CN117890740B

CN117890740B - Partial discharge positioning method, device and equipment for power station cable and storage medium

Info

Publication number: CN117890740B
Application number: CN202410292339.7A
Authority: CN
Inventors: 朱琳; 吴文韬; 麦欣; 张文斌; 贾启彤; 欧来洪; 徐声鸿
Original assignee: Yunnan Power Investment Green Energy Technology Co ltd
Current assignee: Yunnan Power Investment Green Energy Technology Co ltd
Priority date: 2024-03-14
Filing date: 2024-03-14
Publication date: 2024-06-21
Anticipated expiration: 2044-03-14
Also published as: CN117890740A

Abstract

The application discloses a partial discharge positioning method, a device, equipment and a storage medium for a power station cable, which relate to the technical field of electric digital data processing.

Description

Partial discharge positioning method, device and equipment for power station cable and storage medium

Technical Field

The application relates to the technical field of electric digital data processing, in particular to a partial discharge positioning method, device and equipment for a power station cable and a storage medium.

Background

The power cable is used as an important transmission medium of the power station and plays a key role in the aspects of power station production, power transmission and the like. The power cable is a cable for transmitting and distributing electric energy, and is commonly used for urban underground power grids, power station outgoing lines, power supply in industrial and mining enterprises and power transmission lines under sea water passing through the river. In the electric power line, the proportion of the cable is gradually increasing. Power cables are cable products used in the main line of power systems to transmit and distribute high power electrical energy, including various voltage classes of 1kV to 500kV and above, various insulated power cables.

Because the number of the cables of the power station is huge, the environments of the cables are different, such as overhead, buried, multi-bending and the like, the cables have defects in long-term use or delivery, such as bubbles in liquid medium, solid pores, severely distorted space electric fields and the like, so that partial discharge of the cables easily occurs in the use process, and if the partial discharge of the cable cannot be detected in time, high-energy charged particles at the partial discharge defect position of the cable terminal and insulators or insulating oil are mutually influenced, and finally insulating materials can be ignited, so that potential safety hazards are caused.

At present, the partial discharge position of the cable is usually positioned by a sound measurement method, a step voltage method, an acousto-magnetic synchronization method and the like, and the problems of poor anti-interference capability, limitation and large positioning precision error of the method exist. The sound detection method needs to collect the sound current excited by the discharge arc, has noise, shielding and the like to the surrounding environment, and is easy to cause inaccurate sound capture or even failure in capturing the sound, thereby causing missed detection; the step voltage method is not suitable for the scene (such as buried, pipelines and the like) which cannot be directly contacted with the cable, and the step voltage method is easy to be interfered by the outside in the process of signal generation and transmission, so that the measurement result is easy to be obviously influenced; the acousto-magnetic synchronous method is similar to the acoustic measurement method, and the acousto-magnetic synchronous method requires a worker to subjectively listen to discharge sound, so that experience of the worker and sensitivity of distinguishing the sound become keys for finding out fault points, subjective factors have large influence, and positioning results are inaccurate or cannot be positioned.

Disclosure of Invention

The application mainly aims to provide a partial discharge positioning method, device and equipment for a power station cable and a storage medium, so as to solve the problems of poor anti-interference capability, limitation and large positioning precision error of the method in the prior art.

In order to achieve the above object, the present application provides the following technical solutions:

A partial discharge positioning method of a power station cable, the power station cable being applied to a plurality of cables of the same power station, the partial discharge positioning method comprising:

step S1, current signals of each cable in the power station in a preset time period are respectively obtained;

Step S2, respectively extracting a plurality of signal components of each current signal based on empirical mode decomposition;

Step S3, classifying all signal components based on the same cable through a Bayesian classification algorithm to obtain at least two signal characteristics;

S4, deleting the same signal characteristics among all cables, and marking the reserved signal characteristics as abnormal characteristics;

Step S5, marking the cable with the abnormal characteristics as an abnormal cable;

step S6, randomly defining at least two signal acquisition points on the abnormal cable, and acquiring at least one amplitude difference of the abnormal characteristics by combining all the signal acquisition points in pairs;

s7, positioning one theoretical discharge point of the abnormal cable according to each amplitude difference, and obtaining the minimum enclosing sphere of all theoretical discharge points;

s8, acquiring thermal imaging data of the minimum bounding sphere through a preset strategy;

Step S9, acquiring the thermal imaging data based on a highlight region of an abnormal cable, and defining the highlight region as an actual discharge point of the abnormal cable.

As a further improvement of the application, step S2, extracting several signal components of each current signal based on empirical mode decomposition, respectively, comprises:

step S21, obtaining all maximum values and all minimum values of the current signal;

Step S22, all maximum values are sequentially connected to form an upper envelope line based on the current signal, and all minimum values are sequentially connected to form a lower envelope line;

Step S23, obtaining the average value of the upper envelope curve and the lower envelope curve based on the current signal to form a mean value envelope curve;

Step S24, subtracting the mean envelope curve from the current signal to obtain a first-order intermediate signal;

step S25, repeating the steps S21 to S24 to iterate the first-order intermediate signal;

Step S26, respectively obtaining first-order intermediate signals with the difference value of 0 or 1 between the number of extreme points and the number of zero crossing points after each iteration, and marking the first-order intermediate signals as second-order intermediate signals;

Step S27, a second-order intermediate signal with a mean envelope of zero is obtained and defined as the signal component.

As a further improvement of the present application, step S3, classifying all signal components based on the same cable by a bayesian classification algorithm, respectively, to obtain at least two signal features, including:

step S31, defining the signal set to be classified according to all the signal components based on the same cable Wherein/>For the signal set/>/>Signal component/>The number of all signal components of the same cable;

step S32, defining a category set according to the preset signal type Wherein/>For the category set/>/>A plurality of preset signal types;

step S33, calculating the signal set to be classified according to the formula (1) Conditional probability at each preset signal type:

（1）；

Wherein, To at/>Under a preset signal type, the signal set to be classified/>Conditional probability of (2); for/> Edge probabilities of the preset signal types; /(I)To at/>Under a preset signal type, the first/>Conditional probabilities of the individual signal components;

Step S34, classifying each signal component into a preset signal type with the highest conditional probability;

in step S35, the preset signal types without signal components are deleted, and the reserved preset signal types are respectively marked as a signal feature.

As a further improvement of the present application, step S6, randomly defining at least two signal acquisition points on the abnormal cable, and acquiring at least one amplitude difference of the abnormal feature by combining all the signal acquisition points in pairs, includes:

Step S61, obtaining the total length of the abnormal cable;

step S62, the passing interval is Randomly generating at least two random numbers by a random function of (a);

step S63, multiplying the current random number by the total length to obtain a random length, namely a random point position corresponding to the current random number on the abnormal cable, wherein one end of the random length is overlapped with one end of the abnormal cable;

step S64, defining each random point location as a signal acquisition point location;

step S65, combining all signal acquisition points two by means of the combination number C of the permutation and combination, so as to acquire at least one amplitude difference of the abnormal feature.

As a further improvement of the present application, step S7 of locating one theoretical discharge point of the abnormal cable according to each amplitude difference and obtaining the minimum bounding sphere of all theoretical discharge points includes:

step S71, judging whether there is a zero amplitude difference;

step S72, if the amplitude difference is zero, two signal acquisition points corresponding to the amplitude difference of zero are acquired and marked as equidistant propagation points;

Step S73, obtaining the shortest connecting line of two equidistant propagation points, and obtaining the central line of the shortest connecting line;

and step S74, obtaining the intersection point of the neutral line and the abnormal cable as the theoretical discharge point.

As a further improvement of the present application, step S71, judges whether there is a zero amplitude difference, and then includes:

step S75, if no amplitude difference is zero, obtaining the minimum value of all amplitude differences;

step S76, two signal acquisition points corresponding to the minimum value are acquired and marked as close-range propagation points;

Step 77, iterating and updating the two close-range propagation points through a global optimizing algorithm to enable the minimum value to be zero;

And step S78, defining two points with the minimum value of zero after iteration is completed as the equidistant propagation points.

As a further improvement of the present application, step S77, iterating and updating the two near-distance propagation points to make the minimum value zero by using a global optimizing algorithm, includes:

Step S771, assigning a plurality of random solutions to the two close-range propagation points according to the formula (2), and defining the calculation result of all the random solutions as zero;

（2）；

Wherein, For the set of all random solutions,/>For each of the random solutions separately,For/>Labels of individual random solutions,/>The number of all random solutions; /(I)For the set of velocities for all the random solutions,The speed of each random solution;

Step S772, initializing the position of each random solution, and updating the position and the speed of each random solution according to equation (3) based on the same random solution:

（3）；

Wherein, For/>The random solution is at the/>The speed of the steps; /(I)To be at the/>Step/>A random solution; for/> The random solution is at the/>Speed inertia of step,/>Is the coefficient of inertia of the material,For/>Self-cognition characterization of individual random solutions,/>For/>Social cognitive characterization of individual random solutions; /(I)And/>Are learning factors,/>For/>Random number of value range,/>For/>Individual optimal solution obtained by random solution,/>Global optimal solutions obtained for all random solutions;

step S773, iterating all the random solutions according to the formula (3) to update each And said/>；

Step S774, judging eachCompared with the previous iteration, if the difference value is less than or equal to the first preset adaptation threshold value, if each/>Comparing with the previous iteration, if the difference values are smaller than or equal to the first preset adaptive threshold value, executing step S775;

Step S775, judging the Comparing whether the difference value of the previous iteration is smaller than or equal to a second preset adaptation threshold value, if soComparing with the difference value of the previous iteration being smaller than or equal to the second preset adaptation threshold value, executing step S776;

in step S776, it is determined that the iteration is completed.

In order to achieve the above purpose, the present application further provides the following technical solutions:

A partial discharge positioning device of a power station cable, the partial discharge positioning device of the power station cable being applied to the partial discharge positioning method of the power station cable, the partial discharge positioning device comprising:

The current signal acquisition module is used for respectively acquiring current signals of each cable in the power station in a preset time period;

The signal component extraction module is used for respectively extracting a plurality of signal components of each current signal based on empirical mode decomposition;

The signal component classification module is used for respectively classifying all signal components based on the same cable through a Bayesian classification algorithm to obtain at least two signal characteristics;

The abnormal feature acquisition and marking module is used for deleting the same signal features among all the cables and marking the reserved signal features as abnormal features;

an abnormal cable marking module for marking a cable having the abnormal characteristics as an abnormal cable;

the abnormal characteristic amplitude difference acquisition module is used for randomly defining at least two signal acquisition points on the abnormal cable and acquiring at least one amplitude difference of the abnormal characteristic by combining all the signal acquisition points;

The minimum bounding sphere acquisition module is used for positioning one theoretical discharge point of the abnormal cable according to each amplitude difference and acquiring the minimum bounding spheres of all the theoretical discharge points;

The thermal imaging data acquisition module is used for acquiring thermal imaging data of the minimum bounding sphere through a preset strategy;

And the actual discharge point definition module is used for acquiring the thermal imaging data based on the highlight area of the abnormal cable and defining the highlight area as the actual discharge point of the abnormal cable.

An electronic device comprising a processor, a memory coupled to the processor, the memory storing program instructions executable by the processor; and when the processor executes the program instructions stored in the memory, the partial discharge positioning method of the power station cable is realized.

a storage medium having stored therein program instructions which, when executed by a processor, implement a method of enabling a partial discharge positioning of a power plant cable as described above.

The application respectively acquires the current signal of each cable in the power station in a preset time period; respectively extracting a plurality of signal components of each current signal based on empirical mode decomposition; classifying all signal components through a Bayesian classification algorithm based on the same cable to obtain at least two signal characteristics; deleting the same signal characteristics among all cables, and marking the reserved signal characteristics as abnormal characteristics; marking a cable with an abnormal characteristic as an abnormal cable; randomly defining at least two signal acquisition points on the abnormal cable, and combining the signal acquisition points in pairs through all the signal acquisition points to acquire at least one amplitude difference of the abnormal characteristics; positioning one theoretical discharge point of the abnormal cable according to each amplitude difference, and acquiring the minimum enclosing sphere of all the theoretical discharge points; acquiring thermal imaging data of the minimum bounding sphere through a preset strategy; the acquisition of the thermal imaging data is based on a highlight region of the abnormal cable and defines the highlight region as an actual discharge point of the abnormal cable. According to the application, all cables of the power station are used as comparison references, and the same signal characteristics (such as normal current signals, integral power grid fluctuation caused by randomness of photovoltaic and wind power and the like) are deleted, so that the signals which are not of the same type and are reserved are identified as abnormal characteristics (such as bubbles in a liquid medium, solid pores, defects of severely distorted space electric fields and the like), compared with current signal acquisition and positioning of a single cable, other cables of the same power station are used as comparison groups, the probability of fault misjudgment is reduced, meanwhile, the signal acquisition points are randomly defined, the amplitude difference is acquired pairwise, and the partial discharge points are acquired through a plurality of groups of signal acquisition points, and compared with single detection, the error can be further reduced and the positioning precision is improved through multiple acquisition of the application.

Drawings

FIG. 1 is a schematic flow chart of steps of an embodiment of a method for positioning partial discharge of a power station cable according to the present application;

FIG. 2 is a schematic diagram of functional modules of an embodiment of a partial discharge positioning device for a power station cable of the present application;

FIG. 3 is a schematic diagram of an embodiment of an electronic device of the present application;

FIG. 4 is a schematic diagram illustrating the structure of an embodiment of a storage medium according to the present application.

Detailed Description

The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.

The terms "first," "second," "third," and the like in this disclosure are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "first," "second," and "third" may explicitly or implicitly include at least one such feature. In the description of the present application, the meaning of "plurality" means at least two, for example, two, three, etc., unless specifically defined otherwise. All directional indications (such as up, down, left, right, front, back … …) in the embodiments of the present application are merely used to explain the relative positional relationship, movement, etc. between the components in a particular gesture (as shown in the drawings), and if the particular gesture changes, the directional indication changes accordingly. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those listed steps or elements but may include other steps or elements not listed or inherent to such process, method, article, or apparatus.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the application. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.

As shown in fig. 1, the present embodiment provides an embodiment of a partial discharge positioning method of a power station cable, the power station cable being applied to a plurality of cables of the same power station, the partial discharge positioning method including the steps of:

Step S1, current signals of each cable in the power station in a preset time period are respectively obtained.

Preferably, in the practical application process, due to wind power and photoelectric randomness or defects of the cable (such as bubbles in a liquid medium, solid pores, space electric field defects with serious distortion and the like), the current signal of the cable is unstable or is missing to different degrees, so that the collected current signal can be subjected to initial pretreatment before the current signal of the cable is positioned.

Specifically, the pretreatment can be performed by removing trend terms and a five-point three-time smoothing method.

The trending term is current signal data acquired in a current test, and due to zero drift generated by an amplifier along with temperature change, instability of low-frequency performance outside a frequency range of a sensor, environmental interference around the sensor and the like, a base line is often deviated, and even the size of the deviation from the base line also changes with time. The entire process of changing over time from baseline is called the trend term of the signal. Trend terms directly affect the correctness of the signal, which should be removed. A common method of eliminating trend terms is the polynomial least squares method.

Preferably, a detrend () function can be provided in MATLAB to perform the detrending operation, but only the mean and linear trend terms can be removed, so if the function is used to perform the operation, it is acknowledged that the trend terms contained in the sensor are linear. If the trend term is considered nonlinear, it needs to be operated with a function of polyfit () and ployval () (e.g., liu_ detrend (t, y, m)). In the actual current signal data processing, polynomial trend term elimination processing is generally performed on the sampled data by taking 1 to 3 degree polynomials.

Wherein a five-point cubic smoothing method can be used as the time-domain and frequency-domain signal smoothing process. The processing method has the effect on time domain data mainly of reducing high-frequency random noise mixed into current signals. The function of the frequency domain data is to make the spectrum curve smooth so as to obtain a better fitting effect in the mode parameter identification. It should be noted that, the frequency domain data is subjected to the five-point three-time smoothing method, so that the peak value in the spectrum curve is reduced, the body shape is widened, and the error of the identification parameter may be increased.

And S2, respectively extracting a plurality of signal components of each current signal based on empirical mode decomposition.

Preferably, the empirical mode decomposition (EMPIRICAL MODE DECOMPOSITION, EMD) algorithm is an empirical mode decomposition EMD that is based on the concept of an instantaneous frequency, eigenmode function (INTRINSIC MODE FUNCTION, IMF) that is capable of decomposing a complex signal into several IMF components, each IMF characterizing a local feature of the signal. The signal decomposition is performed according to the time scale characteristics of the data, and any basis function is not required to be preset, so that the method has self-adaption. The advantage of empirical mode decomposition is that no well defined function is used as a basis, but rather the natural mode function is adaptively generated from the analyzed signal. The method can be used for analyzing nonlinear and non-stable signal sequences, and has high signal-to-noise ratio and good time-frequency focusing property. The design of the present embodiment aims to accurately decompose the current signal by an empirical mode decomposition algorithm to distinguish between a normal current signal and an abnormal current signal.

And step S3, classifying all the signal components based on the same cable through a Bayesian classification algorithm to obtain at least two signal characteristics.

Preferably, the Bayesian classification is an irregular classification method, and the Bayesian classification technology learns to generalize a classification function (prediction of discrete variables is called classification, and classification of continuous variables is called regression) by training a classified sample subset, and the classification of unclassified data is realized by using a classifier obtained by training. Among different classification algorithms, naive Bayes classification algorithm (Naive Bayes) is a simple Bayes classification algorithm, and the application effect of the Naive Bayes classification algorithm is better than that of neural network classification algorithm and decision tree classification algorithm, especially when the data volume to be classified is very large, the Bayes classification method has high accuracy compared with other classification algorithms, and the Naive Bayes classification algorithm is preferred in the embodiment, but the design intention of the neural network classification algorithm is high accuracy.

Preferably, the signal features are largely divided into three time domain features: short-time energy, zero crossing rate and experience permutation entropy; six frequency domain features: spectrum centroid, spectrum spread, spectrum entropy, spectrum flux, spectrum roll-off point, mel-frequency cepstral coefficient.

Preferably, in this embodiment, one or two of the above features are preferable, and if the features are selected too much, the calculation amount tends to be increased suddenly, and the computer is likely to be blocked or unresponsive in the actual application process.

Preferably, the embodiment can reduce the detection difficulty by one or two of short-time energy, zero-crossing rate, spectrum center of gravity and spectrum flux.

And S4, deleting the same signal characteristics among all the cables, and marking the reserved signal characteristics as abnormal characteristics.

Preferably, the signal features may select one-dimensional features, such as phase features, polarity features, amplitude features, time-frequency features, wavelet packet features.

Preferably, the signal features may be directly obtained through a PRPD spectrogram, and the PRPD spectrogram is a mature prior art, and specific extraction of the one-dimensional features is also a prior art, which is not described in detail in this embodiment.

And S5, marking the cable with the abnormal characteristics as an abnormal cable.

And S6, randomly defining at least two signal acquisition points on the abnormal cable, and combining the signal acquisition points in pairs through all the signal acquisition points to acquire at least one amplitude difference of the abnormal characteristics.

And S7, positioning one theoretical discharge point of the abnormal cable according to each amplitude difference, and obtaining the minimum enclosing sphere of all the theoretical discharge points.

Preferably, the minimum bounding sphere is obtained, after all theoretical discharge points are obtained, two theoretical discharge points with the farthest mutual distance are obtained in all theoretical discharge points and used as two ends of the diameter of the minimum bounding sphere, and the generated sphere is the minimum bounding sphere.

And S8, acquiring thermal imaging data of the minimum bounding sphere through a preset strategy.

Preferably, the image of the minimum bounding sphere region can be subjected to graying and background suppression processing by adopting a thermal radiation acquisition mode such as infrared imaging, ultrasonic infrared thermal imaging and the like to obtain a highlight region, and the partial discharge defect part of the cable terminal is defined through the highlight region.

In step S9, the thermal imaging data is acquired based on the highlight region of the abnormal cable, and the highlight region is defined as the actual discharge point of the abnormal cable.

Further, step S2, extracting a plurality of signal components of each current signal based on empirical mode decomposition, specifically includes the following steps:

step S21, all maximum values and all minimum values of the current signal are obtained.

Step S22, all maxima are connected in sequence to form an upper envelope and all minima are connected in sequence to form a lower envelope based on the current signal.

Step S23, the average value of the upper envelope curve and the lower envelope curve is obtained based on the current signal, and a mean value envelope curve is formed.

Step S24, subtracting the mean envelope curve from the current signal to obtain a first-order intermediate signal.

step S26, respectively obtaining first-order intermediate signals with the difference value of 0 or 1 between the number of extreme points and the number of zero crossing points after each iteration, and marking the first-order intermediate signals as second-order intermediate signals.

In step S27, a second-order intermediate signal with a mean envelope of zero is obtained and defined as a signal component.

Preferably, the signal component is an connotation mode component (INTRINSIC MODE FUNCTIONS, IMF) which is a signal component of each layer obtained after the original signal is decomposed by EMD.

Further, step S3, classifying all signal components based on the same cable by a bayesian classification algorithm, to obtain at least two signal features, including:

step S31, defining the signal set to be classified according to all the signal components based on the same cable Wherein/>For the signal set to be classified/>/>Signal component/>Is the number of all signal components of the same cable.

Step S32, defining a category set according to the preset signal typeWherein/>For category set/>/>The signal type is preset.

Step S33, calculating the signal set to be classified according to the formula (1)Conditional probability at each preset signal type:

（1）。

Wherein, To at/>Under the preset signal types, the signal set to be classified/>Conditional probability of (2); for/> Edge probabilities of the preset signal types; /(I)To at/>Under a preset signal type, the first/>Conditional probability of the individual signal components.

Step S34, each signal component is classified into the preset signal type with the highest conditional probability.

Preferably, the preset signal type can be set according to the main and mainstream fault type, for example, bubbles, solid pores and severely distorted space electric fields in the liquid medium, and specifically include defects such as insulation defect, solid conductive powder, liquid conductivity, bubbles, pores and stress cone displacement; or by the discharge type, such as tip discharge, particle discharge, air gap discharge, floating discharge, creeping discharge, etc.

It should be noted that, in the prior art, the above features have a clear distinguishing method, and each type also has a clear signal feature, which is different from each other, and the clear signal feature can be used as a classification basis. The specific signal characteristics of each type can be directly obtained from the prior art, and this embodiment will not be described in detail.

Preferably, in the actual calculation process, the duty ratio of the signal component generated by the normal current signal is the highest, and after deleting the signal component generated by the normal current signal, the number of the remaining signal components and the number of the corresponding preset signal types are greatly reduced, so that the effect effectively reduces the calculation force burden of the overall calculation.

Further, step S6, randomly defining at least two signal acquisition points on the abnormal cable, and obtaining at least one amplitude difference of the abnormal feature by combining all the signal acquisition points in pairs, includes:

Step S61, the total length of the abnormal cable is acquired.

Step S62, the passing interval isAt least two random numbers are randomly generated by a random function of (a).

Preferably, the number of random numbers can be set according to the cable length, for example, it can be ensured that there is on average one random point every 5 meters or every 10 meters, i.e. a 500m long cable for example requires 50 to 100 random numbers. Meanwhile, the decimal point post-digit of the random number is generally set to be two digits.

Step S63, the current random number is multiplied by the total length, and the obtained random length is the random point position of the current random number corresponding to the abnormal cable, and one end of the random length coincides with one end of the abnormal cable.

Preferably, for example, if a certain random number is 0.35, and a cable with the same length of 500m is adopted, 500×0.35 obtains 175m, and from one end of the cable, the running 175m is the random point position corresponding to the random number.

In step S64, each random point location is defined as a signal acquisition point location.

Step S65, combining all signal acquisition points two by two through the combination number C of the permutation and combination to acquire at least one amplitude difference of the abnormal characteristic.

Preferably, the total number of random numbers is set asObtaining/>, based on the number of combinations C of the permutation and combination。

Further, step S7, locating a theoretical discharge point of the abnormal cable according to each amplitude difference, and obtaining a minimum bounding sphere of all theoretical discharge points, includes:

Step S71, determining whether there is a zero amplitude difference.

In step S72, if there is a zero amplitude difference, two signal acquisition points corresponding to the zero amplitude difference are acquired and marked as equidistant propagation points.

Step S73, the shortest connecting line of two equidistant propagation points is obtained, and the central line of the shortest connecting line is obtained.

And S74, acquiring an intersection point of the neutral line and the abnormal cable as a theoretical discharge point.

Further, step S71, determining whether there is a zero amplitude difference, then includes:

In step S75, if there is no amplitude difference of zero, the minimum value of all the amplitude differences is obtained.

Step S76, two signal acquisition points corresponding to the minimum value are acquired and marked as close-range propagation points.

And S77, iterating and updating the two close-range propagation points through a global optimizing algorithm to enable the minimum value to be zero.

In step S78, two points with zero minimum value after the iteration is completed are defined as equidistant propagation points.

Further, step S77, iterating and updating the two close-range propagation points to make the minimum value zero by the global optimizing algorithm, includes:

step S771, a plurality of random solutions are given to the two close-range propagation points according to the formula (2), and the calculation result of all the random solutions is defined as zero.

（2）。

Wherein,For the set of all random solutions,/>For each of the random solutions separately,For/>Labels of individual random solutions,/>The number of all random solutions; /(I)For the set of velocities for all the random solutions,The velocity of each random solution is separate.

（3）。

Wherein, For/>The random solution is at the/>The speed of the steps; /(I)To be at the/>Step/>A random solution; for/> The random solution is at the/>Speed inertia of step,/>Is the coefficient of inertia of the material,For/>Self-cognition characterization of individual random solutions,/>For/>Social cognitive characterization of individual random solutions; /(I)And/>Are learning factors,/>For/>Random number of value range,/>For/>Individual optimal solution obtained by random solution,/>And the obtained global optimal solution is used for all random solutions.

Preferably, the method comprises the steps of,The value of (2) is in the range of [0,0.5], preferably 0.4; /(I)The value of (2) is in the range of [0.5,1], preferably 0.8.

Step S773, iterating all the random solutions according to equation (3) to update each/>。

Step S774, judging eachCompared with the previous iteration, if the difference value is less than or equal to the first preset adaptation threshold value, if each/>Compared with the difference value of the previous iteration being smaller than or equal to the first preset adaptive threshold value, step S775 is executed.

Step S775, judgingCompared with the previous iteration, if the difference value is smaller than or equal to the second preset adaptation threshold value, if/>Step S776 is performed when the difference value from the previous iteration is less than or equal to the second preset adaptation threshold.

In step S776, it is determined that the iteration is completed.

The method comprises the steps of respectively obtaining current signals of each cable in a power station in a preset time period; respectively extracting a plurality of signal components of each current signal based on empirical mode decomposition; classifying all signal components through a Bayesian classification algorithm based on the same cable to obtain at least two signal characteristics; deleting the same signal characteristics among all cables, and marking the reserved signal characteristics as abnormal characteristics; marking a cable with an abnormal characteristic as an abnormal cable; randomly defining at least two signal acquisition points on the abnormal cable, and combining the signal acquisition points in pairs through all the signal acquisition points to acquire at least one amplitude difference of the abnormal characteristics; positioning one theoretical discharge point of the abnormal cable according to each amplitude difference, and acquiring the minimum enclosing sphere of all the theoretical discharge points; acquiring thermal imaging data of the minimum bounding sphere through a preset strategy; the acquisition of the thermal imaging data is based on a highlight region of the abnormal cable and defines the highlight region as an actual discharge point of the abnormal cable. According to the embodiment, all cables of the power station are used as reference, the same signal characteristics (such as normal current signals, integral power grid fluctuation caused by randomness of photovoltaic and wind power and the like) are deleted, so that the signals which are not of the same type and are recognized as abnormal characteristics (such as bubbles in a liquid medium, solid pores, defects of a severely distorted space electric field and the like) are reserved.

As shown in fig. 2, the present embodiment provides an embodiment of a partial discharge positioning device of a power station cable, which is applied to the partial discharge positioning method in the above embodiment, and includes a current signal acquisition module 1, a signal component extraction module 2, a signal component classification module 3, an abnormal feature acquisition and marking module 4, an abnormal cable marking module 5, an abnormal feature amplitude difference acquisition module 6, a minimum bounding sphere acquisition module 7, a thermal imaging data acquisition module 8, and an actual discharge point definition module 9, which are electrically connected in this order.

The current signal acquisition module 1 is used for respectively acquiring current signals of each cable in the power station in a preset time period; the signal component extraction module 2 is used for respectively extracting a plurality of signal components of each current signal based on empirical mode decomposition; the signal component classification module 3 is used for classifying all signal components based on the same cable through a Bayesian classification algorithm to obtain at least two signal characteristics; the abnormal feature acquisition and marking module 4 is used for deleting the same signal features among all cables and marking the reserved signal features as abnormal features; the abnormal cable marking module 5 is used for marking the cable with abnormal characteristics as an abnormal cable; the abnormal characteristic amplitude difference acquisition module 6 is used for randomly defining at least two signal acquisition points on the abnormal cable, and acquiring at least one amplitude difference of the abnormal characteristic by combining all the signal acquisition points; the minimum bounding sphere acquisition module 7 is used for positioning one theoretical discharge point of the abnormal cable according to each amplitude difference and acquiring the minimum bounding spheres of all the theoretical discharge points; the thermal imaging data acquisition module 8 is used for acquiring thermal imaging data of the minimum bounding sphere through a preset strategy; the actual discharge point definition module 9 is configured to acquire thermal imaging data based on a highlight region of the abnormal cable, and define the highlight region as an actual discharge point of the abnormal cable.

Further, the signal component extraction module comprises a first signal component extraction sub-module, a second signal component extraction sub-module, a third signal component extraction sub-module, a fourth signal component extraction sub-module, a fifth signal component extraction sub-module, a sixth signal component extraction sub-module and a seventh signal component extraction sub-module which are electrically connected in sequence; the first signal component extraction submodule is electrically connected with the current signal acquisition module, and the seventh signal component extraction submodule is electrically connected with the signal component classification module.

The first signal component extraction submodule is used for acquiring all maximum values and all minimum values of the current signal; the second signal component extraction submodule is used for sequentially connecting all maximum values to form an upper envelope line and sequentially connecting all minimum values to form a lower envelope line based on the current signal; the third signal component extraction submodule is used for obtaining the average value of the upper envelope curve and the lower envelope curve based on the current signal to form a mean value envelope curve; the fourth signal component extraction submodule is used for subtracting the mean envelope curve from the current signal to obtain a first-order intermediate signal; the fifth signal component extraction submodule is used for repeatedly executing the first signal component extraction submodule to the fourth signal component extraction submodule so as to iterate the first-order intermediate signal; the sixth signal component extraction submodule is used for respectively obtaining first-order intermediate signals with the difference value of 0 or 1 between the number of extreme points and the number of zero crossing points after each iteration, and marking the first-order intermediate signals as second-order intermediate signals; the seventh signal component extraction sub-module is used for obtaining a second-order intermediate signal with the mean envelope of zero and defining the second-order intermediate signal as a signal component.

Further, the signal component classifying module comprises a first signal component classifying sub-module, a second signal component classifying sub-module, a third signal component classifying sub-module, a fourth signal component classifying sub-module and a fifth signal component classifying sub-module which are electrically connected in sequence; the first signal component classifying sub-module is electrically connected with the seventh signal component extracting sub-module, and the fifth signal component classifying sub-module is electrically connected with the abnormal feature acquiring and marking module.

Wherein the first signal component classifying sub-module is used for defining a signal set to be classified according to all signal components based on the same cableWherein/>For the signal set to be classified/>/>Signal component/>Is the number of all signal components of the same cable.

The second signal component classification submodule is used for defining a class set according to the preset signal typeWherein/>For category set/>/>The signal type is preset.

The third signal component classifying sub-module is used for calculating a signal set to be classified according to the formula (1)Conditional probability at each preset signal type:

（1）。

The fourth signal component classifying sub-module is used for classifying each signal component into a preset signal type with highest respective conditional probability.

The fifth signal component classifying submodule is used for deleting preset signal types without signal components and marking the reserved preset signal types as signal characteristics respectively.

Further, the abnormal characteristic amplitude value difference acquisition module comprises a first abnormal characteristic amplitude value difference acquisition sub-module, a second abnormal characteristic amplitude value difference acquisition sub-module, a third abnormal characteristic amplitude value difference acquisition sub-module, a fourth abnormal characteristic amplitude value difference acquisition sub-module and a fifth abnormal characteristic amplitude value difference acquisition sub-module which are electrically connected in sequence; the first abnormal characteristic amplitude difference acquisition sub-module is electrically connected with the abnormal cable marking module, and the fifth abnormal characteristic amplitude difference acquisition sub-module is electrically connected with the minimum bounding sphere acquisition module.

The first abnormal characteristic amplitude value difference acquisition sub-module is used for acquiring the total length of the abnormal cable; the second abnormal characteristic amplitude difference acquisition submodule is used for acquiring the passing interval asRandomly generating at least two random numbers by a random function of (a); the third abnormal characteristic amplitude value difference obtaining sub-module is used for multiplying the current random number by the total length, and the obtained random length is the random point position of the current random number corresponding to the abnormal cable, and one end of the random length coincides with one end of the abnormal cable; the fourth abnormal characteristic amplitude difference acquisition sub-module is used for respectively defining each random point position as a signal acquisition point position; the fifth abnormal characteristic amplitude difference obtaining sub-module is used for combining all signal obtaining points in pairs through the combination number C of permutation and combination to obtain at least one amplitude difference of the abnormal characteristic.

Further, the minimum bounding sphere acquisition module comprises a first minimum bounding sphere acquisition sub-module, a second minimum bounding sphere acquisition sub-module, a third minimum bounding sphere acquisition sub-module and a fourth minimum bounding sphere acquisition sub-module which are electrically connected in sequence; the first minimum bounding sphere acquisition sub-module is electrically connected with the fifth abnormal characteristic amplitude difference acquisition sub-module, and the fourth minimum bounding sphere acquisition sub-module is electrically connected with the thermal imaging data acquisition module.

The first minimum bounding sphere acquisition sub-module is used for judging whether an amplitude difference of zero exists or not; the second minimum bounding sphere acquisition submodule is used for acquiring two signal acquisition points corresponding to the zero amplitude difference and marking the two signal acquisition points as equidistant propagation points if the amplitude difference is zero; the third minimum bounding sphere acquisition submodule is used for acquiring the shortest connecting line of two equidistant propagation points and acquiring the central line of the shortest connecting line; and the fourth minimum bounding sphere acquisition submodule is used for acquiring the intersection point of the neutral line and the abnormal cable as a theoretical discharge point.

Further, the minimum bounding sphere acquisition module further comprises a fifth minimum bounding sphere acquisition sub-module, a sixth minimum bounding sphere acquisition sub-module, a seventh minimum bounding sphere acquisition sub-module and an eighth minimum bounding sphere acquisition sub-module which are electrically connected in sequence; the fifth minimum bounding sphere acquisition sub-module is electrically connected with the first minimum bounding sphere acquisition sub-module, and the eighth minimum bounding sphere acquisition sub-module is electrically connected with the thermal imaging data acquisition module.

The fifth minimum bounding sphere acquisition submodule is used for acquiring the minimum value of all amplitude differences if the amplitude difference is zero; the sixth minimum bounding sphere acquisition submodule is used for acquiring two signal acquisition points corresponding to the minimum value and marking the two signal acquisition points as close-range propagation points; the seventh minimum bounding sphere acquisition sub-module is used for iterating and updating the points of the two close-range propagation points on the abnormal cable through a global optimizing algorithm so as to enable the minimum value to be zero; the eighth minimum bounding sphere acquisition submodule is used for defining two points with zero minimum value after iteration is completed as equidistant propagation points.

Further, the seventh minimum bounding sphere acquisition submodule comprises a first minimum bounding sphere acquisition unit, a second minimum bounding sphere acquisition unit, a third minimum bounding sphere acquisition unit, a fourth minimum bounding sphere acquisition unit, a fifth minimum bounding sphere acquisition unit and a sixth minimum bounding sphere acquisition unit which are electrically connected in sequence; the first minimum surrounding sphere acquisition unit is electrically connected with the sixth minimum surrounding sphere acquisition submodule, and the sixth minimum surrounding sphere acquisition unit is electrically connected with the eighth minimum surrounding sphere acquisition submodule.

The first minimum bounding sphere acquisition unit is used for giving a plurality of random solutions to the two close-range propagation points according to the formula (2), and defining the calculation result of all the random solutions as zero minimum value.

（2）。

The second minimum bounding sphere acquisition unit is used for initializing the position of each random solution and updating the position and the speed of each random solution according to the formula (3) based on the same random solution:

（3）。

A third minimum bounding sphere acquisition unit for iterating all random solutions according to equation (3) to update each/>。

A fourth minimum bounding sphere acquisition unit for judging eachWhether the difference value compared with the previous iteration is smaller than or equal to a first preset adaptation threshold value.

A fifth minimum bounding sphere acquisition unit for each ofCompared with the previous iteration, the difference value is smaller than or equal to the first preset adaptation threshold value, and the/> isjudgedWhether the difference value compared with the previous iteration is smaller than or equal to a second preset adaptation threshold value.

The sixth minimum bounding sphere acquisition unit is used for ifAnd compared with the previous iteration, if the difference value is smaller than or equal to the second preset adaptation threshold value, judging that the iteration is completed.

It should be noted that, the present embodiment is a functional module embodiment based on the foregoing method embodiment, and additional contents such as preference, expansion, illustration, and principle description of the present embodiment may be referred to the foregoing embodiment, which is not repeated herein.

As shown in fig. 3, the present embodiment provides an embodiment of an electronic device, in which the electronic device 10 includes a processor 101 and a memory 102 coupled to the processor 101.

The memory 102 stores program instructions for implementing the partial discharge positioning method of the power plant cable of any of the embodiments described above.

The processor 101 is configured to execute program instructions stored in the memory 102 for performing a partial discharge positioning of the power plant cable.

The processor 101 may also be referred to as a CPU (Central Processing Unit ). The processor 101 may be an integrated circuit chip having data processing capabilities. Processor 101 may also be a general purpose processor, a digital data processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

Further, fig. 4 is a schematic structural diagram of a storage medium according to an embodiment of the present application, where the storage medium 11 according to an embodiment of the present application stores program instructions 111 capable of implementing all the methods described above, where the program instructions 111 may be stored in the storage medium in the form of a software product, and include several instructions for making a computer device (which may be a personal computer, a server, or a network device) or a processor (processor) execute all or part of the steps of the methods described in the embodiments of the present application. 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, an optical disk, or other various media capable of storing program codes, or a terminal device such as a computer, a server, a mobile phone, a tablet, or the like.

In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of elements is merely a logical functional division, and there may be additional divisions of actual implementation, e.g., multiple elements 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 forms.

In addition, each functional unit in the embodiments of the present application 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 foregoing is only the embodiments of the present application, and the patent scope of the application is not limited thereto, but is also covered by the patent protection scope of the application, as long as the equivalent structure or equivalent flow changes made by the description and the drawings of the application or the direct or indirect application in other related technical fields are adopted.

The embodiments of the present application have been described in detail above, but they are merely examples, and the present application is not limited to the above-described embodiments. It will be apparent to those skilled in the art that any equivalent modifications or substitutions to the present application are within the scope of the present application, and therefore, equivalent changes and modifications, improvements, etc., which do not depart from the spirit and scope of the present application, are intended to be covered by the present application.

Claims

1. A partial discharge positioning method of a power station cable, the power station cable being applied to a plurality of cables of the same power station, the partial discharge positioning method comprising:

Step S9, acquiring a highlight region of the thermal imaging data based on an abnormal cable, and defining the highlight region as an actual discharge point of the abnormal cable;

acquiring a minimum enclosing sphere, after the acquisition of all theoretical discharge points is completed, acquiring two theoretical discharge points with the farthest mutual distance from all theoretical discharge points and taking the theoretical discharge points as two ends of the diameter of the minimum enclosing sphere, wherein the generated sphere is the minimum enclosing sphere;

step S7, locating a theoretical discharge point of the abnormal cable according to each amplitude difference, and obtaining the minimum surrounding sphere of all theoretical discharge points, wherein the step comprises the following steps:

step S71, judging whether there is a zero amplitude difference;

step S74, obtaining the intersection point of the neutral line and the abnormal cable as the theoretical discharge point;

Step S71, determining whether there is a zero amplitude difference, and then includes:

step S78, defining two points with the minimum value of zero after iteration is completed as the equidistant propagation points;

Step S77, iterating and updating the two close-range propagation points through the global optimizing algorithm to make the minimum value be zero, including:

（2）；

Wherein, For the set of all random solutions,/>For each random solution,/>For/>Labels of individual random solutions,/>The number of all random solutions; /(I)For the set of velocities for all the random solutions,The speed of each random solution;

（3）；

in step S776, it is determined that the iteration is completed.

2. The partial discharge positioning method according to claim 1, wherein the step S2 of extracting a plurality of signal components of each current signal based on empirical mode decomposition, respectively, includes:

3. The partial discharge positioning method according to claim 1, wherein step S3, classifying all signal components by bayesian classification algorithm based on the same cable, respectively, to obtain at least two signal features, includes:

（1）；

Wherein, To at/>Under a preset signal type, the signal set to be classified/>Conditional probability of (2); /(I)For/>Edge probabilities of the preset signal types; /(I)To at/>Under a preset signal type, the first/>Conditional probabilities of the individual signal components;

4. The partial discharge positioning method according to claim 1, wherein step S6, randomly defining at least two signal acquisition points on the abnormal cable, and combining two by two all signal acquisition points to acquire at least one amplitude difference of the abnormal feature, includes:

Step S61, obtaining the total length of the abnormal cable;

5. A partial discharge positioning device of a power station cable, the partial discharge positioning device of the power station cable being applied to the partial discharge positioning method of a power station cable according to any one of claims 1 to 4, characterized in that the partial discharge positioning device comprises:

the actual discharge point definition module is used for acquiring the thermal imaging data based on the highlight area of the abnormal cable and defining the highlight area as the actual discharge point of the abnormal cable;

The minimum bounding sphere acquisition module comprises a first minimum bounding sphere acquisition sub-module, a second minimum bounding sphere acquisition sub-module, a third minimum bounding sphere acquisition sub-module and a fourth minimum bounding sphere acquisition sub-module which are electrically connected in sequence; the first minimum bounding sphere acquisition sub-module is electrically connected with the fifth abnormal characteristic amplitude difference acquisition sub-module, and the fourth minimum bounding sphere acquisition sub-module is electrically connected with the thermal imaging data acquisition module;

The first minimum bounding sphere acquisition sub-module is used for judging whether an amplitude difference of zero exists or not; the second minimum bounding sphere acquisition submodule is used for acquiring two signal acquisition points corresponding to the zero amplitude difference and marking the two signal acquisition points as equidistant propagation points if the amplitude difference is zero; the third minimum bounding sphere acquisition submodule is used for acquiring the shortest connecting line of two equidistant propagation points and acquiring the central line of the shortest connecting line; the fourth minimum bounding sphere acquisition submodule is used for acquiring an intersection point of the neutral line and the abnormal cable to be a theoretical discharge point;

The minimum bounding sphere acquisition module further comprises a fifth minimum bounding sphere acquisition sub-module, a sixth minimum bounding sphere acquisition sub-module, a seventh minimum bounding sphere acquisition sub-module and an eighth minimum bounding sphere acquisition sub-module which are electrically connected in sequence; the fifth minimum bounding sphere acquisition sub-module is electrically connected with the first minimum bounding sphere acquisition sub-module, and the eighth minimum bounding sphere acquisition sub-module is electrically connected with the thermal imaging data acquisition module;

The fifth minimum bounding sphere acquisition submodule is used for acquiring the minimum value of all amplitude differences if the amplitude difference is zero; the sixth minimum bounding sphere acquisition submodule is used for acquiring two signal acquisition points corresponding to the minimum value and marking the two signal acquisition points as close-range propagation points; the seventh minimum bounding sphere acquisition sub-module is used for iterating and updating the points of the two close-range propagation points on the abnormal cable through a global optimizing algorithm so as to enable the minimum value to be zero; the eighth minimum bounding sphere acquisition submodule is used for defining two points with zero minimum value after iteration is completed as equidistant propagation points;

The seventh minimum bounding sphere acquisition submodule comprises a first minimum bounding sphere acquisition unit, a second minimum bounding sphere acquisition unit, a third minimum bounding sphere acquisition unit, a fourth minimum bounding sphere acquisition unit, a fifth minimum bounding sphere acquisition unit and a sixth minimum bounding sphere acquisition unit which are electrically connected in sequence; the first minimum bounding sphere acquisition unit is electrically connected with the sixth minimum bounding sphere acquisition submodule, and the sixth minimum bounding sphere acquisition unit is electrically connected with the eighth minimum bounding sphere acquisition submodule;

The first minimum bounding sphere acquisition unit is used for endowing two close-range propagation points with a plurality of random solutions according to the formula (2), and defining the calculation results of all the random solutions as zero minimum values;

（2）；

（3）；

A third minimum bounding sphere acquisition unit for iterating all random solutions according to equation (3) to update each And；

A fourth minimum bounding sphere acquisition unit for judging eachWhether the difference value compared with the previous iteration is smaller than or equal to a first preset adaptation threshold value;

a fifth minimum bounding sphere acquisition unit for each of Compared with the previous iteration, the difference value is smaller than or equal to the first preset adaptation threshold value, and the/> isjudgedWhether the difference value compared with the previous iteration is smaller than or equal to a second preset adaptation threshold value;

The sixth minimum bounding sphere acquisition unit is used for if And compared with the previous iteration, if the difference value is smaller than or equal to the second preset adaptation threshold value, judging that the iteration is completed.

6. An electronic device comprising a processor, and a memory coupled to the processor, the memory storing program instructions executable by the processor; the processor, when executing the program instructions stored in the memory, implements a partial discharge positioning method of a power station cable according to any one of claims 1 to 4.

7. A storage medium having stored therein program instructions which, when executed by a processor, implement a partial discharge positioning method capable of implementing a power plant cable as claimed in any one of claims 1 to 4.