CN113902049B - Medium-voltage cable intermediate joint operation state evaluation method - Google Patents
Medium-voltage cable intermediate joint operation state evaluation method Download PDFInfo
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Abstract
The invention provides a method for evaluating the running state of a middle joint of a medium-voltage cable, which utilizes various sensors to monitor the running parameters of the middle joint of the medium-voltage cable in real time; establishing a state type identification fuzzy transformation matrix reflecting the relation between the monitoring data of the medium-voltage cable joint and the working state of the medium-voltage cable joint based on past historical maintenance data and current field operation data; based on the state type identification fuzzy transformation matrix, the membership in the state type identification fuzzy transformation matrix is weighted and fused by adopting an expert experience method and a Dempster-Shafer evidence theory, potential redundancy and complementary relations among different monitoring data are fully excavated, and high reliability assessment of the running state of the intermediate connector of the medium voltage cable is realized. According to the invention, the multi-source monitoring data can be organically fused through the evaluation criteria, the coupling relation between the data can be fully mined, and the operation state evaluation of the cable can be accurately completed by utilizing the relation.
Description
Technical Field
The invention relates to the technical field of monitoring and evaluating the running state of a middle joint of a medium-voltage cable, in particular to a method for evaluating the running state of the middle joint of the medium-voltage cable.
Background
In recent years, with the upgrading and reconstruction of power systems, the application proportion of cables in power transmission is gradually increased. In particular, considering that the cable power supply has the advantages of safety, reliability, stability, no influence on environmental beauty and the like, the cable power supply is widely adopted in the 10kV urban power distribution network, and the proportion is larger and larger. However, during the use of power cables, lines, especially intermediate connectors, are subject to fire and explosion events, which can cause significant economic and social losses to the grid enterprise. According to statistics and analysis of cable operation faults, except for damage caused by external force, overload, insulation degradation and damp of the cable are main reasons for causing cable accidents of a distribution network, and the middle joint part is a weak link of the cable operation, and more than 80% of cable fault points are all arranged at the middle joint part, so that maintenance and overhaul of the cable middle joint part are enhanced, the risk probability of faults is prevented, the troubleshooting and maintenance time after the faults is shortened, and the method has great practical significance for reliable and economic operation of an electric power system.
Conventionally, manual periodic and classified maintenance is adopted, for example, in the enterprise standard of the national power grid company (refer to the power cable and channel maintenance procedure Q/GDW 11262-2014), cable maintenance is divided into four types according to the working content and the working range, which are respectively: class a service, class B service, class C service and class D service. Wherein, the overhaul periods and the contents of different categories are different. In addition, the patrol period of the cable line is regulated in the power cable operation maintenance and overhaul regulations: ① The cable terminal in the substation is checked together with the inspection of the high-voltage distribution device, at least 1 time per week; ② The outdoor cable head should be 1 time per month. By the frequent and high-strength inspection, the reliability of the cable performance can be ensured. However, with the large-scale application of the power cable, the number of cables and cable heads is increased sharply and the distribution is wider, so that the traditional method will generate great cost of manpower and material resources, and has extremely low efficiency and difficult practicality. In summary, the conventional overhaul and maintenance method for the power cable has the following problems:
(1) Different from the common overhead line overhaul environment, the cable line is deeply buried, the maintenance and overhaul work of the cable line is not easy, and particularly, the number of the cable is increased in an explosive manner along with the large-scale application of the cable, and the existing manpower and material resources are insufficient for maintaining the traditional overhaul scheme;
(2) Generally, in order to ensure safe and stable operation of power cable equipment, an maintainer often sets a corresponding maintenance period according to technical parameters of the cable and related equipment, a load-bearing operation load and other factors, and the method of performing inspection according to a fixed period is called "scheduled maintenance". However, it should be noted that it is difficult to set up a service period that meets all of the cable service requirements, considering that factors that affect or exacerbate the extent of cable and related equipment failure are different. Once the maintenance period is too long, the probability of cable faults is increased; otherwise, once the maintenance period is too short, the service lives of the cable and related equipment are shortened, and the waste of human and material resources which cannot be ignored is generated.
In order to solve the problems, in some areas, such as Zhejiang, guangdong and the like, which have high requirements on power supply reliability, a state maintenance concept is introduced in cable maintenance. The cable operation parameters can be monitored in real time by arranging the on-line monitoring terminal around the cable. The method can timely know the running states of the cable line and related equipment after processing and analyzing the collected monitoring data. Once a fault is found, corresponding maintenance strategies and protection measures can be timely made, site workers are arranged to realize fixed-point and accurate maintenance, the working efficiency is greatly improved, and the intelligent conversion from 'passive first-aid maintenance' to 'active operation and maintenance' is realized. However, currently mainstream condition maintenance schemes often evaluate the cable operating condition with only a single monitored (temperature-based) data. The reliability of the assessment method by means of single monitoring quantity is not guaranteed, and various problems such as false alarm and missing alarm can occur, so that serious economic loss is caused. In addition, even though few areas adopt an evaluation method based on multiple monitoring amounts, the currently adopted method is only a simple list of monitoring data sets, the coupling relation among the data is not deeply researched, and a comprehensive criterion capable of effectively fusing multiple monitoring data is not formed.
Disclosure of Invention
In order to solve the problems, the invention aims to provide a method for evaluating the running state of a middle joint of a medium-voltage cable, which can organically integrate multi-source monitoring data through evaluation criteria, fully mine the coupling relation between the data, accurately complete the running state evaluation of the cable by utilizing the relation, solve the problems that the traditional scheme of 'planning maintenance' is difficult to adapt to the current explosive growth of the cable, and solve the problems that the monitoring data is insufficient and the data mining degree is not deep enough in the current state maintenance scheme.
In order to achieve the above purpose, the technical scheme of the invention is realized as follows:
The method for evaluating the running state of the intermediate connector of the medium-voltage cable comprises the following steps of:
s1, measuring the state quantity of an intermediate connector of a medium-voltage cable through a monitoring terminal;
S2, the underground miniature cable data concentrator timely collects monitoring data of each miniature state sensing sensor in the monitoring terminal through a LORA local wireless communication network technology, packages and compresses the monitoring data, and transmits the monitoring data to a monitoring master station or an operation and maintenance personnel terminal through a GPRS wireless communication mode, so that cable state monitoring historical data are formed;
S3, comprehensively utilizing past cable overhaul experience and massive historical data, and establishing a membership function group between monitoring data and working states of the medium-voltage cable connector based on a cloud theory algorithm; decompressing the transmitted data packet to obtain monitoring data of different sensors, substituting the monitoring data into a membership function group, calculating membership of the cable to different working states at the moment, forming a state type identification fuzzy transformation matrix, and laying a foundation for subsequent state evaluation;
S4, weighting the membership degree obtained by the state type identification fuzzy transformation matrix R according to expert experience by using a subjective weighting method based on expert experience to obtain a state type comprehensive identification matrix N; wherein, the more the cable operation parameter reflecting the fault nature, the higher the weight coefficient is given;
s5, carrying out fusion processing on the multisource membership in the state type comprehensive identification matrix by adopting a Dempster-Shafer evidence theory, calculating a new membership value obtained by combining a plurality of membership, judging the working state of the tested cable joint according to the membership maximum criterion, and realizing high-precision evaluation of the state of the cable joint.
Further, the step S3 specifically includes:
S31: according to the type of the existing microsensor and the history maintenance experience, obtaining monitoring data comprising cable surface temperature, local discharge capacity and sheath current, and assuming that three monitoring data obtained by measurement at a certain moment are respectively named as X i (i=1, 2 and 3) and jointly forming a set X; the common working states of the cable comprise a short circuit fault, a ground fault, a broken line fault and a normal running state, and the four working states are respectively named as Y j (j=1, 2,3, 4) and jointly form a set Y;
s32: based on massive historical data, a cloud theory algorithm is adopted, a membership degree function group U from monitoring data to the working state of the cable is established, and the membership degree function group U is shown in the following formula (1);
Wherein r ij represents a membership function of the monitoring data x i corresponding to the cable working state y i, and x represents the numerical value of the monitoring data; each monitoring data form an independent membership function based on a cloud theory algorithm, and the general expression of r ij∈[0,1];rij is shown as the following formula (2):
wherein, X i represents the monitoring data, n represents the number of historical data used to solve the membership function; the larger r ij (not more than 1) indicates the higher the possibility that the cable is affiliated to the corresponding operation state, whereas the smaller r ij (not less than 0) indicates the lower the possibility that the cable is affiliated to the corresponding operation state;
S33: after the membership function group U is obtained, substituting monitoring data at a certain moment into the membership function group U to form a state type identification fuzzy transformation matrix R, wherein the state type identification fuzzy transformation matrix R is shown in the following formula (3); wherein x i (i=1, 2, 3) represents a specific value of the monitoring data measured at a certain moment;
Further, the step S5 specifically includes: based on deep fusion of the Dempster-Shafer evidence theory realization state type comprehensive identification matrix N, different membership degrees (corresponding to r 1x(x＝1,2,3)、r2x(x＝1,2,3)、r3x (x=1, 2, 3) and r 4x (x=1, 2, 3) in the formula (1)) corresponding to different working states are fused, the actual running state of the cable joint is estimated according to the maximum membership degree principle, and the reality and reliability of the running state estimation result are ensured.
Further, the step S4 specifically includes:
S41: because the importance of each element in the set X is different, for this purpose, weight judgment is carried out on each element according to expert experience, and a judgment matrix M is constructed; for convenience of scale, a 1-9 scale method is adopted, and a judgment matrix M is shown as the following formula (4):
Wherein m ij represents the influence degree of the monitoring data x i on the cable running state evaluation result compared with x j, the size of the monitoring data x i can be represented by 1-9 and the inverse thereof, and the larger the numerical value is, the higher the importance degree is represented;
S42: calculating a characteristic value lambda 1,λ2,λ3 of the judging matrix M to form weight coefficients corresponding to different types of monitoring data, and multiplying the weight coefficients by column data corresponding to a state type identification fuzzy transformation matrix R to form a state type comprehensive identification matrix N, wherein the formula (5) is as follows; wherein mu ij represents the membership degree of the cable in the working state y j which is deduced from the monitoring data x i;
further, the step S5 specifically includes:
S51: for different working states y j (j=1, 2,3, 4) of the cable joint, membership degrees of various monitoring data x i (i=1, 2, 3) of the cable joint are mu ij respectively, and a conflict coefficient matrix K among the various monitoring data is calculated, wherein the conflict coefficient matrix K is shown in the following formula (6):
s52: calculating a new membership matrix after combining a plurality of membership degrees:
s53: in the formed new membership matrix, each element corresponds to one cable working state in the Y matrix, and the state corresponding to the largest element in the newly formed membership matrix is judged by searching the largest element, namely the actual running state of the cable joint, so that the state real-time evaluation is completed.
Further, the monitoring terminal comprises an underground miniature temperature sensor, an underground miniature partial discharge sensor, an underground miniature current sensor and a miniature state sensing sensor, and the monitoring data comprises surface temperature, local discharge capacity, sheath current and environment temperature and humidity when the cable runs.
Furthermore, the underground miniature temperature sensor, the underground miniature partial discharge sensor, the underground miniature current sensor and the miniature state sensing sensor are all fixed at the temperature measuring part of the cable joint in an elastic silica gel binding mode, and the underground miniature temperature sensor can detect the temperature of three points simultaneously.
Furthermore, the underground miniature temperature sensor can monitor real-time temperature conditions of each point along the cable by winding the temperature measuring optical fiber on the surface of the insulating shielding layer of the cable by using a distributed optical fiber temperature measuring method; the miniature temperature sensor is used for independently setting alarm values of temperature measuring points for three detection points and supporting various threshold alarm modes of constant temperature, differential temperature and average temperature; the underground miniature current sensor utilizes a current transformer to measure a cable grounding wire current signal, and can reflect the surface insulation state of a cable to be measured in real time; the underground micro partial discharge sensor adopts an electromagnetic coupling method, and the measuring position is at the grounding lead of the metal shielding layer of the cable terminal.
Furthermore, the underground miniature cable data concentrator is fixedly arranged on a cable bridge or fixedly bound on a cable, timely gathers abnormal operation information of the temperature sensor, timely uploads the abnormal operation information, and detects environmental temperature and humidity and discharge information of nearby cables; the underground miniature cable data concentrator is provided with a positioning module, and after the cable has abnormal temperature or discharge fault, the underground miniature cable data concentrator timely uploads temperature abnormal or discharge information and position information to the management platform so as to reduce fault searching time.
Furthermore, the data collection points of the underground miniature cable data concentrator are at least provided with 48 paths, the data are stored locally, the data can be received and updated once every 1min according to operation and maintenance requirements, and the data result is uploaded to a monitoring main station or an operation and maintenance personnel terminal through a LORA local wireless communication network.
The beneficial effects are that: according to the invention, the Dempster-Shafer evidence theory is adopted to fuse the state type comprehensive identification matrix, membership degrees of various monitoring data are fused, potential redundancy and complementary relation among the monitoring data are fully mined, high-reliability state evaluation considering fusion of various single uncertainty results is realized, and an effective basis is provided for evaluating the running state of the intermediate connector of the medium-voltage cable.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention, illustrate and explain the invention and together with the description serve to explain the invention. In the drawings:
Fig. 1 is a flow chart illustrating a method for evaluating an operation state of an intermediate connector of a medium voltage cable according to an embodiment of the present invention;
Fig. 2 is a schematic installation diagram of a monitoring terminal of a method for evaluating an operation state of an intermediate connector of a medium voltage cable according to an embodiment of the present invention;
fig. 3 is a schematic functional structural diagram of an evaluation method for the running state of an intermediate connector of a medium voltage cable according to an embodiment of the present invention.
Detailed Description
It should be noted that, without conflict, the embodiments of the present invention and features of the embodiments may be combined with each other.
The invention will be described in detail below with reference to the drawings in connection with embodiments.
Example 1
See fig. 1-3: the method for evaluating the running state of the intermediate connector of the medium-voltage cable comprises the following steps of:
s1, measuring the state quantity of an intermediate connector of a medium-voltage cable through a monitoring terminal;
S2, the underground miniature cable data concentrator timely collects monitoring data of each miniature state sensing sensor in the monitoring terminal through a LORA local wireless communication network technology, packages and compresses the monitoring data, and transmits the monitoring data to a monitoring master station or an operation and maintenance personnel terminal through a GPRS wireless communication mode, so that cable state monitoring historical data are formed;
S3, comprehensively utilizing past cable overhaul experience and massive historical data, and establishing a membership function group between monitoring data and working states of the medium-voltage cable connector based on a cloud theory algorithm; decompressing the transmitted data packet to obtain monitoring data of different sensors, substituting the monitoring data into a membership function group, calculating membership of the cable to different working states at the moment, forming a state type identification fuzzy transformation matrix, and laying a foundation for subsequent state evaluation;
S4, weighting the membership degree obtained by the state type identification fuzzy transformation matrix R according to expert experience by using a subjective weighting method based on expert experience to obtain a state type comprehensive identification matrix N; wherein, the more the cable operation parameter reflecting the fault nature, the higher the weight coefficient is given;
s5, carrying out fusion processing on the multisource membership in the state type comprehensive identification matrix by adopting a Dempster-Shafer evidence theory, calculating a new membership value obtained by combining a plurality of membership, judging the working state of the tested cable joint according to the membership maximum criterion, and realizing high-precision evaluation of the state of the cable joint.
The cloud theory is based on cross penetration of probability theory and fuzzy set theory, and seeks an uncertainty mapping relation between qualitative concept and quantitative numerical value. Specifically, the monitoring data belong to quantitative values, the cable working state belongs to qualitative concepts, and the membership degree of the cable working state is calculated based on each monitoring data. Thus, the method of evaluation may be implemented by constructing a membership function.
The membership function is defined as: for any element x i in the research scope, there is a membership value r ij(xi) e [0,1] corresponding to the class y j, where the closer the membership r ij(xi) is to 1, the greater the probability that element x i belongs to class y j, and the closer P(s) is to 0, the lesser the probability that element x i belongs to class y j. When x i varies within its domain, r ij (x) is called the membership function of class y j. The cable monitoring process is described in connection with the cable monitoring process, the monitoring data corresponds to the element x i, the cable working state corresponds to the y j, and each monitoring data can infer the working state of the cable at the moment, for example, if the surface temperature of the cable is 70 ℃ at a certain moment, the cable is likely to be in a short-circuit working state at the moment, so that the slave attribute of the cable in the short-circuit state is close to 1, and the membership of the other working states is close to 0. And the like, based on the historical overhaul data, the distribution situation of each monitoring data corresponding to each working state under different values can be generalized, and a membership function from the monitoring data to the cable working state is established by utilizing a cloud theory algorithm.
In addition, referring to past overhaul experience, the importance of overhaul experts to each monitored variable will be different. Therefore, a method for determining the weight of the monitored variable by subjective judgment based on the experience of the expert is called a subjective weighting method based on the experience of the expert, and the original data is obtained completely according to the subjective judgment of the experience of the expert.
It can be understood that the membership value obtained based on the cloud theory algorithm basically belongs to objective weight (completely referring to historical data), and the objective weighting method ignores the difference of the indexes, so that the obtained weight coefficient is easily influenced by the randomness of the sample data. Therefore, the subjective weighting method based on expert experience is applied to cable state evaluation, the organic combination of subjective experience and objective data is realized, and the reliability of membership in a state type identification fuzzy transformation matrix is improved.
In summary, on the basis of obtaining multiple groups of membership degrees of the monitoring data to the working state of the cable by using a cloud theory algorithm and a subjective weighting method, uncertain information from different monitoring terminals is further fused, and a brand new membership degree is obtained through calculation and is used as output; and finally, evaluating the actual running state of the cable joint according to the membership degree maximum principle.
In a specific example, the step S3 specifically includes:
S31: according to the type of the existing microsensor and the history maintenance experience, obtaining monitoring data comprising cable surface temperature, local discharge capacity and sheath current, and assuming that three monitoring data obtained by measurement at a certain moment are respectively named as X i (i=1, 2 and 3) and jointly forming a set X; the common working states of the cable comprise a short circuit fault, a ground fault, a broken line fault and a normal running state, and the four working states are respectively named as Y j (j=1, 2,3, 4) and jointly form a set Y;
s32: based on massive historical data, a cloud theory algorithm is adopted, a membership degree function group U from monitoring data to the working state of the cable is established, and the membership degree function group U is shown in the following formula (1);
Wherein r ij represents a membership function of the monitoring data x i corresponding to the cable working state y i, and x represents the numerical value of the monitoring data; each monitoring data form an independent membership function based on a cloud theory algorithm, and the general expression of r ij∈[0,1];rij is shown as the following formula (2):
wherein, X i represents the monitoring data, n represents the number of historical data used to solve the membership function; the larger r ij (not more than 1) indicates the higher the possibility that the cable is affiliated to the corresponding operation state, whereas the smaller r ij (not less than 0) indicates the lower the possibility that the cable is affiliated to the corresponding operation state;
S33: after the membership function group U is obtained, substituting monitoring data at a certain moment into the membership function group U to form a state type identification fuzzy transformation matrix R, wherein the state type identification fuzzy transformation matrix R is shown in the following formula (3); wherein x i (i=1, 2, 3) represents a specific value of the monitoring data measured at a certain moment;
In a specific example, the step S5 specifically includes: based on Dempster-Shafer evidence theory, the deep fusion of the state type comprehensive identification matrix N is realized, different slave attributes (r 1x(x＝1,2,3)、r2x(x＝1,2,3)、r3x (x=1, 2, 3) and r 4x (x=1, 2, 3) in corresponding formula (1)) corresponding to different working states are fused, the actual running state of the cable joint is estimated according to the maximum membership principle, and the reality and reliability of the running state estimation result are ensured.
In a specific example, the step S4 specifically includes:
S41: because the importance of each element in the set X is different, for this purpose, weight judgment is carried out on each element according to expert experience, and a judgment matrix M is constructed; for convenience of scale, a 1-9 scale method is adopted, and a judgment matrix M is shown as the following formula (4):
Wherein m ij represents the influence degree of the monitoring data x i on the cable running state evaluation result compared with x j, the size of the monitoring data x i can be represented by 1-9 and the inverse thereof, and the larger the numerical value is, the higher the importance degree is represented; for example, assuming that the expert subjectively considers x i to be 2 times more important than x j, one can consider m ij =2, and correspondingly m ji =1/2;
S42: calculating a characteristic value lambda 1,λ2,λ3 of the judging matrix M to form weight coefficients corresponding to different types of monitoring data, and multiplying the weight coefficients by column data corresponding to a state type identification fuzzy transformation matrix R to form a state type comprehensive identification matrix N, wherein the formula (5) is as follows; wherein mu ij represents the membership degree of the cable in the working state y j which is deduced from the monitoring data x i;
in a specific example, the step S5 specifically includes:
S51: for different working states y j (j=1, 2,3, 4) of the cable joint, membership degrees of various monitoring data x i (i=1, 2, 3) of the cable joint are mu ij respectively, and a conflict coefficient matrix K among the various monitoring data is calculated, wherein the conflict coefficient matrix K is shown in the following formula (6):
s52: calculating a new membership matrix after combining a plurality of membership degrees:
s53: in the formed new membership matrix, each element corresponds to one cable working state in the Y matrix, and the state corresponding to the largest element in the newly formed membership matrix is judged by searching the largest element, namely the actual running state of the cable joint, so that the state real-time evaluation is completed.
In a specific example, the monitoring terminal includes an underground miniature temperature sensor, an underground miniature partial discharge sensor, an underground miniature current sensor and a miniature state sensing sensor, and the monitoring data includes a surface temperature, a local discharge amount, a sheath current and an environmental temperature and humidity when the cable is operated.
It should be noted that, the monitoring terminal of the present embodiment can utilize various sensing technologies to measure the state quantity of the underground cable joint, and the monitoring terminal is various in variety, including, but not limited to, a special miniature state sensing sensor such as an underground miniature temperature sensor, an underground miniature partial discharge sensor, an underground miniature current sensor, etc. The monitoring terminal has the characteristics of small volume and high precision, can work in a narrow underground pipeline, and can adapt to the extreme working environments such as low temperature, high temperature, damp heat and the like in areas with different longitudes and latitudes. The monitoring process of the embodiment can accurately monitor the state information such as the temperature, partial discharge, sheath current, environment temperature and humidity of the intermediate joint of the underground cable in real time, and provide data support for the subsequent comprehensive state evaluation of the intermediate joint of the underground cable.
In a specific example, the downhole micro temperature sensor, the downhole micro partial discharge sensor, the downhole micro current sensor and the micro state sensing sensor are all fixed at the temperature measuring part of the cable joint in an elastic silica gel binding manner, and the downhole micro temperature sensor can detect the temperature of three points at the same time.
It should be noted that, each type of downhole microsensor of the present embodiment collects monitoring data once every 1 minute; when temperature abnormality occurs (absolute temperature exceeds alarm temperature, temperature phase difference among three phases exceeds alarm limit value, alarm temperature and alarm limit value can be set), the temperature sensor uploads temperature data to the data concentrator through LORA wireless communication mode.
In a specific example, the downhole micro temperature sensor uses a distributed optical fiber temperature measurement method, and real-time temperature conditions of each point along the cable can be monitored by winding a temperature measurement optical fiber on the surface of an insulating shielding layer of the cable; the miniature temperature sensor is used for independently setting alarm values of temperature measuring points for three detection points and supporting various threshold alarm modes of constant temperature, differential temperature and average temperature; the underground miniature current sensor utilizes a current transformer to measure a cable grounding wire current signal, and can reflect the surface insulation state of a cable to be measured in real time; the underground miniature partial discharge sensor adopts an electromagnetic coupling method, and the measuring position is at the grounding lead of the metal shielding layer of the cable terminal.
In a specific example, the underground miniature cable data concentrator is fixedly arranged on a cable bridge or fixedly bound on a cable, timely gathers abnormal operation information of a temperature sensor, timely uploads the abnormal operation information, and detects environmental temperature and humidity and discharge information of nearby cables; the underground miniature cable data concentrator is provided with a positioning module, and after the cable has abnormal temperature or discharge fault, the underground miniature cable data concentrator timely uploads temperature abnormal or discharge information and position information to the management platform so as to reduce fault searching time.
It should be noted that, the data concentrator of this embodiment is fixedly installed on a cable bridge or fixedly bound on a cable, and timely gathers the abnormal operation information of the downhole micro sensor in a certain range around and timely sends up, and thus forms a cable state monitoring historical data set at the monitoring master station.
In a specific example, at least 48 paths of data points are collected by the underground miniature cable data concentrator, the data is stored in situ, and the data result is uploaded to a monitoring master station or an operation and maintenance personnel terminal through a LORA local wireless communication network after receiving and updating one time every 1min according to operation and maintenance requirements.
It should be noted that, the LORA local wireless communication network technology is one of LPWAN communication technologies, is an ultra-long distance wireless transmission scheme based on spread spectrum technology adopted and promoted by Semtech company in usa, and has the advantages of long transmission distance, low working power consumption, many networking nodes and the like. Particularly, the monitoring terminals work in the field and are widely distributed, the requirements for communication among the terminals are very harsh, and the LORA local wireless communication network technology can effectively meet the actual working requirements.
Example 2
In a specific implementation, the method for evaluating the running state of the intermediate connector of the medium voltage cable in the embodiment comprises the following steps:
Step 1: cable operation parameter collection based on monitoring terminal: the state of a 10kV ZR-YJY 22-3X 240 cable with the underground length of 200m in a certain city substation is monitored through a monitoring terminal, wherein the monitoring shows that the working temperature of the cable at a certain moment is 25 ℃, the local discharge capacity is 3pC, and the sheath current is 5 mu A. In addition, the monitoring terminal collects monitoring data once every 1 minute, uploads the collected data to the data concentrator in a Lora wireless communication mode, and further uploads the collected data to the cable running state real-time evaluation master station in a GPRS wireless communication network, so that cable state monitoring calendar history data are formed;
Step 2: based on the mass data of the historical database, a mapping relation between monitoring data and working states of the medium-voltage cable joint is established based on a cloud theory algorithm: firstly, three kinds of monitoring data for evaluating the running state of the cable are determined according to the types of the microsensors contained in the actual monitoring process, wherein the three kinds of monitoring data are respectively: surface temperature, partial discharge capacity, sheath current, denoted by X 1-X3; secondly, determining common cable working states according to historical overhaul data of the cable, wherein the common cable working states are respectively as follows: short circuit fault, ground fault, disconnection fault, and normal operation state, denoted by S 1-S4. On the basis, a cloud theory algorithm is adopted to respectively establish membership functions from each monitoring data to different cable working states, and a 3 multiplied by 4 membership function group U can be formed according to the combination of the possibility of 4 fault types corresponding to 3 monitoring data. Further, the field operation data measured in the step 1 are substituted into the membership function group U to form a state type identification fuzzy transformation matrix R reflecting the mapping relation between the monitoring data and the working state. At this time, the fuzzy transformation matrix R is calculated as:
step 3: and weighting the importance of the three monitoring data, namely the surface temperature, the partial discharge capacity and the sheath current, based on the running experience of the field expert. The specific method is as follows: searching for guidance from a plurality of experts by issuing a questionnaire, and establishing the judgment matrix using the data obtained by the questionnaire, as shown in formula (7):
Further, based on the judgment matrix, the characteristic vector and the characteristic value are calculated, wherein the characteristic value is subjective weight. The weights of the three monitoring data of the surface temperature, the partial discharge amount and the sheath current are calculated to be 0.8,0.8,0.6, and a state type comprehensive identification matrix N is formed in conclusion, and is shown as a formula (10).
The state type comprehensive identification matrix N is displayed with a membership relationship in a table form, as shown in table 1, wherein μ (S i) represents the membership of the working state S i:
TABLE 1 State type comprehensive identification matrix
| Monitoring object | μ(S1) | μ(S2) | μ(S3) | μ(S4) |
| Surface temperature of cable | 0.0296 | 0.2576 | 0.0112 | 0.5016 |
| Partial discharge amount | 0.4184 | 0.1016 | 0 | 0.28 |
| Sheath current | 0.3486 | 0.0516 | 0 | 0.1998 |
Step 4: finally, the membership degree of various monitoring objects in table 1 is subjected to deep fusion processing by adopting a Dempster-Shafer evidence theory, and data are substituted into formulas (6) and (7), so that a conflict coefficient K is 0.9663, and the comprehensive credibility distribution of each running state (S 1-S4) is respectively 0.128, 0.04, 0 and 0.8327. The result shows that the membership mu (S 4) is obviously greater than the other three kinds of trust, and the corresponding running state is normal running, so that the medium-voltage cable can be considered to be in the normal running state at the moment, the result is consistent with the actual checking result, and the correctness and the reliability of the proposed evaluation scheme are verified.
The foregoing description of the preferred embodiments of the invention is not intended to limit the invention to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and scope of the invention are intended to be included within the scope of the invention.
Claims (9)
1. The method for evaluating the running state of the intermediate connector of the medium-voltage cable is characterized by comprising the following steps of:
s1, measuring the state quantity of an intermediate connector of a medium-voltage cable through a monitoring terminal;
S2, the underground miniature cable data concentrator timely collects monitoring data of each miniature state sensing sensor in the monitoring terminal through a LORA local wireless communication network technology, packages and compresses the monitoring data, and transmits the monitoring data to a monitoring master station or an operation and maintenance personnel terminal through a GPRS wireless communication mode, so that cable state monitoring historical data are formed;
s3, comprehensively utilizing past cable overhaul experience and massive historical data, and establishing a membership function group between monitoring data and working states of the medium-voltage cable connector based on a cloud theory algorithm; decompressing the transmitted data packet to obtain monitoring data of different sensors, substituting the monitoring data into a membership function group, calculating membership of the cable to different working states at the moment, forming a state type identification fuzzy transformation matrix, and laying a foundation for subsequent state evaluation;
s4, weighting the membership degree obtained by the state type identification fuzzy transformation matrix R according to expert experience by using a subjective weighting method based on expert experience to obtain a state type comprehensive identification matrix N; wherein, the more the cable operation parameter reflecting the fault nature, the higher the weight coefficient is given;
S5, carrying out fusion processing on the multisource membership in the state type comprehensive identification matrix by adopting a Dempster-Shafer evidence theory, calculating a new membership value obtained by combining a plurality of membership, judging the working state of the tested cable joint by using a membership maximum criterion, and realizing high-precision evaluation of the state of the cable joint;
the step S3 specifically includes:
s31: according to the type of the existing microsensor and the history maintenance experience, obtaining monitoring data comprising cable surface temperature, local discharge capacity and sheath current, and assuming that three monitoring data obtained by measurement at a certain moment are respectively named as X i, i=1, 2 and 3, and jointly forming a set X; the common working states of the cable comprise a short circuit fault, a ground fault, a broken line fault and a normal running state, and the four working states are respectively named as Y j, j=1, 2,3 and 4 and form a set Y together;
S32: based on massive historical data, a cloud theory algorithm is adopted to establish a membership degree function group U from monitoring data to a cable working state, wherein the membership degree function group U is shown in the following formula (1);
Wherein r ij represents a membership function of the monitoring data x i corresponding to the cable working state y i, and x represents the numerical value of the monitoring data; each monitoring data form an independent membership function based on a cloud theory algorithm, and the general expression of r ij∈[0,1];rij is shown as the following formula (2):
wherein, X i represents the monitoring data, n represents the number of historical data used to solve the membership function; the larger r ij is, the r ij is not more than 1, which means that the possibility that the cable belongs to the corresponding working state is higher, whereas the smaller r ij is, the smaller r ij is, the more 0 is, and the lower the possibility that the cable belongs to the corresponding working state is;
S33: after the membership function group U is obtained, substituting monitoring data at a certain moment into the membership function group U to form a state type identification fuzzy transformation matrix R, wherein the state type identification fuzzy transformation matrix R is shown in the following formula (3); wherein x i, i=1, 2,3, represents a specific value of the monitoring data measured at a certain moment;
2. The method for evaluating the running state of the intermediate connector of the medium voltage cable according to claim 1, wherein the step S5 is specifically: based on Dempster-Shafer evidence theory, the deep fusion of the state type comprehensive identification matrix N is realized, different membership degrees corresponding to different working states are fused corresponding to r 1x,x＝1,2,3,r2x,x＝1,2,3,r3x, x=1, 2 and 3 and r 4x, x=1, 2 and 3 in the formula (1), the actual running state of the cable joint is estimated according to the maximum membership degree principle, and the true reliability of the running state estimation result is ensured.
3. The method for evaluating the running state of the intermediate connector of the medium voltage cable according to claim 1, wherein the step S4 specifically comprises:
S41: because the importance of each element in the set X is different, for this purpose, each element is subjected to weight judgment according to expert experience, and a judgment matrix M is constructed; for convenience of scale, a 1-9 scale method is adopted, and a judgment matrix M is shown as the following formula (4):
Wherein m ij represents the influence degree of the monitoring data x i on the cable running state evaluation result compared with x j, the size of the monitoring data x i can be represented by 1-9 and the inverse thereof, and the larger the numerical value is, the higher the importance degree is represented;
S42: calculating a characteristic value lambda 1,λ2,λ3 of the judging matrix M to form weight coefficients corresponding to different types of monitoring data, and multiplying the weight coefficients by column data corresponding to a state type identification fuzzy transformation matrix R to form a state type comprehensive identification matrix N, wherein the formula (5) is as follows; wherein mu ij represents the membership degree of the cable in the working state y j which is deduced from the monitoring data x i;
4. the method for evaluating the running state of the intermediate connector of the medium voltage cable according to claim 1, wherein the step S5 specifically comprises:
S51: for different working states y j, j=1, 2,3,4 of the cable joint, membership degrees of various monitoring data x i, i=1, 2,3 are mu ij respectively, and a conflict coefficient matrix K among the various monitoring data is calculated, wherein the conflict coefficient matrix K is shown in the following formula (6):
s52: calculating a new membership matrix after combining a plurality of membership degrees:
S53: in the formed new membership matrix, each element corresponds to one cable working state in the set Y, and the state corresponding to the largest element in the newly formed membership matrix is judged by searching the largest element, namely the actual running state of the cable joint, so that the state real-time evaluation is completed.
5. The method for evaluating the running state of the intermediate connector of the medium-voltage cable according to claim 1, wherein the monitoring terminal comprises an underground miniature temperature sensor, an underground miniature partial discharge sensor, an underground miniature current sensor and a miniature state sensing sensor, and the monitoring data comprises the surface temperature, the partial discharge amount, the sheath current and the environment temperature and humidity during the cable running.
6. The method for evaluating the running state of the middle joint of the medium-voltage cable according to claim 5, wherein the underground miniature temperature sensor, the underground miniature partial discharge sensor, the underground miniature current sensor and the miniature state sensing sensor are all fixed at the temperature measuring part of the cable joint in a mode of binding elastic silica gel, and the underground miniature temperature sensor can detect the temperature of three points at the same time.
7. The method for evaluating the running state of the intermediate connector of the medium-voltage cable according to claim 5, wherein the underground miniature temperature sensor can monitor the real-time temperature condition of each point along the cable by winding a temperature measuring optical fiber on the surface of an insulating shielding layer of the cable by using a distributed optical fiber temperature measuring method; the miniature temperature sensor is used for independently setting alarm values of temperature measuring points for three detection points and supporting various threshold alarm modes of constant temperature, differential temperature and average temperature; the underground miniature current sensor utilizes a current transformer to measure a cable grounding wire current signal, and can reflect the surface insulation state of a cable to be measured in real time; the underground miniature partial discharge sensor adopts an electromagnetic coupling method, and the measuring position is at the grounding lead of the metal shielding layer of the cable terminal.
8. The method for evaluating the running state of the intermediate connector of the medium-voltage cable according to claim 1, wherein the underground miniature cable data concentrator is fixedly arranged on a cable bridge or fixedly bound on a cable, timely gathers abnormal running information of a temperature sensor, timely uploads the abnormal running information, and detects environmental temperature and humidity and discharge information of nearby cables; the underground miniature cable data concentrator is provided with a positioning module, and after the cable has abnormal temperature or discharge fault, the underground miniature cable data concentrator timely uploads temperature abnormal or discharge information and position information to the management platform so as to reduce fault searching time.
9. The method for evaluating the running state of the intermediate connector of the medium-voltage cable according to claim 1, wherein at least 48 paths of collected data points of the underground miniature cable data concentrator are arranged, the data are stored in situ, updated data can be received every 1min according to the operation and maintenance requirements, and the data result is uploaded to a monitoring main station or an operation and maintenance personnel terminal through a LORA local wireless communication network.
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