second identification sequence based on characteristic frequency identification are obtained according to the characteristic sequence, and finally the characteristic current signal can be judged by comparing with the characteristic sequence. In the embodiment of the present application, by simultaneously directly identifying the current signal and identifying the characteristic frequency current signal, accurate identification is achieved in different noise or interference environments, which significantly improves the accuracy and robustness of identification.

[0024] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0026] Figure 1 A schematic diagram of a flow chart of a method for identifying characteristic current of a power line provided in an embodiment of the present application;

[0027] Figure 2 This is a schematic diagram of a current signal according to a specific implementation of the present application;

[0028] Figure 3 This is a schematic diagram of a current signal after characteristic frequency extraction according to a specific implementation method of the present application;

[0029] Figure 4 A schematic diagram of a current signal according to another specific embodiment of the present application;

[0030] Figure 5 This is a schematic diagram of a current signal after characteristic frequency extraction according to another specific embodiment of the present application;

[0031] Figure 6 A schematic diagram of a time window array recognition sequence acquisition process according to an embodiment of the present application;

[0032] Figure 7 A schematic diagram of a power line characteristic current identification device provided in an embodiment of the present application;

[0033] Figure 8 A schematic diagram of an identification sequence calculation unit according to an embodiment of the present application;

[0034] Fig. 9 A schematic diagram of an identification sequence calculation unit provided in a specific embodiment of the present application. DETAILED DESCRIPTION

[0035] In order to make the technical solutions and beneficial effects of the present invention more clearly understood, the following is a detailed description by listing specific embodiments. Unless otherwise defined, the technical and scientific terms used herein have the same meanings as those in the technical field to which this application belongs.

[0036] Figure 1 This is a schematic diagram of a method for identifying a characteristic current of a power line provided in an embodiment of the present application. Figure 1 As shown, the method includes:

[0037] S1. Obtain the current signal in the power line.

[0038] Specifically, obtaining the current signal of the power line refers to obtaining the current signals of multiple different power lines, and through the characteristic current identification, it can be determined that the phase line or substation to which the electric energy meter corresponding to the characteristic current signal belongs. In the embodiment of the present application, the characteristic current signal is generated according to the characteristic frequency and the characteristic sequence, wherein the characteristic sequence includes an m-bit characteristic code, and the bit width time of each bit of the characteristic code is t, and the characteristic code is represented by 1 or 0. As an optional specific implementation method, the characteristic current signal is modulated by OOK (On-Off keying). Specifically, the presence or absence of a fixed bit width characteristic current is achieved by OOK modulation to represent the "1" and "0" of the digital signal; the characteristic frequency of the modulated carrier frequency is f1, and the duration of each bit is the set bit width time t. If the bit is 1, the frequency f1 is used for switching during the bit duration; if the bit is 0, no switching is performed. In the embodiment of the present application, the characteristic code is represented by 1 and 0, and the electric energy meter uses OOK modulation to send the characteristic current signal corresponding to the characteristic sequence to the power line. It should be noted that the characteristic current varies according to the load. If the load is a constant resistance load and the internal resistance remains constant, the characteristic current varies with the current amplitude; if the load is a constant current load and the internal resistance varies with the AC amplitude, the characteristic current remains constant. In the embodiment of the present application, the current signal in the power line can be received by a current transformer, thereby eliminating the need for additional wiring.

[0039] S2. Based on a preset time window and a preset sliding step, a time window array is obtained according to the current signal.

[0040] The time width of the preset time window is equal to the time width of the characteristic current signal; and the time width of the preset sliding step is smaller than the time width of the characteristic code bit.

[0041] Specifically, the current signal is divided into continuous time windows based on the preset time window and the preset sliding step to obtain a time window array. For example, the feature sequence has a total of 16 feature codes, and the bit width of each feature code is 0.6s, then the time width of the feature current signal is 16x0.6=9.6s, then the preset time window width is 9.6s, if the sampling frequency of the current signal is 5000Hz, then the number of sampling points in each time window is 48000; the sliding step is 500 sampling points, then the corresponding sliding step time width is 0.1s. As an optional specific implementation, the time width of the preset sliding step is less than the feature code bit width time, so that while achieving real-time recognition of the feature current signal, it can also reduce the missed recognition caused by too large a sliding step. Furthermore, the feature code bit width time is an integer multiple of the time width of the preset sliding step. It should be noted that the continuous time window of the present application refers to the time window divided according to the sliding step, and there is an overlapping part between two adjacent time windows. For example, the time corresponding to the first time window is from t0 to t 16 , then the next time window corresponds to the time from t0+a to t 16 +a, where t0 represents the time when the current signal is acquired, a represents the time width of the sliding step, and the time width of the time window is equal to t 16 and t0.

[0042] As an optional specific implementation, a time window array is obtained according to the current signal, including: extracting and processing the current signal according to a preset extraction interval to obtain the extracted current signal; correspondingly, dividing the extracted current signal into continuous time windows based on the preset time window and the preset sliding step to obtain a time window array. In the embodiment of the present application, the current signal is extracted and processed by the preset extraction interval, so as to reduce the amount of data processing and speed up the processing. For example, if the preset extraction interval is 500 sampling points, the time between two sampling points after the extraction process is 0.1s, then the number of sampling points in each bit width time is 6 points, and the number of sampling points in each time window is 96 points, thereby greatly reducing the amount of subsequent data processing. Furthermore, the feature code bit width time is an integer multiple of the time width of the preset sliding step.

[0043] As an optional specific implementation, based on a preset time window and a preset sliding step, a time window array is obtained according to the current signal, including:

[0044] The current signal corresponding to the characteristic frequency in the current signal is extracted, and the current signal corresponding to the characteristic frequency is divided into continuous time windows based on a preset time window and a preset sliding step size to obtain a time window array.

[0045] In the embodiment of the present application, by extracting the current signal corresponding to the characteristic frequency in the characteristic current signal, the interference and noise in the current signal can be effectively removed, and the accuracy and reliability of identification can be improved. It should be noted that the interference here includes power line power frequency current signal interference, harmonic interference, etc. The power frequency current signal is the current that flows continuously in the current line, and its frequency is usually fixed. The strength of the power frequency current signal will vary according to the connected load or operating conditions. The frequency of the characteristic current signal is usually much higher than the power frequency current signal to ensure that it can be effectively transmitted on the power line. After the characteristic current signal is sent on the power line, the characteristic current signal will be superimposed with the power frequency current signal, but because the frequencies of the two are different, they can be separated. For example, the characteristic frequency of the characteristic frequency signal is 833.3Hz, then after the characteristic current signal of 833.3Hz is superimposed with the power frequency current signal of 50Hz, the effective frequency domain peaks of the characteristic current signal are 783.3Hz and 883.3Hz, therefore, it can be identified by extracting the current signal corresponding to the characteristic frequency, thereby improving the accuracy of identification. In the embodiment of the present application, it can be extracted by Fourier transform or multi-order filtering, etc., and the present application is not limited.

[0046] As an optional specific implementation, based on a preset time window and a preset sliding step, a time window array is obtained according to the current signal, including:

[0047] The current signal is divided into continuous time windows based on a preset time window and a preset sliding step to obtain a first time window array; the current signal corresponding to the characteristic frequency is extracted from the current signal, and the current signal corresponding to the characteristic frequency is divided into a series of continuous time windows based on the preset time window and the preset sliding step to obtain a second time window array.

[0048] In the embodiment of the present application, the first time window array includes all frequency signals in the power line without separating the frequencies; the second time window array contains current signals corresponding to the characteristic frequencies; by subsequently simultaneously identifying the characteristic current signals in each time window in the first time window array and the second time window array, the accuracy and reliability of the identification can be improved, and the dual identification mechanism ensures that the characteristic current signals can be accurately and effectively identified in different environments.

[0049] For example, the characteristic sequence corresponding to the characteristic current signal is 1010101011101001. Figure 2This is a schematic diagram of a current signal of a specific implementation method of the present application. In the figure, the characteristic current signal is subject to less interference or noise. At this time, the strength of the characteristic current signal will directly affect the waveform of the current signal in the power signal. In the T1-T2 time window, the characteristic current signal is directly identified by envelope detection or threshold judgment. The identification code of the time period where a convex position is formed in the corresponding current signal is 1, and the identification code of the time period where no convex position is formed is 0. The obtained identification sequence is 1010101011101001, and the identification sequence corresponds to the characteristic sequence one by one, so that the characteristic current signal is accurately identified. Figure 3 This is a schematic diagram of a current signal after characteristic frequency extraction according to a specific implementation of the present application. Specifically, Figure 3 for Figure 2 The current signal in is sampled at preset intervals (interval is 500 points) and the current signal waveform after characteristic frequency extraction. It can be seen from the figure that after characteristic frequency extraction, some characteristic peaks of the waveform in the T1-T2 time window are not obvious, but difficult to identify, and easy to misjudge and misidentify. Figure 4 This is a schematic diagram of a current signal of another specific implementation of the present application. In the figure, the characteristic current signal is subject to greater interference or noise. At this time, the strength of the characteristic current signal does not directly affect the waveform of the current signal in the power signal. Direct identification at this time is prone to misjudgment. Figure 5 This is a schematic diagram of a current signal after characteristic frequency extraction according to another specific implementation of the present application. Specifically, Figure 5 for Figure 4 The current signal in is sampled at preset intervals (interval is 1000 points) and the current signal waveform after characteristic frequency extraction. It can be seen from the figure that after characteristic frequency extraction, the peaks and troughs of the waveform are obvious in the T1'-T2' time window, so that an accurate identification code can be obtained by threshold judgment in the subsequent process. Correspondingly, the identification sequence is 1010101011101001. The identification sequence corresponds to the characteristic sequence one by one, so that the characteristic current signal is accurately identified.

[0050] In the embodiment of the present application, a first time window array and a second time window array are obtained based on the processing of the current signal, and the current signal and the current signal corresponding to the characteristic frequency are simultaneously identified, so that the characteristic current signal can be accurately identified even in different interference or noise environments, thereby improving the accuracy and reliability of identification.

[0051] S3. Obtain the recognition sequence corresponding to each time window according to the time window array and the feature sequence.

[0052] Specifically, Figure 6 This is a schematic diagram of the time window array recognition sequence acquisition process of an embodiment of the present application. Figure 6As shown, step S3 includes:

[0053] S31, dividing each time window in the time window array into equal intervals according to a preset time length.

[0054] Each time window is divided into m time periods; the preset time length is equal to the bit width time of each bit of the feature code, and the m time periods correspond to the m-bit feature codes one by one.

[0055] S32. Calculate the recognition threshold corresponding to each time window according to the intensity values ​​and characteristic sequences of the current signals in the m time periods corresponding to each time window.

[0056] Specifically, the recognition threshold is calculated by the following formula:

[0057]

[0058] Among them, sum i (1) represents the intensity value of the current signal in the i-th time period whose corresponding feature code is 1 among the m time periods, sum i (0) represents the intensity value of the current signal of the i-th time period corresponding to the feature code 0 in the m time periods, m1 represents the number of feature codes 1 in the feature sequence, and m0 represents the number of feature codes 0 in the feature sequence. It should be noted that the intensity value of the current signal in each time period may be the intensity peak value, intensity average value or total intensity value of the current signal in the time period.

[0059] In the embodiment of the present application, the recognition threshold is not a fixed threshold, but is adaptively and dynamically adjusted based on the strength value of the current signal in the m time periods in each time window, and the correspondence between the m time periods and the characteristic code. The recognition threshold of each time window in the embodiment of the present application takes into account the current signal strength of the characteristic signal when the characteristic code is 1 and the level of noise or interference signal strength when the characteristic code is 0, so that the corresponding identification code can be accurately obtained in each time period. The recognition threshold of the embodiment of the present application is more accurate, because the signal strength of interference and noise is taken into account. Therefore, even if the interference or noise level in the communication environment is difficult to predict, the embodiment of the present application can also obtain an accurate recognition threshold for determining the identification code.

[0060] As an optional specific implementation, S32 includes:

[0061] Calculate the recognition threshold corresponding to each time window according to the intensity average value and characteristic sequence of the current signal in each time period of the m time periods corresponding to each time window;

[0062] Correspondingly, sum i(1) represents the average value of the intensity of the current signal in the i-th time period whose corresponding feature code is 1 among the m time periods, sum i (0) represents the average value of the intensity of the current signal in the i-th time period corresponding to the characteristic code 0 in the m time periods. It should be noted that the total intensity value of the current signal refers to the average value of the current intensity values ​​of the sampling points in the time period.

[0063] As an optional specific implementation, S32 includes:

[0064] Calculate the recognition threshold corresponding to each time window according to the total intensity value and characteristic sequence of the current signal in each time period of the m time periods corresponding to each time window;

[0065] Correspondingly, sum i (1) represents the total intensity value of the current signal in the i-th time period whose corresponding feature code is 1 among the m time periods, sum i (0) represents the total intensity value of the current signal in the i-th time period corresponding to the characteristic code 0 in the m time periods. It should be noted that the total intensity value of the current signal refers to the sum of the current intensity values ​​of the sampling points in the time period.

[0066] In an embodiment of the present application, an identification threshold is obtained by using the intensity mean or total intensity value of each time period. Correspondingly, an identification code for the time period is subsequently obtained by using the identification threshold corresponding to the intensity mean or total intensity value. Compared with using the peak value in each time period to determine the identification code, the embodiment of the present application uses the intensity mean or total intensity value in a more accurate manner, and can prevent the problem of incorrect or inaccurate identification code caused by abnormal peak points or multiple peaks, thereby improving the accuracy and reliability of the identification code.

[0067] S33, judging the magnitude of the intensity value of the current signal in each time period corresponding to each time window and the corresponding recognition threshold, and obtaining the recognition sequence of each time window.

[0068] Specifically, S33 includes:

[0069] If the intensity value of the current signal in a certain time period is greater than the corresponding identification threshold, the identification code of the time period is 1; if the intensity value of the current signal in a certain time period is less than the corresponding identification threshold, the identification code of the time period is 0;

[0070] Each time window obtains an identification sequence according to the identification codes of the corresponding m time periods.

[0071] Specifically, if sum i (1) is greater than the recognition threshold, then the feature code of the i-th time period whose corresponding feature code is 1 among the m time periods is 1; if sum i(1) is less than the recognition threshold, then the feature code of the i-th time period whose corresponding feature code is 1 among the m time periods is 0; if sum i (0) is greater than the recognition threshold, then the feature code of the i-th time period whose corresponding feature code is 0 among the m time periods is 1; if sum i (0) is less than the recognition threshold, then the feature code of the i-th time period whose corresponding feature code is 0 among the m time periods is 0.

[0072] In the embodiments of the present application, the recognition threshold of each time window is dynamically adjusted according to the current signal strength in the time window and the relationship corresponding to the characteristic sequence. Through the adaptive dynamic adjustment mechanism of the recognition threshold, it is possible to dynamically adjust the noise or interference environment of each time window, ensuring that even under complex and changeable noise and interference conditions, it is still possible to accurately judge and generate the identification code of each time period, thereby obtaining a reliable and accurate recognition sequence, improving the accuracy of the recognition sequence, and reducing the possibility of misjudgment. Compared with the traditional fixed threshold method, the recognition threshold of the embodiment of the present application can be adjusted in real time according to the change of interference or noise, and can be applied to various complex and changeable environments, greatly improving the accuracy and reliability of the recognition sequence, thereby laying the foundation for the subsequent accurate recognition and judgment of characteristic current signals.

[0073] As an optional specific implementation, a first identification sequence corresponding to each time window is obtained according to the first time window array and the characteristic sequence; a second identification sequence corresponding to each time window is obtained according to the second time window array and the characteristic sequence. It should be noted that the time windows in the first time window array and the second time window array are one-to-one corresponding, but their current signal data will have different results due to different processing. In the embodiment of the present application, each time window has a corresponding first identification sequence and a second identification sequence, so that the advantages of the two different processing methods can be combined, and the characteristic current signal can be accurately identified in different interference or noise environments.

[0074] S4. Compare the recognition sequence of each time window with the characteristic sequence, and determine whether there is a characteristic current signal based on the comparison result.

[0075] Specifically, if the recognition sequence is the same as the characteristic sequence, it is determined that the characteristic current signal is recognized, otherwise it is determined that the characteristic current signal is not recognized. Through the one-to-one correspondence between the recognition sequence and the characteristic sequence, it is possible to accurately determine whether the characteristic current signal is recognized.

[0076] In the embodiment of the present application, the recognition threshold of each time window is adaptively and dynamically adjusted, so that an accurate identification code corresponding to each time period can be obtained, and then the recognition sequence corresponding to each time window can be obtained. The recognition sequence of the embodiment of the present application is simple and convenient, and can be accurately obtained even in the case of variable noise or interference. Compared with the existing fixed threshold method, the recognition threshold of the embodiment of the present application takes into account the situation of noise interference and the size of the characteristic signal strength, and then the recognition sequence obtained by the recognition threshold is more accurate, so that it can accurately determine whether there is a characteristic current.

[0077] As an optional specific implementation, S4 includes:

[0078] The first identification sequence corresponding to each time window in the first time window array and the second identification sequence corresponding to each time window in the second time window array are compared with the characteristic sequence, and whether a characteristic current signal exists is determined according to the comparison result.

[0079] Specifically, if the first recognition sequence and / or the second recognition sequence is the same as the characteristic sequence, it is determined that the characteristic current signal is recognized; otherwise, it is determined that the characteristic current signal is not recognized.

[0080] In the embodiment of the present application, by combining the two methods of direct current signal recognition and characteristic frequency current signal recognition, by comparing the first recognition sequence (based on direct current signal recognition) and the second recognition sequence (based on characteristic frequency recognition) with the characteristic sequence, if any recognition sequence is the same as the characteristic sequence, it is determined that the characteristic current signal is recognized, thereby achieving accurate recognition in different noise and interference environments, significantly improving the accuracy and robustness of recognition.

[0081] It should be understood that although Figure 1 and Figure 6 The steps in the flowchart are not necessarily executed sequentially. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 1 and Figure 6 At least part of the steps may include multiple steps or multiple stages. These steps or stages are not necessarily performed at the same time, but can be performed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed in turn or alternately with other steps or at least part of the steps or stages in other steps.

[0082] Figure 7 This is a schematic diagram of a power line characteristic current identification device provided in an embodiment of the present application. Figure 7 As shown, the device comprises:

[0083] The acquisition unit 100 is used to acquire a current signal in a power line.

[0084] The time window array calculation unit 200 is used to obtain a time window array according to the current signal based on a preset time window and a preset sliding step.

[0085] As an optional specific implementation, a time window array is obtained according to a current signal, including: extracting and processing the current signal according to a preset extraction interval to obtain the extracted current signal; correspondingly, dividing the extracted current signal into continuous time windows based on a preset time window and a preset sliding step to obtain a time window array.

[0086] As an optional specific implementation, based on a preset time window and a preset sliding step, a time window array is obtained according to the current signal, including:

[0087] The current signal corresponding to the characteristic frequency in the current signal is extracted, and the current signal corresponding to the characteristic frequency is divided into continuous time windows based on a preset time window and a preset sliding step size to obtain a time window array.

[0088] The recognition sequence calculation unit 300 is used to obtain the recognition sequence corresponding to each time window according to the time window array and the feature sequence.

[0089] Specifically, Figure 8 FIG. 1 is a schematic diagram of an identification sequence calculation unit according to an embodiment of the present application. Figure 8 As shown, the recognition sequence calculation unit 300 includes:

[0090] The division module 301 is used to divide each time window in the time window array into equal intervals according to a preset time length.

[0091] The recognition threshold calculation module 302 is used to calculate the recognition threshold corresponding to each time window according to the intensity values ​​and characteristic sequences of the current signal in the m time periods corresponding to each time window.

[0092] Specifically, the recognition threshold is calculated by the following formula:

[0093]

[0094] Among them, sum i (1) represents the intensity value of the current signal in the i-th time period whose corresponding feature code is 1 among the m time periods, sum i (0) represents the intensity value of the current signal in the i-th time period corresponding to the feature code 0 in the m time periods, m1 represents the number of feature codes 1 in the feature sequence, and m0 represents the number of feature codes 0 in the feature sequence.

[0095] The identification code determination module 303 is used to determine the magnitude between the intensity value of the current signal in each time period corresponding to each time window and the corresponding identification threshold value, so as to obtain the identification sequence of each time window.

[0096] Specifically, the recognition sequence of each time window is obtained, including:

[0097] If the intensity value of the current signal in a certain time period is greater than the corresponding identification threshold, the identification code of the time period is 1; if the intensity value of the current signal in a certain time period is less than the corresponding identification threshold, the identification code of the time period is 0;

[0098] Each time window obtains an identification sequence according to the identification codes of the corresponding m time periods.

[0099] Specifically, if sum i (1) is greater than the recognition threshold, then the feature code of the i-th time period whose corresponding feature code is 1 among the m time periods is 1; if sum i (1) is less than the recognition threshold, then the feature code of the i-th time period whose corresponding feature code is 1 among the m time periods is 0; if sum i (0) is greater than the recognition threshold, then the feature code of the i-th time period whose corresponding feature code is 0 among the m time periods is 1; if sum i (0) is less than the recognition threshold, then the feature code of the i-th time period whose corresponding feature code is 0 among the m time periods is 0.

[0100] The judgment unit 400 is used to compare the recognition sequence of each time window with the characteristic sequence, and judge whether there is a characteristic current signal according to the comparison result.

[0101] Specifically, judging whether a characteristic current signal exists according to the comparison result includes:

[0102] If the recognition sequence is the same as the characteristic sequence, it is determined that the characteristic current signal is recognized, otherwise it is determined that the characteristic current signal is not recognized. Through the one-to-one correspondence between the recognition sequence and the characteristic sequence, it is possible to accurately determine whether the characteristic current signal is recognized.

[0103] Fig. 9 A schematic diagram of a recognition sequence calculation unit provided in a specific embodiment of the present application. Fig. 9 As shown, the time window array calculation unit 200 includes:

[0104] The first time window array calculation unit 210 is used to divide the current signal into continuous time windows based on a preset time window and a preset sliding step size to obtain a first time window array.

[0105] The second time window array calculation unit 220 is used to extract the current signal corresponding to the characteristic frequency from the current signal, divide the current signal corresponding to the characteristic frequency into a series of continuous time windows based on a preset time window and a preset sliding step, and obtain a second time window array.

[0106] Correspondingly, the recognition sequence calculation unit 300 includes:

[0107] A first recognition sequence calculation unit 310, configured to obtain a first recognition sequence corresponding to each time window according to the first time window array and the feature sequence;

[0108] The second recognition sequence calculation unit 320 is used to obtain a second recognition sequence corresponding to each time window according to the second time window array and the feature sequence.

[0109] Correspondingly, the judgment unit 400 compares the first recognition sequence corresponding to each time window in the first time window array and the second recognition sequence corresponding to each time window in the second time window array with the characteristic sequence, and determines whether there is a characteristic current signal according to the comparison result.

[0110] Specifically, judging whether a characteristic current signal exists according to the comparison result includes:

[0111] Specifically, if the first recognition sequence and / or the second recognition sequence is the same as the characteristic sequence, it is determined that the characteristic current signal is recognized; otherwise, it is determined that the characteristic current signal is not recognized.

[0112] The embodiment of the present application also provides a phase line identification system, which includes the identification device of the above embodiment, a collection terminal and multiple electric energy meters, the multiple electric energy meters are arranged at each phase line branch in the collection terminal, the identification device is connected to each phase line in the collection terminal through multiple current transformers; the electric energy meter includes an electric energy meter to be identified;

[0113] The acquisition terminal is used to send a phase line identification signal to the electric energy meter to be identified;

[0114] The electric energy meter to be identified is used to respond to the phase line identification signal and send a characteristic current signal;

[0115] The identification device is used to receive the current signal of each phase line, perform characteristic current signal identification on the current signal, and determine the phase line of the electric energy meter to be identified according to the identification result.

[0116] An embodiment of the present application also provides a transformer substation topology structure identification system, the system comprising: multiple identification devices of the above embodiments, the identification devices are respectively arranged at each power line branch in the transformer substation, the identification device determines the electric energy meter on each power line branch, and determines the topology structure of the transformer substation according to the electric energy meter on each power line branch.

[0117] It should be understood that the above embodiments are exemplary and are not intended to include all possible implementations included in the claims. Various modifications and changes may be made on the basis of the above embodiments without departing from the scope of the present disclosure. Similarly, the various technical features of the above embodiments may be arbitrarily combined to form other embodiments of the present invention that may not be explicitly described. Therefore, the above embodiments only express several implementations of the present invention and do not limit the scope of protection of the patent of the present invention.

Claims

1. A characteristic current signal recognition method, characterized in that: The characteristic current signal is generated according to the characteristic frequency and the characteristic sequence, and the method includes: Acquire the current signal in the power line; Based on a preset time window and a preset sliding step, obtaining a time window array according to the current signal; Obtaining an identification sequence corresponding to each time window according to the time window array and the feature sequence; Comparing the recognition sequence of each time window with the characteristic sequence, and judging whether there is a characteristic current signal according to the comparison result; Wherein, obtaining the recognition sequence corresponding to each time window according to the time window array and the feature sequence includes: Dividing each time window in the time window array into equal intervals according to a preset time length; Calculate the recognition threshold corresponding to each time window according to the intensity values ​​of the current signal in the m time periods corresponding to each time window and the characteristic sequence; The magnitude of the intensity value of the current signal in each time period corresponding to each time window and the corresponding recognition threshold are determined to obtain the recognition sequence of each time window.

2. The characteristic current signal identification method according to claim 1, characterized in that: According to the intensity values ​​of the current signals in the m time periods corresponding to each time window and the characteristic sequence, the recognition threshold corresponding to each time window is calculated, specifically: Among them, sum i (1) represents the intensity value of the current signal in the i-th time period whose corresponding feature code is 1 among the m time periods, sum i (0) represents the intensity value of the current signal in the i-th time period corresponding to the feature code 0 in the m time periods, m1 represents the number of feature codes 1 in the feature sequence, and m0 represents the number of feature codes 0 in the feature sequence.

3. The characteristic current signal recognition method according to claim 2, characterized in that: Determine the magnitude of the intensity value of the current signal in each time period corresponding to each time window and the corresponding recognition threshold value, and obtain the recognition sequence of each time window, including: If the intensity value of the current signal in a certain time period is greater than the corresponding identification threshold, the identification code of the time period is 1; if the intensity value of the current signal in a certain time period is less than the corresponding identification threshold, the identification code of the time period is 0; Each time window obtains an identification sequence according to the identification codes of the corresponding m time periods.

4. The characteristic current signal identification method according to claim 3, characterized in that: According to the current signals of the m time periods corresponding to each time window and the characteristic sequence, the recognition threshold corresponding to each time window is calculated, specifically: Calculate the recognition threshold corresponding to each time window according to the average value of the intensity of the current signal in each time period of the m time periods corresponding to each time window and the characteristic sequence; Correspondingly, sum i (1) represents the average value of the intensity of the current signal in the i-th time period whose corresponding feature code is 1 among the m time periods, sum i (0) represents the average value of the intensity of the current signal in the i-th time period whose corresponding characteristic code is 0 among the m time periods.

5. The characteristic current signal identification method according to claim 3, characterized in that: According to the current signals of the m time periods corresponding to each time window and the characteristic sequence, the recognition threshold corresponding to each time window is calculated, specifically: Calculate the recognition threshold corresponding to each time window according to the total intensity value of the current signal in each time period of the m time periods corresponding to each time window and the characteristic sequence; Correspondingly, sum i (1) represents the total intensity value of the current signal in the i-th time period whose corresponding feature code is 1 among the m time periods, sum i (0) represents the total intensity value of the current signal of the i-th time period whose corresponding characteristic code is 0 among the m time periods.

6. The characteristic current signal identification method according to claim 1, characterized in that: Comparing the identification sequence of each time window with the characteristic sequence, and judging whether a characteristic current signal exists according to the comparison result, including: If the recognition sequence is the same as the characteristic sequence, it is determined that the characteristic current signal is recognized, otherwise it is determined that the characteristic current signal is not recognized.

7. The characteristic current signal identification method according to claim 1, characterized in that: Based on the preset time window and the preset sliding step, a time window array is obtained according to the current signal, including: A current signal corresponding to a characteristic frequency in the current signal is extracted, and the current signal corresponding to the characteristic frequency is divided into continuous time windows based on a preset time window and a preset sliding step size to obtain a time window array.

8. A characteristic current signal identification device, characterized in that: The characteristic current signal is generated according to the characteristic frequency and the characteristic sequence, wherein the characteristic sequence includes an m-bit characteristic code, and the characteristic code is represented by 1 or 0. The identification device includes: An acquisition unit, used for acquiring a current signal in the power line; A time window array calculation unit, used to obtain a time window array according to the current signal based on a preset time window and a preset sliding step; wherein the time width of the preset time window is equal to the time width of the characteristic current signal; and the time width of the preset sliding step is less than the bit width time of the characteristic code; An identification sequence calculation unit, used for obtaining an identification sequence corresponding to each time window according to the time window array and the feature sequence; The judging unit is used to compare the recognition sequence of each time window with the characteristic sequence, and judge whether there is a characteristic current signal according to the comparison result.

9. A phase line identification system, characterized in that: The phase line identification system comprises the identification device as claimed in claim 8, a collection terminal and a plurality of electric energy meters, wherein the plurality of electric energy meters are arranged at each phase line branch in the collection terminal, and the identification device is respectively connected to each phase line in the collection terminal through a plurality of current transformers; the electric energy meters include electric energy meters to be identified; The acquisition terminal is used to send a phase line identification signal to the electric energy meter to be identified; The electric energy meter to be identified is used to respond to the phase line identification signal and send a characteristic current signal; The identification device is used to receive the current signal of each phase line, perform characteristic current signal identification on the current signal, and determine the phase line of the electric energy meter to be identified according to the identification result.

10. A transformer area topology structure identification system, characterized in that: The system includes: a plurality of characteristic current signal identification devices as described in claim 8, wherein the identification devices are respectively arranged at each power line branch in the transformer substation, the identification devices determine the electric energy meter on each power line branch, and determine the topological structure of the transformer substation according to the electric energy meter on each power line branch.

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