CN111291328B - Transient event identification method, system and equipment based on fine slope - Google Patents
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Abstract
The invention discloses a transient event identification method, a transient event identification system and transient event identification equipment based on a fine slope, which comprise the following steps: collecting working characteristic data of E kinds of electrical equipment under different arrangement and combination operation conditions; dividing the preprocessed working characteristic data to generate a periodic time period sequence; calculating the variance of the fine slope value corresponding to each period in the period time period sequence; calculating the variance ratio and the variance difference of adjacent time periods of each period; and calculating a fine slope variance difference value threshold and a fine slope variance ratio threshold, and judging transient events. According to the embodiment of the invention, the waveform characteristics of the electric appliances during operation are reflected by solving the fine slope characteristics, transient event identification is carried out on most electric appliances by the fine slope characteristics, and almost all possible switching states of the electric appliances are considered by solving the fine slope variance difference threshold and the fine slope variance ratio threshold, so that the accuracy of identifying the transient event is greatly improved.
Description
Technical Field
The invention relates to the technical field of transient analysis of power systems, in particular to a transient event identification method, system and equipment based on a fine slope.
Background
The traditional power load monitoring method is greatly limited in application due to the characteristics of high cost, low efficiency and the like. Non-invasive load detection (NILM) technology is favored by power load detection workers because it only requires a related sensor to be installed at the customer's entrance to the grid to monitor the operation of the electrical equipment.
At present, research on non-invasive load monitoring is mainly focused on load steady state feature recognition technology and the like. However, the efficiency and accuracy of the load steady state identification have certain limitations on industrial application, so that the identification of the load and the running state thereof by utilizing the load transient characteristics becomes another key technology for load monitoring of NILM development. The key of the load identification technology based on transient characteristics is the accurate capturing technology and method of switching time of electrical equipment. For the accurate capturing technology and method of the switching time of the electrical equipment, the related technical scheme is an active power threshold method and a bilateral accumulation and transient event automatic detection algorithm based on a sliding window. The research results at home and abroad show that the transient event identification method is basically a traditional threshold method for judging according to the change characteristics of related signals (such as current effective values, active power and the like), the method needs to determine the corresponding threshold according to expert experience, lacks a scientific method for determining the threshold, has low accuracy, is easily influenced by system noise, has weak anti-interference capability, has poor capturing effect on transient switching events of low-power electrical equipment, and is inconvenient to operate.
In summary, in the prior art, the transient event recognition method needs to determine the corresponding threshold according to the human experience, which has the technical problem of low recognition accuracy.
Disclosure of Invention
The invention provides a transient event identification method, a transient event identification system and transient event identification equipment based on a fine slope, which solve the technical problem that the identification accuracy is low because the transient event identification method in the prior art needs to determine a corresponding threshold value according to human experiences.
The invention provides a transient event identification method based on a fine slope, which comprises the following steps:
collecting working characteristic data of E kinds of electrical equipment under different arrangement and combination operation conditions in a preset period;
preprocessing the working characteristic data of each permutation and combination;
dividing the preprocessed working characteristic data to generate a periodic time period sequence;
calculating the variance of the fine slope value corresponding to each period in the period time period sequence;
calculating a variance ratio and a variance difference of adjacent time periods of each period according to the variance of the fine slope value;
calculating a fine slope variance difference threshold and a fine slope variance ratio threshold according to the variance ratio and the variance difference;
and judging the transient event according to the variance ratio, the variance difference, the fine slope variance difference threshold and the fine slope variance ratio threshold.
Preferably, the operating characteristic data comprises high frequency current data and high frequency voltage data of the steady state process.
Preferably, the preprocessing process is to perform wavelet noise reduction processing and interpolation processing on the working characteristic data, and the obtained high-frequency current data sequence and high-frequency voltage data sequence are obtained.
Preferably, the specific process of generating the periodic time period sequence is as follows:
dividing the current data sequence and the voltage data sequence by taking the first working characteristic data sampling point as a starting point and taking the working characteristic data sampling point n of one period as a unit to generate a period time period sequence Tn (T) 1 ,T 2 ,…，T Tn ) Where Tn represents the total number of cycles.
Preferably, the specific process of calculating the variance of the fine slope value corresponding to each cycle in the cycle time period sequence is as follows:
calculating the slope of adjacent pseudo sampling points in each period:
calculating the fine slope corresponding to each period according to the slope of the adjacent pseudo sampling points in each period:
calculating the average value of the fine slope of each period according to the fine slope corresponding to each period;
the variance of the fine slope value is calculated from the average of the fine slopes of each cycle.
Preferably, the specific process of performing transient event judgment is as follows:
statistics of meeting ΔSk in each period time period sequence pjj Less than the fine slope variance difference threshold and Rk pjj The proportion P (l) occupied by the time period smaller than the fine slope variance ratio threshold is judged, and the transient event is judged according to the value of P (l); wherein Rk is pjj And ΔSk pjj And respectively representing the variance ratio and the variance difference characteristics of the jth time period in the high-frequency steady-state current and the high-frequency steady-state voltage data of the p-th permutation and combination.
Preferably, the specific process of judging the transient event according to the value of P (l) is as follows:
setting a minimum threshold p1 and a maximum threshold p2;
if P (l) < P1, then this time period is indicated as being in steady state;
if P1 is less than P (l) and less than P2, indicating that the time period is in a transient event early warning process;
if P (l) > P2, this time period is indicated to be in transient.
Preferably, if in the transient state, the duration of the transient process is recorded.
A transient event identification system based on a fine slope comprises a data acquisition module, a preprocessing module, a data segmentation module, a calculation module and a transient event judgment module;
the data acquisition module is used for acquiring working characteristic data of E kinds of electrical equipment under different arrangement and combination operation conditions in a preset period;
the preprocessing module is used for preprocessing the working characteristic data of each permutation and combination;
the data segmentation module is used for segmenting the preprocessed working characteristic data to generate a periodic time period sequence;
the calculating module is used for calculating the variance of the fine slope value corresponding to each period in the period time period sequence; calculating a variance ratio and a variance difference of adjacent time periods of each period according to the variance of the fine slope value; calculating a fine slope variance difference threshold and a fine slope variance ratio threshold according to the variance ratio and the variance difference;
the transient event judgment module is used for judging the transient event according to the variance ratio, the variance difference, the fine slope variance difference threshold and the fine slope variance ratio threshold.
A fine slope based transient event identification device comprising the device comprising a processor and a memory;
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is configured to execute a fine slope based transient event identification method as described above according to instructions in the program code.
From the above technical scheme, the invention has the following advantages:
the embodiment of the invention reflects the waveform characteristics of the electric appliances during operation by solving the fine slope characteristics, and because each electric appliance has unique waveform data, the fine slope characteristics have very excellent transient event identification effect on most electric appliances including low-power electric appliances, and the accuracy of identifying the transient event is greatly improved by solving the fine slope variance difference threshold and the fine slope variance ratio threshold which give consideration to the switching state of the electric appliances which are almost all possible to occur.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only some embodiments of the invention, and that other drawings can be obtained from these drawings without inventive faculty for a person skilled in the art.
Fig. 1 is a flowchart of a method, a system and a device for transient event identification based on a fine slope according to an embodiment of the present invention.
Fig. 2 is a system structure diagram of a transient event recognition method, system and device based on a fine slope according to an embodiment of the present invention.
Fig. 3 is a device structure diagram of a transient event recognition method, system and device based on a fine slope according to an embodiment of the present invention.
Fig. 4 is a logic diagram of a method for generating a time period of a transient event identification method, a system and a device based on a fine slope according to an embodiment of the present invention.
Detailed Description
The embodiment of the invention provides a transient event identification method, a transient event identification system and transient event identification equipment based on a fine slope, which solve the technical problem that the identification accuracy is low because a corresponding threshold value is required to be determined according to human experiences in the transient event identification method in the prior art.
In order to make the objects, features and advantages of the present invention more comprehensible, the technical solutions in the embodiments of the present invention are described in detail below with reference to the accompanying drawings, and it is apparent that the embodiments described below are only some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The embodiment aims to overcome the defect that the corresponding threshold value is required to be determined according to human experience in the prior art, and provides a transient event identification method, a transient event identification system and transient event identification equipment based on a fine slope. The method can effectively solve the defect of poor transient event identification effect of low-power electrical equipment, and can effectively improve the accuracy and operability of transient event identification.
The following describes a common method for identifying transient events of electrical equipment:
(1) Active power thresholding: the method comprises the steps of acquiring power values of a user side, and acquiring a power sequence according to a sampling sequence; calculating a 0.5 percentile of the power sequences as a threshold; a power differential sequence is calculated. Judging whether each absolute value in the power differential sequence exceeds a threshold value, taking the point exceeding the threshold value as a variable point, and recording, and arranging the variable points according to the sequence of corresponding elements in the power differential sequence to form a variable point sequence; and according to the variable point sequence, obtaining a transient event start point sequence and a steady event start point sequence by an event start point calculation method.
(2) Sliding window based bilateral accumulation sum (CUSUM) transient event automatic detection algorithm: the algorithm theory is based on a sequential probability ratio detection theory in a sequential analysis principle, a data sequence of related signals such as current, voltage, active power and the like is obtained, sliding window difference value accumulation is carried out on the data sequence, small offsets in the process are continuously accumulated, the effect of amplification is achieved, and whether the accumulated result meets the threshold condition of transient event occurrence or not is judged according to a preset threshold value, so that transient event detection is achieved.
(3) Current effective value thresholding: calculating a current effective value according to the obtained original current data: and judging that an event occurs when the continuous variation amplitude of the current effective value in a time period is not smaller than a first preset wide value and the difference between the current effective value at the ending moment of the time period and the current effective value at the starting moment of the time period is larger than a second preset wide value.
From the above three methods, all of the three methods are conventional thresholding methods based on human judgment, and all of the three methods have various disadvantages of the conventional thresholding methods.
Referring to fig. 1, fig. 1 is a flowchart of a method for identifying transient events based on a fine slope, a system and a device according to an embodiment of the present invention.
As shown in fig. 1, the transient event identification method based on the fine slope provided by the embodiment of the invention includes the following steps:
collecting working characteristic data of E kinds of electrical equipment under different arrangement and combination operation conditions in a preset period Time; since there are E kinds of electrical devices in total, the combination mode has p=2 in total E A kind of module is assembled in the module and the module is assembled in the module.
Preprocessing the working characteristic data of each permutation and combination;
dividing the preprocessed working characteristic data to generate a periodic time period sequence;
calculating the variance of the fine slope value corresponding to each period in the period time period sequence;
calculating a variance ratio and a variance difference of adjacent time periods of each period according to the variance of the fine slope value;
calculating a fine slope variance difference threshold and a fine slope variance ratio threshold according to the variance ratio and the variance difference;
and judging the transient event according to the variance ratio, the variance difference, the fine slope variance difference threshold and the fine slope variance ratio threshold.
As a preferred embodiment, the operating characteristic data comprise high frequency current data i of the steady state process k1 ,i k2 ,...,i kn And high-frequency voltage data u k1 ,u k2 ,...,u kn Wherein k represents the kth permutation and combination, and the specific permutation and combination is shown in table 1.
Table 1: working characteristic data collected under p kinds of arrangement and combination modes
As a preferred embodiment, the preprocessing is performed by performing wavelet noise reduction processing and interpolation processing on the operation characteristic data, and the obtained high-frequency current data sequence (I 1 ,I 2 ,…,I m ) And a high-frequency voltage data sequence (U 1 ,U 2 ,…,U m ) Wherein m represents the total working characteristic data sampling point number after interpolation processing, I m And U m The instantaneous current value and the instantaneous voltage value at the mth point are represented.
As a preferred embodiment, the specific procedure for generating the periodic time period sequence is as follows:
dividing the current data sequence and the voltage data sequence by taking the first working characteristic data sampling point as a starting point and taking the working characteristic data sampling point n of one period as a unit to generate a period time period sequence Tn (T) 1 ,T 2 ,…，T Tn ) Where Tn represents the total number of cycles, the specific process is as follows:
generating a first period by taking a first sampling point as a starting point and taking the sampling point number n of one period as a unit:
generating a second period by taking the (n+1) th sampling point as a starting point and taking the sampling point number n of one period as a unit:
and so on, a periodic time series (T 1 ,T 2 ,…，T Tn )。
Further, the period time sequence is divided into t periods as units and one period as a step length to generate a time sequence (t 1 ,t 2 ,…，t Tn-t ) Wherein Tn-t represents the total number of time periods, and the specific processing is as follows:
(1) Recording the preset period number as t, and generating a first time period t by taking t periods as a unit 1 ＝(T 1 ,T 2 ,...，T t )；
(2) Generating a second time period t by taking one period as a step length 2 ＝(T 2 ,T 3 ,…，T t+1 )；
(3) And so on, with t periods as a unit and one period as a step length, a time period sequence (t 1 ,t 2 ,…，t Tn-t )；
Fig. 4 is a logic diagram of a time period generation method, where m represents the total sampling number, n represents the sampling number contained in each cycle, tn represents the total number of cycles, and Tn-t represents the total number of time periods.
As a preferred embodiment, the specific process of calculating the variance of the fine slope value corresponding to each cycle in the sequence of cycle time periods is:
calculating the slope of adjacent pseudo sampling points in each period:
obtaining slope sequences (k) of adjacent pseudo-sampling points in each period j,1 ,k j,2 ,…，k j,n-1, ),j∈[1,Tn]Tn represents the total number of periods, k j,n-1, Representing the slope of the n-1 sampling time point of the jth cycle.
Calculating the fine slope corresponding to each period according to the slope of the adjacent pseudo sampling points in each period:
obtain the fine slope (Ak) corresponding to each period 1 ,Ak 2 ,…，Ak j ),j∈[1,Tn]Tn represents the total number of cycles, ak j,n-1, Representing the fine slope corresponding to the j-th cycle.
Calculating the average value of the fine slope of each period according to the fine slope corresponding to each period;
where t represents the number of preset cycles, i.e. the number of cycles comprised by a time period,
indicate->
Average value of fine slope of each period of time.
Calculating variance of fine slope values from average value of fine slope of each period
Further, calculating the variance ratio and variance difference characteristics of the adjacent time periods specifically includes:
(1) Calculating variance ratio of adjacent time periods
(2) Calculating variance difference features for adjacent time periods
Combining the high-frequency voltage and high-frequency current data generated by p permutation and combination to obtain variance characteristic values corresponding to each permutation and combination condition:
(1) Calculating variance ratio of adjacent time periods
(2) Calculating variance difference features for adjacent time periods
Wherein Rk pjj And ΔSk pjj And respectively representing the variance ratio and the variance difference characteristics of the jth time period in the high-frequency steady-state current and the high-frequency steady-state voltage data of the p-th permutation and combination.
Further, according to the obtained ΔSk pjj And Rk pjj Obtaining a fine slope variance difference threshold Sk using a normal distribution model on And a fine slope variance ratio threshold Rk on The process is described as follows:
experimental verification shows that variance feature DeltaSk pjj And Rk pjj The distribution of (a) respectively conforms to the normal distribution N (mu, sigma) 2 ) Events, therefore, the fine slope variance difference ΔSk is calculated by 3 sigma principle pjj And a fine slope variance ratio Rk pjj Two boundaries S falling within the range of (μ -3σ, μ+3σ) 1 ，S 2 ，R 1 ，R 2 Obtaining a corresponding fine slope variance difference threshold Sk on And a fine slope variance ratio threshold Rk on Equal to respectively:
Sk on ＝S 2
Rk on ＝R 2 。
as a preferred embodiment, the specific procedure for transient event judgment is as follows:
statistics of meeting ΔSk in each period time period sequence pjj Less than the fine slope variance difference threshold and Rk pjj Less than fineAnd judging the transient event according to the value of P (l).
The concrete steps are as follows:
the proportion of the time period satisfying the threshold condition within each cycle time period L:
as a preferred embodiment, the specific procedure for judging the transient event according to the value of P (l) is as follows:
setting a minimum threshold p1 and a maximum threshold p2;
if P (l) < P1, then this time period is indicated as being in steady state;
if P1 is less than P (l) and less than P2, indicating that the time period is in a transient event early warning process;
if P (l) > P2, this time period is indicated as transient.
As a preferred embodiment, if in a transient state, the duration of the transient process is recorded, specifically as follows: taking the starting time of the first time period of the time periods as T STARTOREND ；
Recording the first T in the sampling period Time seconds STARTOREND Start time T for transient event process start The last T in the acquisition sampling period Time seconds is recorded STARTOREND For the end time T of the transient event process end ；
The duration of the transient event is recorded as C, c=t end -T start 。
As shown in fig. 2, a transient event recognition system based on a fine slope, comprising:
the system comprises a data acquisition module 201, a preprocessing module 202, a data segmentation module 203, a calculation module 204 and a transient event judgment module 205;
the data acquisition module 201 is used for acquiring working characteristic data of E kinds of electrical equipment under different arrangement and combination operation conditions in a preset period;
the preprocessing module 202 is configured to preprocess the working characteristic data of each permutation and combination;
the data segmentation module 203 is configured to segment the preprocessed working feature data to generate a periodic time period sequence;
the calculating module 204 is configured to calculate a variance of a fine slope value corresponding to each cycle in the cycle time period sequence; calculating a variance ratio and a variance difference of adjacent time periods of each period according to the variance of the fine slope value; calculating a fine slope variance difference threshold and a fine slope variance ratio threshold according to the variance ratio and the variance difference;
the transient event judgment module 205 is configured to perform transient event judgment according to the variance ratio, the variance difference, the fine slope variance difference threshold, and the fine slope variance ratio threshold.
As shown in fig. 3, a fine slope based transient event identification device 30 includes a processor 300 and a memory 301;
the memory 301 is used for storing a program code 302 and transmitting the program code 302 to the processor;
the processor 300 is configured to perform the steps of one embodiment of the fine slope based transient event identification method described above in accordance with instructions in the program code 302.
Illustratively, the computer program 302 may be partitioned into one or more modules/units that are stored in the memory 301 and executed by the processor 300 to complete the present application. The one or more modules/units may be a series of computer program instruction segments capable of performing the specified functions, which instruction segments are used for describing the execution of the computer program 302 in the terminal device 30.
The terminal device 30 may be a computing device such as a desktop computer, a notebook computer, a palm computer, and a cloud server. The terminal device may include, but is not limited to, a processor 300, a memory 301. It will be appreciated by those skilled in the art that fig. 3 is merely an example of the terminal device 30 and is not meant to be limiting as to the terminal device 30, and may include more or fewer components than shown, or may combine certain components, or different components, e.g., the terminal device may also include input and output devices, network access devices, buses, etc.
The processor 300 may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 301 may be an internal storage unit of the terminal device 30, such as a hard disk or a memory of the terminal device 30. The memory 301 may also be an external storage device of the terminal device 30, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the terminal device 30. Further, the memory 301 may also include both an internal storage unit and an external storage device of the terminal device 30. The memory 301 is used for storing the computer program and other programs and data required by the terminal device. The memory 301 may also be used to temporarily store data that has been output or is to be output. It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, which are not repeated herein.
In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied essentially or in part or all of the technical solution or in part in the form of a software product stored in a storage medium, including instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (8)
1. A transient event identification method based on a fine slope, comprising the steps of:
collecting working characteristic data of E kinds of electrical equipment under different arrangement and combination operation conditions in a preset period;
preprocessing the working characteristic data of each permutation and combination;
dividing the preprocessed working characteristic data to generate a periodic time period sequence, wherein the periodic time period sequence comprises the following specific steps of:
dividing the current data sequence and the voltage data sequence by taking the first working characteristic data sampling point as a starting point and taking the working characteristic data sampling point n of one period as a unit to generate a period time period sequence Tn (T) 1 ,T 2 ,…，T Tn ) Wherein Tn represents the total number of cycles;
calculating the variance of the fine slope value corresponding to each period in the period time period sequence, wherein the variance is specifically as follows:
calculating the slope of adjacent pseudo sampling points in each period:
calculating the fine slope corresponding to each period according to the slope of the adjacent pseudo sampling points in each period:
calculating the average value of the fine slope of each period according to the fine slope corresponding to each period;
calculating the variance of the fine slope value according to the average value of the fine slope of each period;
calculating a variance ratio and a variance difference of adjacent time periods of each period according to the variance of the fine slope value;
calculating a fine slope variance difference threshold and a fine slope variance ratio threshold according to the variance ratio and the variance difference;
and judging the transient event according to the variance ratio, the variance difference, the fine slope variance difference threshold and the fine slope variance ratio threshold.
2. The fine slope based transient event identification method of claim 1, wherein the operating characteristic data comprises high frequency current data and high frequency voltage data of a steady state process.
3. The transient event recognition method based on fine slope according to claim 2, wherein the preprocessing process is a wavelet noise reduction process and an interpolation process on the working characteristic data, and the obtained high-frequency current data sequence and high-frequency voltage data sequence are obtained.
4. The transient event identification method based on fine slope according to claim 3, wherein the specific process of transient event judgment is as follows:
statistics of meeting ΔSk in each period time period sequence pjj Less than the fine slope variance difference threshold and Rk pjj The proportion P (l) occupied by the time period smaller than the fine slope variance ratio threshold is judged, and the transient event is judged according to the value of P (l); wherein Rk is pjj And ΔSk pjj And respectively representing the variance ratio and the variance difference characteristics of the jth time period in the high-frequency steady-state current and the high-frequency steady-state voltage data of the p-th permutation and combination.
5. The method for identifying transient event based on fine slope according to claim 4, wherein the specific process of judging transient event according to the value of P (l) is as follows:
setting a minimum threshold p1 and a maximum threshold p2;
if P (l) < P1, then this time period is indicated as being in steady state process;
if P1< P (l) < P2, indicating that the time period is in a transient event early warning process;
if P (l) > P2, this time period is indicated to be in transient.
6. The method of claim 5, wherein the duration of the transient is recorded if the transient is in a transient state.
7. The transient event identification system based on the fine slope is characterized by comprising a data acquisition module, a preprocessing module, a data segmentation module, a calculation module and a transient event judgment module;
the data acquisition module is used for acquiring working characteristic data of E kinds of electrical equipment under different arrangement and combination operation conditions in a preset period;
the preprocessing module is used for preprocessing the working characteristic data of each permutation and combination;
the data segmentation module is used for segmenting the preprocessed working characteristic data to generate a periodic time period sequence, and specifically comprises the following steps:
dividing the current data sequence and the voltage data sequence by taking the first working characteristic data sampling point as a starting point and taking the working characteristic data sampling point n of one period as a unit to generate a period time period sequence Tn (T) 1 ,T 2 ,…，T Tn ) Wherein Tn represents the total number of cycles;
the calculating module is used for calculating the variance of the fine slope value corresponding to each period in the period time period sequence, and specifically comprises the following steps:
calculating the slope of adjacent pseudo sampling points in each period:
calculating the fine slope corresponding to each period according to the slope of the adjacent pseudo sampling points in each period:
calculating the average value of the fine slope of each period according to the fine slope corresponding to each period;
calculating the variance of the fine slope value according to the average value of the fine slope of each period;
calculating a variance ratio and a variance difference of adjacent time periods of each period according to the variance of the fine slope value;
calculating a fine slope variance difference threshold and a fine slope variance ratio threshold according to the variance ratio and the variance difference;
the transient event judgment module is used for judging the transient event according to the variance ratio, the variance difference, the fine slope variance difference threshold and the fine slope variance ratio threshold.
8. A fine slope based transient event identification device, the device comprising a processor and a memory;
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is configured to execute the fine slope based transient event identification method of any of claims 1-6 according to instructions in the program code.
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