A distribution box capable of automatically sensing line faults and a method for automatically sensing line faults

Abstract

The present invention relates to the field of line fault detection technology, and specifically to a distribution box for automatic line fault sensing and a method for automatic line fault sensing. The method performs short-time Fourier transform on the voltage and current data of the distribution box to obtain the phase and frequency in the short-time interval; combines the high-frequency characteristics of intermittent short circuits and the deviations from historical short-time intervals to obtain intermittent short circuit characteristic indicators; obtains the retained indicator to optimize the voltage signal decomposition process according to the intermittent short circuit characteristic indicators and the current and voltage phase deviations and trend changes of each data point in each short-time interval, and obtains the signal component from the envelope and energy anomaly to evaluate the intermittent short circuit fault results. The present invention introduces short-time Fourier transform to analyze historical data in the instantaneous range, and optimizes the signal decomposition degree in combination with the phase and voltage change trend anomalies, so that the intermittent short circuit feature retention degree is higher, the perception ability of intermittent short circuit line faults is improved, and the accuracy of fault detection is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of line fault detection, and in particular to a distribution box capable of automatically sensing line faults and a method for automatically sensing line faults. Background Art

[0002] The composition of modern power systems is becoming increasingly complex, including a diversified power structure such as distributed generation and renewable energy access. This has increased the types and probability of line failures to a certain extent. Line failures not only cause local power outages, but may also cause large-scale power outages, affecting normal power supply operations. Especially in critical infrastructure, a reliable supply of electricity is crucial, and rapid detection and response can significantly reduce the impact of line failures.

[0003] With the continuous development and application of intelligent sensing technology, power line fault detection and diagnosis methods mainly rely on technologies such as the Internet of Things, big data analysis, and artificial intelligence, which can realize intelligent perception, automatic detection, and accurate diagnosis of power line faults, thereby improving the safety, reliability, and economy of the power system.

[0004] However, when the fault in the circuit is an unstable intermittent short circuit, since the intermittent fault is manifested as an unstable state and intermittent circuit fault. This fault lasts for a short time in the circuit and then returns to normal, but it will occur again after a while. The short circuit caused by the fault will produce instantaneous peaks of overvoltage and current, causing certain damage to the equipment and may gradually develop into a permanent short circuit. The instantaneous change of this intermittent short circuit is very easy to be confused with the instantaneous change generated when the electrical equipment is enabled, resulting in inaccurate fault detection and more serious losses in the distribution box. Summary of the invention

[0005] In order to solve the technical problem in the prior art that the instantaneous change of intermittent short circuit is easily confused with the instantaneous change generated when the electrical equipment is enabled, resulting in inaccurate fault detection, the purpose of the present invention is to provide a distribution box for automatic line fault sensing and a method for automatic line fault sensing. The technical solution adopted is as follows:

[0006] The present invention provides a method for automatically sensing line faults, the method comprising:

[0007] Obtain the voltage signal segment of the distribution box in the same period of each cycle in the historical period; the voltage signal segment includes the current voltage segment and the historical voltage segment; obtain the current signal segment corresponding to the current voltage segment; after short-time Fourier transform of all voltage signal segments and current signal segments, obtain the phase, frequency and amplitude of each frequency component of each voltage signal segment and current signal segment in different short-time intervals;

[0008] According to the high frequency degree of each frequency component in each short-time interval in the current voltage segment, the similarity of the frequency component distribution between historical voltage segments, and the amplitude deviation and time deviation of the frequency component between the current voltage segment and each historical voltage segment, the intermittent short circuit characteristic index of each short-time interval in the current voltage segment is obtained;

[0009] According to the phase deviation between the frequency components of the current signal segment and the current voltage segment, and the degree of signal change trend of each data point in the current voltage segment, combined with the intermittent short circuit characteristic index of the short time interval where each data point is located, the retention index of each data point in the current voltage segment is obtained;

[0010] Iterative signal decomposition is performed based on the retention index of each data point in the current voltage segment to obtain signal components; intermittent short circuit evaluation indicators of each signal component are obtained according to the envelope change characteristics of each signal component and the chaotic energy distribution of the signal component in different short time intervals;

[0011] The fault perception result is obtained based on all intermittent short circuit evaluation indicators of the current voltage segment.

[0012] Furthermore, the method for obtaining the intermittent short circuit characteristic index includes:

[0013] For any short-time interval in the current voltage segment, the amplitude of each frequency component in the short-time interval is normalized, and the frequency of the frequency component in the short-time interval is weighted and averaged based on the amplitude weight as the amplitude weight of each frequency component to obtain the high-frequency proportion index of the short-time interval;

[0014] According to the closeness of the amplitude between the frequency components in the short time interval and each short time interval in each historical voltage segment, the component similarity between the short time interval and each short time interval in each historical voltage segment is obtained;

[0015] The short-time interval with the greatest component similarity to each historical voltage segment is used as the target interval of the short-time interval in each historical voltage segment;

[0016] According to the time distribution disorder degree of the short time interval and the target interval of all historical voltage segments, the time series distribution characteristic index of the short time interval is obtained;

[0017] According to the time deviation and component similarity between the short time interval and each target interval, the historical feature weight of the short time interval is obtained;

[0018] The intermittent short circuit characteristic index of the short time interval is obtained by combining the high frequency proportion index, time series distribution characteristic index and historical characteristic weight of the short time interval.

[0019] Furthermore, the method for obtaining the component similarity includes:

[0020] For any historical voltage segment, each short-time interval in the historical voltage segment is taken as the analysis interval in turn;

[0021] Normalize the frequency of each frequency component in the analysis interval to obtain the frequency weight of each frequency component;

[0022] Negative correlation mapping is performed between the amplitude difference of the short time interval and the analysis interval between each frequency component to obtain the amplitude approximation of each frequency component;

[0023] The amplitude approximation is weighted based on the frequency weight of the frequency component and the sum is calculated to obtain the component similarity between the short-time interval and the analysis interval.

[0024] Furthermore, the method for obtaining the time series distribution characteristic index includes:

[0025] Sort all short-time intervals in each historical voltage segment in time sequence to obtain an interval sequence for each historical voltage segment;

[0026] The serial number of each target interval in the interval sequence of the historical voltage segment is used as the distribution serial number of each target interval; the variance of the distribution serial numbers of all target intervals corresponding to the short-time interval is used as the time series distribution characteristic indicator of the short-time interval.

[0027] Furthermore, the method for obtaining the historical feature weights includes:

[0028] Negative correlation mapping is performed between the time difference between the short time interval and each target interval at the start time to obtain the time difference weight between the short time interval and each target interval;

[0029] The component similarities between the short time interval and the target interval are weighted based on the time difference weight and the sum is calculated to obtain the historical feature weight of the short time interval.

[0030] Furthermore, the method for obtaining the retention index includes:

[0031] For any short-time interval in the current voltage segment, the short-time interval corresponding to the short-time interval in the current signal segment is used as the current short-time interval of the short-time interval;

[0032] Calculate the phase difference between the short-time interval and the current short-time interval at each frequency component, and calculate the sum of all phase differences to obtain the current phase difference value of the short-time interval;

[0033] In the current voltage segment, the average of the current phase difference between the short time interval and each adjacent short time interval is calculated to obtain the phase difference change index of the short time interval;

[0034] The first-order derivative at each data point in the current voltage segment is normalized as the change value of each data point; the product of the absolute value of the voltage of each data point in the current voltage segment and the change value is used as the abnormal retention degree of each data point in the current voltage segment;

[0035] The retention index of each data point in the current voltage segment is obtained by combining the abnormal retention degree of each data point in the current voltage segment, as well as the phase change index and current phase difference value of the short-time interval corresponding to the data point.

[0036] Furthermore, the iterative signal decomposition based on the retention index of each data point in the current voltage segment to obtain the signal components includes:

[0037] The retention index of each data point in the current voltage segment is used as a weight, and the value of each data point in the current voltage segment is weighted to obtain the current modulation signal; the current modulation signal is decomposed by an iterative envelope estimation function to obtain signal components.

[0038] Furthermore, the method for obtaining the intermittent short circuit evaluation index includes:

[0039] For any signal component, the signal energy value of the signal component in each short time interval is obtained; the variance of the signal energy values ​​of the signal component in all short time intervals is used as the energy anomaly indicator of the signal component;

[0040] Obtain the envelope of the signal component, the envelope including an upper envelope and a lower envelope; calculate the information entropy of the derivative of each data point on each envelope as the variation complexity of each envelope; take the mean of the variation complexity of the envelope of the signal component as the envelope anomaly indicator of the signal component;

[0041] The product of the energy abnormality index and the envelope abnormality index of the signal component is used as the intermittent short circuit evaluation index of the signal component.

[0042] Furthermore, the fault perception result is obtained based on all intermittent short circuit evaluation indicators of the current voltage segment, including:

[0043] When the normalized value of the intermittent short circuit evaluation index of the signal component is greater than the preset fault threshold, the fault perception result at the current moment is recorded as the existence of an intermittent short circuit fault.

[0044] The present invention also provides a distribution box with automatic line fault sensing, comprising a distribution box body and a sensing unit, wherein the sensing unit comprises a data acquisition module, a data processing module, a data analysis module and a communication module;

[0045] The signal output end of the data acquisition module is connected to the signal input end of the data processing module, the signal output end of the data processing module is connected to the signal input end of the data analysis module, and the output end of the data analysis module is connected to the signal input end of the communication module; the communication module is used to display the fault perception result;

[0046] The data acquisition module is used to collect current signals and voltage signals through current sensors and voltage sensors, and transmit all collected data to the data processing module, including the current voltage segment and the historical voltage segment in the same period of each cycle in the historical period, as well as the current signal segment corresponding to the current voltage segment;

[0047] The data processing module is used to obtain the phase, frequency and amplitude of each frequency component of each voltage signal segment and current signal segment in different short time intervals after short-time Fourier transformation of all voltage signal segments and current signal segments, and transmit all data to the data analysis module;

[0048] The data analysis module obtains the intermittent short circuit characteristic index of each short time interval in the current voltage segment according to the high frequency degree of each frequency component in each short time interval in the current voltage segment, the similarity of the frequency component distribution between the historical voltage segments, and the amplitude deviation and time deviation of the frequency component between the current voltage segment and each historical voltage segment;

[0049] According to the phase deviation between the frequency components of the current signal segment and the current voltage segment, and the degree of signal change trend of each data point in the current voltage segment, combined with the intermittent short circuit characteristic index of the short time interval where each data point is located, the retention index of each data point in the current voltage segment is obtained;

[0050] Iterative signal decomposition is performed based on the retention index of each data point in the current voltage segment to obtain signal components. According to the envelope change characteristics of each signal component and the chaotic energy distribution of the signal component in different short time intervals, the intermittent short circuit evaluation index of each signal component is obtained.

[0051] The fault perception results are obtained based on all intermittent short circuit evaluation indicators of the current voltage segment, and the fault perception results are transmitted and displayed through the communication module.

[0052] The present invention has the following beneficial effects:

[0053] After obtaining the voltage and current data of the distribution box, the present invention performs a short-time Fourier transform on the voltage and current data to obtain the phase and frequency of the power signal data in the short time interval, and improves the analysis accuracy of the instantaneous change by introducing the short-time Fourier transform. The intermittent short circuit characteristic index of the line voltage signal data under the current situation can be analyzed in combination with the high-frequency characteristics of the intermittent short circuit and the deviation from the historical short time interval, and the distribution characteristics of the frequency in the local instantaneous detail range of the signal and the historical distinction can be used to reflect the probability of the existence of the intermittent short circuit. Further, from the phase difference change of the current and voltage and the voltage change trend of the intermittent short circuit in the short time interval, the abnormal possibility of the data point in the signal is analyzed, and the intermittent short circuit characteristic index and the current and voltage phase deviation and trend change of each data point in each short time interval are combined to evaluate the degree of retention of each sampled data point in the subsequent signal decomposition process, and the voltage signal decomposition process is optimized by the retention index of the data point, and the signal component is obtained from the envelope and energy anomaly to evaluate the intermittent short circuit fault result. The present invention introduces short-time Fourier transform analysis to distinguish the distribution of historical data in the instantaneous range, and optimizes the degree of signal decomposition in combination with the abnormal phase and voltage change trend, so that the intermittent short circuit characteristics are more retained, the perception ability of intermittent short circuit line faults is enhanced, and the accuracy of fault detection is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0055] Figure 1 A distribution box for automatic line fault sensing and a method for automatic line fault sensing provided by an embodiment of the present invention;

[0056] Figure 2 A schematic diagram of a power distribution box housing with automatic line fault sensing provided by an embodiment of the present invention;

[0057] Figure 3 A schematic diagram of the internal partial structure of a distribution box with automatic line fault sensing provided by an embodiment of the present invention;

[0058] Figure 4 A schematic diagram of a sensing unit structure provided by an embodiment of the present invention;

[0059] Figure 5 A flow chart of a method for obtaining an intermittent short circuit characteristic indicator provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0060] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the specific implementation method, structure, features and effects of a distribution box and a method for automatically sensing line faults proposed by the present invention in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0061] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0062] The specific scheme of a distribution box with automatic line fault sensing and a method for automatic line fault sensing provided by the present invention will be described in detail below with reference to the accompanying drawings.

[0063] A distribution box is an electrical device used to distribute electricity. It is usually installed on each floor and is used to distribute power signals from the main line to each branch for use by electrical equipment. The present invention provides a distribution box with automatic line fault sensing. Figure 2 , which shows a schematic diagram of a distribution box shell with automatic line fault sensing provided by an embodiment of the present invention. The shell has the function of protecting internal components and has functions such as waterproof, dustproof and corrosion-resistant. General components include switches, leakage protection switches, fuses or miniature circuit breakers, neutral wire and ground wire terminal blocks, indicator lights and other common components of distribution boxes.

[0064] See also Figure 3 , which shows a schematic diagram of the internal partial structure of a distribution box for automatic line fault sensing provided by an embodiment of the present invention, including a distribution box body and a sensing unit. The sensing unit realizes automatic line fault sensing through data analysis, including a data acquisition module, a data processing module, a data analysis module and a communication module, please refer to Figure 4 , which shows a schematic diagram of the structure of a sensing unit provided by an embodiment of the present invention. The data acquisition module is used to collect current signals and voltage signals through current sensors and voltage sensors. The signal output end of the data acquisition module is connected to the signal input end of the data processing module, and preliminary data decomposition and analysis preparation is performed through the data processing module. The signal output end of the data processing module is connected to the signal input end of the data analysis module, and the fault perception result is obtained through signal data analysis and displayed through the communication module.

[0065] See also Figure 1 , which shows a flow chart of a line fault automatic sensing method provided by an embodiment of the present invention, the method comprising the following steps:

[0066] S1: Obtain the voltage signal segment of the distribution box in the same period of each cycle in the historical period; the voltage signal segment includes the current voltage segment and the historical voltage segment; obtain the current signal segment corresponding to the current voltage segment; after short-time Fourier transform of all voltage signal segments and current signal segments, obtain the phase, frequency and amplitude of each frequency component of each voltage signal segment and current signal segment in different short-time intervals.

[0067] When monitoring household distribution boxes, the daily changes in electricity consumption of household electrical equipment usually have certain regularity. Therefore, when evaluating line faults reflected in power data, it is necessary to analyze the characteristics of power data changes in different time periods in combination with historical cycles. In an embodiment of the present invention, one day is taken as a cycle, the voltage signal ten minutes before the current moment is taken as the current voltage segment, the current signal of the time period corresponding to the current voltage segment is taken as the current signal segment, and one week is taken as the historical period, and the voltage signal segment in the same period as the current voltage segment is taken as the historical voltage segment.

[0068] In addition to direct data changes, to analyze line faults in distribution boxes, it is also necessary to analyze the frequency and phase of power signal data. The frequency and phase of power signal data can reflect the health status of the power grid and power equipment; their changes usually indicate power grid failures, equipment abnormalities, or power quality problems.

[0069] The short-time Fourier transform (STFT) is used to decompose the current signal segment and the voltage signal segment. The short-time Fourier transform can decompose the signal into several sine waves of different frequencies in each short-time window to obtain several frequency components, that is, each signal segment is divided into several short-time intervals, and the signal in each short-time interval is decomposed into several frequency components. In an embodiment of the present invention, the short-time window length is set to 500ms, and each short-time window in each signal segment is a short-time interval. The STFT performs Fourier transform on the signal in each short-time interval to obtain the frequency component, and then obtains the amplitude, phase and frequency information of the frequency component. It should be noted that the short-time Fourier transform is a technical means well known to those skilled in the art and will not be elaborated here.

[0070] In household circuits, changes in voltage signals can reflect circuit operating status, load fluctuations, and fault conditions. Especially when detecting intermittent short circuits, some transient and non-steady-state abnormal components will appear in the voltage signal, but these components are usually buried in the main frequency signal. Therefore, it is necessary to separate the fault components in the original voltage signal through signal decomposition to reduce the interference of the fundamental signal.

[0071] However, the traditional LMD decomposition algorithm iterates the mean envelope function and obtains the pure FM signal that constitutes the PF component. The iteration end condition is that the envelope estimation function is 1, at which time the pure FM signal can be obtained. However, for the distribution box voltage signal containing intermittent short circuit and equipment startup voltage characteristics, it is easy to confuse the decomposition of intermittent short circuit and equipment startup signals, which affects the sensitivity of subsequent fault detection. Therefore, it is necessary to further analyze the signal characteristics and optimize the iteration conditions to ensure that the high-frequency characteristics of different segments are completely decomposed.

[0072] S2: According to the high frequency degree of each frequency component in each short-time interval in the current voltage segment, the similarity of the frequency component distribution between historical voltage segments, and the amplitude deviation and time deviation of the frequency component between the current voltage segment and each historical voltage segment, the intermittent short-circuit characteristic index of each short-time interval in the current voltage segment is obtained.

[0073] For intermittent short circuits, the signal change characteristics are similar to the changes in the startup signals of electrical equipment, and the load changes in household circuits have certain periodic characteristics, which are affected by the actual users' daily routines, electrical appliance usage, etc. However, the occurrence of line faults is random, and directly decomposing the signals can easily confuse the voltage signal characteristics of normal equipment startup and intermittent short circuits. Different signal segments need to be further evaluated and analyzed. First, it is necessary to analyze the change characteristics of voltage fluctuations that may be caused by intermittent short circuits in combination with historical data.

[0074] Preferably, in the embodiment of the present invention, the method for obtaining the intermittent short circuit characteristic index can be found in Figure 5 , which shows a flow chart of a method for obtaining an intermittent short circuit characteristic index provided by an embodiment of the present invention, the method comprising the following steps:

[0075] The intermittent short circuit feature is reflected in the high-frequency feature in the voltage signal. For the high-frequency signal feature caused by normal electrical equipment, since the power parameters of the equipment are consistent at startup, the high-frequency signals caused by the electrical equipment are similar. Therefore, the possibility of intermittent short circuit can be analyzed through the similarity of historical distribution. Taking into account the credibility of the historical time period, the intermittent short circuit feature index is obtained through the similarity of components in the historical voltage segment, combined with the high-frequency situation and historical analysis, reflecting the degree of short circuit feature.

[0076] S201: For any short-time interval in the current voltage segment, the amplitude of each frequency component in the short-time interval is normalized as the amplitude weight of each frequency component; based on the amplitude weight, the frequency of the frequency component in the short-time interval is weighted and averaged to obtain the high-frequency proportion index of the short-time interval.

[0077] The intermittent short circuit feature is reflected in the high-frequency feature in the voltage signal. Therefore, it is necessary to first determine the proportion of high-frequency signals in the short-time interval, and use the amplitude of the frequency component as a weight to reflect the contribution of the component. A higher weight is given to the frequency of the frequency component with higher amplitude energy. The high-frequency proportion index is obtained by weighted average of the frequency. The larger the high-frequency proportion index, the higher the proportion of high-frequency signals in the short-time interval.

[0078] It should be noted that normalization is a technical means well known to those skilled in the art, and the normalization method may be linear normalization or standard normalization, etc. The specific normalization method is not limited here.

[0079] S202: Obtain component similarity between the short time interval and each short time interval in each historical voltage segment according to the degree of proximity between the amplitudes of the frequency components in the short time interval and each short time interval in each historical voltage segment.

[0080] In order to evaluate the short-circuit characteristics of the high-frequency part of the current voltage segment, it is necessary to analyze the voltage data in the historical data at the same time. For the high-frequency signal characteristics caused by normal equipment switching, the power parameters of the equipment are consistent when it is started, and the high-frequency voltage data fluctuations generated usually have certain similarities. Therefore, the amplitude proximity of each frequency component in the short-time interval and each historical voltage segment is analyzed to preliminarily analyze the degree of similarity.

[0081] In an embodiment of the present invention, a method for obtaining component similarity includes:

[0082] Firstly, for any historical voltage segment, each short-time interval in the historical voltage segment is taken as an analysis interval and each historical voltage segment is analyzed.

[0083] The frequency of each frequency component in the analysis interval is further normalized to obtain the frequency weight of each frequency component. During the analysis process, in order to further highlight the intermittent short circuit characteristics in the circuit or the energy amplitude differences on normal electrical equipment, it is necessary to amplify the comparison weights between high-frequency information. Therefore, the frequency is used as a weight to improve the accuracy of similarity analysis of high-frequency features.

[0084] The amplitude difference between the short-time interval and the analysis interval in each frequency component is further negatively correlated to obtain the amplitude approximation of each frequency component. The smaller the difference, the more similar the amplitudes are. It should be noted that negative correlation mapping is a technical means well known to technicians in this field, and can be in the form of inverse proportion or negative exponential power, which will not be elaborated here.

[0085] Finally, the amplitude approximation is weighted and summed based on the frequency weight of the frequency component to obtain the component similarity between the short-time interval and the analysis interval. The similarity analysis contribution of the high-frequency part is increased by the frequency weight to obtain the component similarity. As an example, the expression of component similarity is: ; In the formula, Expressed as component similarity, Expressed as The amplitude difference of the frequency components is Represented as the first The frequency of the frequency component, Expressed as the total number of frequency components, It is expressed as a preset adjustment factor, the purpose of which is to prevent the denominator from being zero, making the formula meaningless. Expressed as a normalized function. Expressed as The frequency weight of the frequency component, Expressed as The amplitude approximation of the frequency components.

[0086] S203: taking the short-time interval with the greatest component similarity to the short-time interval in each historical voltage segment as the target interval of the short-time interval in each historical voltage segment.

[0087] By screening the short-time intervals with the highest similarity in the historical voltage segments, the distribution pattern of the short-time intervals with the most similar situations can clearly reflect the characteristic degree of regular startup of electrical equipment.

[0088] S204: Obtaining a time series distribution characteristic index of the short time interval according to the time distribution disorder degree of the short time interval and the target interval of all historical voltage segments.

[0089] The startup time of electrical equipment in household circuits usually has a certain regularity. Therefore, the worse the regularity between the most similar intervals in each cycle in the historical data, the more likely it is that an intermittent short circuit has occurred. Therefore, a preliminary analysis is conducted through the distribution chaos of the target interval.

[0090] In an embodiment of the present invention, a method for obtaining a time series distribution characteristic index includes:

[0091] Firstly, all the short time intervals in each historical voltage segment are sorted in time sequence to obtain the interval sequence of each historical voltage segment, and the distribution order is used to reflect the time distribution of the target interval.

[0092] The sequence number of each target interval in the interval sequence of the historical voltage segment is further used as the distribution sequence number of each target interval to reflect the distribution order of the target interval. Finally, the variance of the distribution sequence number of all target intervals corresponding to the short-time interval is used as the time series distribution characteristic index of the short-time interval. The variance reflects the degree of disorder of the distribution sequence number. The more disordered the time series order distribution of the target interval is, the more significant the possible manifestation of intermittent short circuit is.

[0093] S205: Obtaining a historical feature weight of the short time interval according to the time deviation and component similarity between the short time interval and each target interval.

[0094] At the same time, when performing similarity analysis, the greater the deviation in electricity consumption of the historical data itself, the greater the error in the similarity calculation result will be, making the result of the comparative analysis with the historical data even less credible. Therefore, it is necessary to combine the time deviation of the target interval and analyze the credible adjustment based on the degree of time deviation of the historical data.

[0095] In an embodiment of the present invention, a method for obtaining historical feature weights includes:

[0096] The time difference between the short time interval and each target interval at the starting time is negatively correlated and mapped to obtain the time difference weight between the short time interval and each target interval. The smaller the time difference, the closer the power consumption characteristics of the short time interval and the target interval are in time distribution, and the result of the similarity analysis is more credible.

[0097] Further, based on the time difference weight, the component similarities between the short time interval and the target interval are weighted and summed to obtain the historical feature weight of the short time interval. The time difference weight reflects the credibility of each target interval, and then combined with the component similarity of the target interval to reflect the overall similarity between the short time interval and the historical data. The larger the historical feature weight, the better the similarity of the short time interval in historical analysis, and the higher the credibility of the historical data.

[0098] S206: Combining the high frequency proportion index, the time series distribution characteristic index and the historical characteristic weight of the short time interval, an intermittent short circuit characteristic index of the short time interval is obtained.

[0099] The credibility of similar analysis is adjusted by historical feature weights, and the probability of intermittent short circuit in a short time interval is calculated by combining the high-frequency features of the short time interval and the historical regularity analysis results. In an embodiment of the present invention, the product of the high-frequency proportion index, the time series distribution feature index and the historical feature weight of the short time interval is used as the intermittent short circuit feature index of the short time interval.

[0100] When compared with historical voltage signals, the more obvious the intermittent short circuit characteristics reflected by the voltage signal characteristics in the short time interval, that is, the larger the intermittent short circuit characteristic index, the higher the probability of intermittent short circuit.

[0101] At this point, the preliminary analysis of the signal is completed, and the probability of the existence of an intermittent short circuit is obtained.

[0102] S3: According to the phase deviation between the frequency components of the current signal segment and the current voltage segment, and the degree of signal change trend of each data point in the current voltage segment, combined with the intermittent short circuit characteristic index of the short time interval in which each data point is located, the retention index of each data point in the current voltage segment is obtained.

[0103] Under normal circumstances, the startup process of electrical equipment is a linear load change, and the change of its voltage signal during the startup of the equipment has little effect on its phase. However, due to the nonlinear effect caused by intermittent short circuits, the synchronization of voltage and current will be disrupted, resulting in irregular changes between their phases.

[0104] The startup process of the equipment will generate a large starting current or impact current, which will be affected by the internal resistance and inductive reactance of the power grid, causing the voltage to drop for a certain short time. In the startup process of general equipment, in order to ensure that its internal circuit components are not directly impacted by the starting current and cause damage to the components, its voltage drop curve is relatively gentle, while intermittent short circuit directly causes line short circuit, and the voltage drop is relatively severe.

[0105] Therefore, the phase deviation of current and voltage, as well as the signal change trend of the data points in the signal, combined with the analyzed intermittent short circuit characteristic indicators, can comprehensively reflect the significance of the intermittent short circuit anomaly at each data point, and retain as many data features as possible in subsequent iterative decomposition.

[0106] Preferably, in an embodiment of the present invention, the method for obtaining the retention index includes:

[0107] First, for any short-time interval in the current voltage segment, the short-time interval corresponding to the short-time interval in the current signal segment is used as the current short-time interval of the short-time interval, and the current corresponding part is determined. The phase difference between the short-time interval and the current short-time interval in each frequency component is further calculated, and the sum of all phase differences is calculated to obtain the current phase difference value of the short-time interval. The current phase difference value reflects the phase deviation degree of the current and voltage itself in the short-time interval.

[0108] Further, in the current voltage segment, the mean difference between the current phase difference between the short-time interval and each adjacent short-time interval is calculated to obtain the phase difference change index of the short-time interval. The difference in the phase difference between adjacent intervals reflects the irregularity of the phase change. Except for the first and last intervals, each short-time interval has two adjacent short-time intervals. The difference between the current phase difference values ​​reflects the difference in the phase current phase difference between the previous short-time interval and the next short-time interval. The larger the phase difference change index, the more obvious the irregular change of the phase difference between the current and voltage.

[0109] Furthermore, the first-order derivative at each data point in the current voltage segment is normalized as the change value of each data point. The derivative reflects the trend change of the signal. The larger the change value, the more significant the change trend. The product of the absolute value of the voltage of each data point in the current voltage segment and the change value is used as the abnormal retention degree of each data point in the current voltage segment. The larger the abnormal retention degree, the more drastic the voltage change of the current time series data point, and the less the voltage change of the data point has the characteristics of the internal protection measures for the components when the equipment is started, and the retention characteristics of the point in the iteration process should be relatively large.

[0110] Finally, the retention index of each data point in the current voltage segment is obtained by combining the abnormal retention degree of each data point in the current voltage segment, the phase change index of the short-time interval corresponding to the data point, and the current phase difference. In an embodiment of the present invention, the product of the abnormal retention degree of each data point in the current voltage segment, the phase change index of the short-time interval corresponding to the data point, and the current phase difference is used as the retention index of each data point in the current voltage segment. The larger the retention index, the more obvious the intermittent short circuit feature at the data point, and the greater the degree of retention should be.

[0111] S4: Perform iterative signal decomposition based on the retention index of each data point in the current voltage segment to obtain signal components; obtain the intermittent short circuit evaluation index of each signal component according to the envelope change characteristics of each signal component and the chaotic energy distribution of the signal component in different short time intervals.

[0112] The retention of the data points is adjusted by the LMD decomposition algorithm according to the iterative mean envelope function and the obtained PF signal components. In an embodiment of the present invention, iterative signal decomposition is performed according to the retention index of each data point in the current voltage segment to obtain the signal components, including:

[0113] The retention index of each data point in the current voltage segment is used as a weight, and the value of each data point in the current voltage segment is weighted to obtain the current modulation signal, and the current modulation signal is further iteratively decomposed.

[0114] The current modulated signal is further decomposed by iterative envelope estimation function to obtain signal components. The decomposition process mainly includes obtaining the local mean function by calculating the mean point of all adjacent extreme points. and the local envelope estimation function ; By subtracting the local mean function from the original signal Get a zero mean signal ; Estimation function through local envelope For zero mean signal Demodulate and get the demodulated signal ; Repeat the above steps until the envelope estimation function ,at this time The product of the demodulated signal and the envelope signal is selected as the decomposition result of the current PF function to obtain the signal component.

[0115] After amplifying the amplitude of the data points on the corresponding time series by retaining the index, in the subsequent calculation process of the envelope estimation function and the local mean function, the retention of the time series data points with obvious short-circuit characteristics in the decomposition process can be amplified, thereby improving the decomposition ability of the intermittent short-circuit fault waveform.

[0116] After decomposition, multiple signal components are obtained for line fault analysis. The decomposed components of the signal for normal operation usually have a relatively regular envelope, while the intermittent short-circuit components will cause irregular spikes or rapid fluctuations in the signal envelope. Since intermittent short-circuit signals usually have a short duration and large voltage fluctuations, the energy of different signal components in a certain time segment is relatively concentrated, so the intermittent short-circuit characteristics can be evaluated through the energy distribution of different signal components. Therefore, fault assessment is performed based on the envelope change characteristics and scattered energy distribution.

[0117] Preferably, in an embodiment of the present invention, a method for obtaining an intermittent short circuit evaluation index includes:

[0118] First, for any signal component, the signal energy value of the signal component in each short time interval is obtained. The signal component is segmented by short time intervals and analyzed from the energy perspective. The variance of the signal energy value of the signal component in all short time intervals is used as the energy anomaly indicator of the signal component. The larger the variance, the more dispersed and chaotic the energy distribution is, and the more obvious the intermittent short circuit energy characteristics contained in the component are.

[0119] The envelope of the signal component is further obtained, and the envelope includes the upper envelope and the lower envelope for analysis. The information entropy of the derivative of each data point on each envelope is calculated as the change complexity of each envelope, reflecting the irregularity of the change. The mean of the change complexity of the envelope of the signal component is used as the envelope abnormality index of the signal component. Combined with the situation reflected by all envelopes, the larger the envelope abnormality index is, the closer the information reflected by the component envelope is to the signal envelope characteristics of intermittent short circuits.

[0120] Finally, the product of the energy anomaly index and the envelope anomaly index of the signal component is used as the intermittent short circuit evaluation index of the signal component. The larger the energy anomaly index and the envelope anomaly index are, the greater the possibility of the intermittent short circuit anomaly is.

[0121] S5: Obtain fault perception results based on all intermittent short circuit evaluation indicators of the current voltage segment.

[0122] Fault perception is performed by obtaining the magnitude of all intermittent short circuit evaluation indicators after iterative decomposition of the current voltage segment. In an embodiment of the present invention, when the value of the intermittent short circuit evaluation indicator in the signal component after normalization is greater than the preset fault threshold, the fault perception result at the current moment is recorded as the presence of an intermittent short circuit fault.

[0123] In the embodiment of the present invention, the preset fault threshold is set to 0.7, and the specific value can be adjusted by the implementer according to the specific implementation scenario, and is not limited here. The fault perception result at the current moment can be displayed to the management end through the communication module to reduce the probability of loss caused by line faults.

[0124] In summary, after obtaining the voltage and current data of the distribution box, the present invention performs a short-time Fourier transform on the voltage and current data to obtain the phase and frequency of the power signal data in the short time interval, and improves the analysis accuracy of instantaneous changes by introducing a short-time Fourier transform. The intermittent short circuit characteristic index of the line voltage signal data under the current situation can be analyzed in combination with the high-frequency characteristics of the intermittent short circuit and the deviation from the historical short time interval, and the distribution characteristics of the frequency in the local instantaneous detail range of the signal and the historical distinction can be used to reflect the probability of the existence of the intermittent short circuit. Further, from the perspective of the phase difference change of the current and voltage and the voltage change trend of the intermittent short circuit in the short time interval, the abnormal possibility of the data points in the signal is analyzed, and the intermittent short circuit characteristic index and the current and voltage phase deviation and trend change of each data point in each short time interval are combined to evaluate the degree of retention of each sampled data point in the subsequent signal decomposition process, and the voltage signal decomposition process is optimized by the retention index of the data point, and the signal component is obtained from the envelope and energy anomaly to evaluate the intermittent short circuit fault result. The present invention introduces short-time Fourier transform analysis to distinguish the distribution of historical data in the instantaneous range, and optimizes the degree of signal decomposition in combination with the abnormal phase and voltage change trend, so that the intermittent short circuit characteristics are more retained, the perception ability of intermittent short circuit line faults is enhanced, and the accuracy of fault detection is improved.

[0125] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0126] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A method for automatically sensing line faults, characterized in that: The method comprises: Obtain the voltage signal segment of the distribution box in the same period of each cycle in the historical period; the voltage signal segment includes the current voltage segment and the historical voltage segment; obtain the current signal segment corresponding to the current voltage segment; after short-time Fourier transform of all voltage signal segments and current signal segments, obtain the phase, frequency and amplitude of each frequency component of each voltage signal segment and current signal segment in different short-time intervals; According to the high frequency degree of each frequency component in each short-time interval in the current voltage segment, the similarity of the frequency component distribution between historical voltage segments, and the amplitude deviation and time deviation of the frequency component between the current voltage segment and each historical voltage segment, the intermittent short circuit characteristic index of each short-time interval in the current voltage segment is obtained; According to the phase deviation between the frequency components of the current signal segment and the current voltage segment, and the degree of signal change trend of each data point in the current voltage segment, combined with the intermittent short circuit characteristic index of the short time interval where each data point is located, the retention index of each data point in the current voltage segment is obtained; Iterative signal decomposition is performed based on the retention index of each data point in the current voltage segment to obtain signal components; intermittent short circuit evaluation indicators of each signal component are obtained according to the envelope change characteristics of each signal component and the chaotic energy distribution of the signal component in different short time intervals; Obtain fault perception results based on all intermittent short circuit evaluation indicators of the current voltage segment; The method for obtaining the intermittent short circuit characteristic index includes: For any short-time interval in the current voltage segment, the amplitude of each frequency component in the short-time interval is normalized, and the frequency of the frequency component in the short-time interval is weighted and averaged based on the amplitude weight as the amplitude weight of each frequency component to obtain the high-frequency proportion index of the short-time interval; According to the closeness of the amplitude between the frequency components in the short time interval and each short time interval in each historical voltage segment, the component similarity between the short time interval and each short time interval in each historical voltage segment is obtained; The short-time interval with the greatest component similarity to each historical voltage segment is used as the target interval of the short-time interval in each historical voltage segment; According to the time distribution disorder degree of the short time interval and the target interval of all historical voltage segments, the time series distribution characteristic index of the short time interval is obtained; According to the time deviation and component similarity between the short time interval and each target interval, the historical feature weight of the short time interval is obtained; The product of the high frequency proportion index, the time series distribution characteristic index and the historical characteristic weight of the short time interval is used as the intermittent short circuit characteristic index of the short time interval; The method for obtaining the component similarity includes: For any historical voltage segment, each short-time interval in the historical voltage segment is taken as the analysis interval in turn; Normalize the frequency of each frequency component in the analysis interval to obtain the frequency weight of each frequency component; Negative correlation mapping is performed between the amplitude difference of the short time interval and the analysis interval between each frequency component to obtain the amplitude approximation of each frequency component; The amplitude approximation is weighted based on the frequency weight of the frequency component and the sum is calculated to obtain the component similarity between the short-time interval and the analysis interval; The method for obtaining the time series distribution characteristic index includes: Sort all short-time intervals in each historical voltage segment in time sequence to obtain an interval sequence for each historical voltage segment; The serial number of each target interval in the interval sequence of the historical voltage segment is used as the distribution serial number of each target interval; the variance of the distribution serial numbers of all target intervals corresponding to the short-time interval is used as the time series distribution characteristic index of the short-time interval; The method for obtaining the historical feature weights includes: Negative correlation mapping is performed between the time difference between the short time interval and each target interval at the start time to obtain the time difference weight between the short time interval and each target interval; Based on the time difference weight, the component similarities between the short time interval and the target interval are weighted and summed to obtain the historical feature weight of the short time interval; The method for obtaining the retention index includes: For any short-time interval in the current voltage segment, the short-time interval corresponding to the short-time interval in the current signal segment is used as the current short-time interval of the short-time interval; Calculate the phase difference between the short-time interval and the current short-time interval at each frequency component, and calculate the sum of all phase differences to obtain the current phase difference value of the short-time interval; In the current voltage segment, the average of the current phase difference between the short time interval and each adjacent short time interval is calculated to obtain the phase difference change index of the short time interval; The first-order derivative at each data point in the current voltage segment is normalized as the change value of each data point; the product of the absolute value of the voltage of each data point in the current voltage segment and the change value is used as the abnormal retention degree of each data point in the current voltage segment; Combine the abnormal retention degree of each data point in the current voltage segment, as well as the phase change index and current phase difference value of the short-time interval corresponding to the data point, to obtain the retention index of each data point in the current voltage segment; The method for obtaining the intermittent short circuit evaluation index includes: For any signal component, the signal energy value of the signal component in each short time interval is obtained; the variance of the signal energy values ​​of the signal component in all short time intervals is used as the energy anomaly indicator of the signal component; Obtain the envelope of the signal component, the envelope including an upper envelope and a lower envelope; calculate the information entropy of the derivative of each data point on each envelope as the variation complexity of each envelope; take the mean of the variation complexity of the envelope of the signal component as the envelope anomaly indicator of the signal component; The product of the energy abnormality index and the envelope abnormality index of the signal component is used as the intermittent short circuit evaluation index of the signal component.

2. A line fault automatic sensing method according to claim 1, characterized in that: The iterative signal decomposition based on the retention index of each data point in the current voltage segment to obtain the signal components includes: The retention index of each data point in the current voltage segment is used as a weight, and the value of each data point in the current voltage segment is weighted to obtain the current modulation signal; the current modulation signal is decomposed by an iterative envelope estimation function to obtain signal components.

3. A line fault automatic sensing method according to claim 1, characterized in that: The fault perception result is obtained based on all intermittent short circuit evaluation indicators of the current voltage segment, including: When the normalized value of the intermittent short circuit evaluation index of the signal component is greater than the preset fault threshold, the fault perception result at the current moment is recorded as the existence of an intermittent short circuit fault.

4. A distribution box with automatic line fault sensing, characterized in that: It includes a distribution box body and a sensing unit, wherein the sensing unit includes a data acquisition module, a data processing module, a data analysis module and a communication module; The signal output end of the data acquisition module is connected to the signal input end of the data processing module, the signal output end of the data processing module is connected to the signal input end of the data analysis module, and the output end of the data analysis module is connected to the signal input end of the communication module; the communication module is used to display the fault perception result; The data acquisition module is used to collect current signals and voltage signals through current sensors and voltage sensors, and transmit all collected data to the data processing module, including the current voltage segment and the historical voltage segment in the same period of each cycle in the historical period, as well as the current signal segment corresponding to the current voltage segment; The data processing module is used to obtain the phase, frequency and amplitude of each frequency component of each voltage signal segment and current signal segment in different short time intervals after short-time Fourier transformation of all voltage signal segments and current signal segments, and transmit all data to the data analysis module; The data analysis module obtains the intermittent short circuit characteristic index of each short time interval in the current voltage segment according to the high frequency degree of each frequency component in each short time interval in the current voltage segment, the similarity of the frequency component distribution between the historical voltage segments, and the amplitude deviation and time deviation of the frequency component between the current voltage segment and each historical voltage segment; According to the phase deviation between the frequency components of the current signal segment and the current voltage segment, and the degree of signal change trend of each data point in the current voltage segment, combined with the intermittent short circuit characteristic index of the short time interval where each data point is located, the retention index of each data point in the current voltage segment is obtained; Iterative signal decomposition is performed based on the retention index of each data point in the current voltage segment to obtain signal components. According to the envelope change characteristics of each signal component and the chaotic energy distribution of the signal component in different short time intervals, the intermittent short circuit evaluation index of each signal component is obtained. Obtain fault perception results based on all intermittent short circuit evaluation indicators of the current voltage segment, and transmit and display the fault perception results through the communication module; The method for obtaining the intermittent short circuit characteristic index includes: For any short-time interval in the current voltage segment, the amplitude of each frequency component in the short-time interval is normalized, and the frequency of the frequency component in the short-time interval is weighted and averaged based on the amplitude weight as the amplitude weight of each frequency component to obtain the high-frequency proportion index of the short-time interval; According to the closeness of the amplitude between the frequency components in the short time interval and each short time interval in each historical voltage segment, the component similarity between the short time interval and each short time interval in each historical voltage segment is obtained; The short-time interval with the greatest component similarity to each historical voltage segment is used as the target interval of the short-time interval in each historical voltage segment; According to the time distribution disorder degree of the short time interval and the target interval of all historical voltage segments, the time series distribution characteristic index of the short time interval is obtained; According to the time deviation and component similarity between the short time interval and each target interval, the historical feature weight of the short time interval is obtained; The product of the high frequency proportion index, the time series distribution characteristic index and the historical characteristic weight of the short time interval is used as the intermittent short circuit characteristic index of the short time interval; The method for obtaining the component similarity includes: For any historical voltage segment, each short-time interval in the historical voltage segment is taken as the analysis interval in turn; Normalize the frequency of each frequency component in the analysis interval to obtain the frequency weight of each frequency component; Negative correlation mapping is performed between the amplitude difference of the short time interval and the analysis interval between each frequency component to obtain the amplitude approximation of each frequency component; The amplitude approximation is weighted based on the frequency weight of the frequency component and the sum is calculated to obtain the component similarity between the short-time interval and the analysis interval; The method for obtaining the time series distribution characteristic index includes: Sort all short-time intervals in each historical voltage segment in time sequence to obtain an interval sequence for each historical voltage segment; The serial number of each target interval in the interval sequence of the historical voltage segment is used as the distribution serial number of each target interval; the variance of the distribution serial numbers of all target intervals corresponding to the short-time interval is used as the time series distribution characteristic index of the short-time interval; The method for obtaining the historical feature weights includes: Negative correlation mapping is performed between the time difference between the short time interval and each target interval at the start time to obtain the time difference weight between the short time interval and each target interval; Based on the time difference weight, the component similarities between the short time interval and the target interval are weighted and summed to obtain the historical feature weight of the short time interval; The method for obtaining the retention index includes: For any short-time interval in the current voltage segment, the short-time interval corresponding to the short-time interval in the current signal segment is used as the current short-time interval of the short-time interval; Calculate the phase difference between the short-time interval and the current short-time interval at each frequency component, and calculate the sum of all phase differences to obtain the current phase difference value of the short-time interval; In the current voltage segment, the average of the current phase difference between the short time interval and each adjacent short time interval is calculated to obtain the phase difference change index of the short time interval; The first-order derivative at each data point in the current voltage segment is normalized as the change value of each data point; the product of the absolute value of the voltage of each data point in the current voltage segment and the change value is used as the abnormal retention degree of each data point in the current voltage segment; Combine the abnormal retention degree of each data point in the current voltage segment, as well as the phase change index and current phase difference value of the short-time interval corresponding to the data point, to obtain the retention index of each data point in the current voltage segment; The method for obtaining the intermittent short circuit evaluation index includes: For any signal component, the signal energy value of the signal component in each short time interval is obtained; the variance of the signal energy values ​​of the signal component in all short time intervals is used as the energy anomaly indicator of the signal component; Obtain the envelope of the signal component, the envelope including an upper envelope and a lower envelope; calculate the information entropy of the derivative of each data point on each envelope as the variation complexity of each envelope; take the mean of the variation complexity of the envelope of the signal component as the envelope anomaly indicator of the signal component; The product of the energy abnormality index and the envelope abnormality index of the signal component is used as the intermittent short circuit evaluation index of the signal component.

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