CN-121984219-A - Online fuse monitoring method and system based on Internet of things

CN121984219ACN 121984219 ACN121984219 ACN 121984219ACN-121984219-A

Abstract

The invention discloses an online fuse monitoring method and system based on the Internet of things, which comprises a sensor module, a remote terminal module, a fuse state monitoring module, an electric power Internet of things local server module, an intelligent terminal device/APP module, a background analysis system module, a LoRaWAN module and an Internet of things cloud server, wherein the condition of a fuse is firstly evaluated through fuzzy set theory to obtain qualitative weight, the quantitative weight is determined through evaluating the influence of the fuse on the reliability of the whole system, then the priority of the fuse in online monitoring is determined by adopting qualitative and quantitative standards, and the fuse is detected according to the priority.

Inventors

LI JIAN
Yang Houteng
WANG HAOYUAN
LU DAYONG
SUN HAIYU
WANG XIAOHUA
XING PENG
LI JIRUI
LI ZHONGKUN
ZHAO RENLONG
ZHANG YABO

Assignees

国网河南省电力公司濮阳供电公司

Dates

Publication Date: 20260505
Application Date: 20251201

Claims (10)

1. The fuse online monitoring system based on the Internet of things is characterized by comprising a sensor module, a remote terminal module, a fuse state monitoring module, an electric power Internet of things local server module, an intelligent terminal device/APP module, a background analysis system module, a LoRaWAN module and an Internet of things cloud server; The sensor module collects real-time state signals of the fuse and transmits the signals to the remote terminal module; the fuse state monitoring module uploads the collected fuse information to a local server module of the electric power Internet of things; The intelligent terminal equipment/APP module is respectively and bidirectionally interconnected with the electric power Internet of things local server module and the background analysis system module, and is used for receiving and displaying information sent by the electric power Internet of things local server module and the background analysis system module and sending information to the electric power Internet of things local server module and the background analysis system module; The background analysis system module is respectively and bidirectionally interconnected with the electric power Internet of things local server module, and is bidirectionally interconnected with the Internet of things cloud server through the LoRaWAN module, and is used for receiving and processing information sent by the electric power Internet of things local server module and the Internet of things cloud server and sending information to the display electric power Internet of things local server module and the Internet of things cloud server.
2. The online fuse monitoring method based on the Internet of things based on the system of claim 1 comprises the following steps: s1, acquiring basic information of all fuses to be detected; S2, performing qualitative analysis on each fuse through a fuzzy analytic hierarchy process to obtain qualitative weight W Qul,F of each fuse; S3, quantitatively analyzing the reliability influence of the fuse, which is not suitable for qualitative analysis, in the whole system by utilizing a reliability index to obtain the quantitative weight W Qun,F of the fuse; S4, combining qualitative and quantitative weighting coefficients, determining the accumulated weight W F,i of each fuse, sequencing the accumulated weights, and determining the detection priority of the fuses according to the sequencing result.
3. The method and system for online monitoring of a fuse based on Internet of things of claim 2, wherein in the step S1, the fuse information comprises fuse drop information, fuse tube temperature information, environment humidity information and fuse position geographic information.
4. The online monitoring method and system for fuses based on the Internet of things of claim 2, wherein in the step S2, the process of obtaining the qualitative weight W Qul,F of each fuse is as follows: 1) Determining the most important standard and the sub-standard related to the standard in the obtained fuse information, and defining the standard and the sub-standard; 2) Normalizing the defined standards and sub-standards to obtain fuse weights associated with the standards, and determining final weights of the standards by fuzzy analytic hierarchy process ; 3) After weighting the defined sub-standards and standards, the final weight of the ith fuse relative to the qualitative standard is obtained ; 4) Performing weight consistency check through a consistency ratio CR formula to finally obtain the qualitative weight of the ith fuse 。
5. The online monitoring method and system for the fuse based on the Internet of things, as set forth in claim 4, wherein in step 2), the language variable in the traditional analytic hierarchy process is converted into a fuzzy language variable, the comparison matrix is completed through the fuzzy language variable, and the final weight of each criterion is calculated by the following formula: In the formula, Is the final fuzzy weight of the ith criterion; Is the relative fuzzy weight of the ith criterion relative to the jth criterion, and the final clear weight C J for each criterion will be calculated by a three-number average operation on the fuzzy final weight for that criterion.
6. The online monitoring method and system for fuses based on the Internet of things of claim 5, wherein in step 3), final weight of the ith fuse relative to qualitative standards is calculated Is determined by the following formula: In the formula, Weights for the j-th criterion; F n represents an nth fuse; Is the weight of the sub-criterion relative to the j-th criterion.
7. The online monitoring method and system for the fuse based on the Internet of things of claim 2, wherein in the step S3, the process of obtaining the quantitative weight W Qun,F of the fuse is as follows: determining the failure rate and the expected cost as reliability indexes through a minimum cut set, visually representing the reliability indexes, and combining through weighting coefficients; determining the quantitative weight of the ith fuse by means of the average value of the defined reliability index 。
8. The online fuse monitoring method and system based on the internet of things of claim 7, wherein the online fuse monitoring method and system based on the internet of things of claim 7 is characterized in that: The failure rate is determined by a failure frequency index Indicating the failure frequency index Including normalized failure frequency return And normalized failure frequency loss And is obtained by the following formula: In the formula, Is the total failure frequency when the ith fuse is in its operational state; For the total failure frequency when the fuse is equipped with an on-line monitoring system; is the total failure frequency when the fuse is at the maximum possible shutdown time; Is the total number of fuses; The expected cost is calculated by an expected cost index Representing an expected cost index Including expected normalized benefit index And an expected normalized loss index And is obtained by the following formula: In the formula, Is the expected cost when the fuse is considered in its operating state; For the expected cost when the fuse is equipped with an on-line monitoring system; For the expected cost when the fuse is at the maximum possible downtime.
9. The method and system for online monitoring of a fuse based on the Internet of things of claim 8, wherein the weighting coefficients are combined as shown in the following two formulas: In the formula, A final index adapted to the associated revenue at the ith fuse for on-line monitoring; Is a final loss indicator due to not performing the necessary on-line monitoring of the ith fuse; , Is that And Important factors of the index, wherein ; , Is that And Important factors of the index, wherein 。
10. The method and system for online monitoring of a fuse based on Internet of things of claim 2, wherein in the step S4, the accumulated weight W F,i of the fuse is obtained by adopting the following formula: In the formula, A quantitative weight for the i-th fuse; A normalization coefficient assigned to the quantitative weight; qualitative weights for the i-th fuse; normalized coefficient assigned for qualitative weight, wherein 。

Description

Online fuse monitoring method and system based on Internet of things Technical Field The invention relates to the technical field of intelligent monitoring, in particular to a fuse online monitoring method and system based on the Internet of things. Background The normal and safe operation of the power distribution equipment is an important support for realizing the stable operation of the power distribution network. Inherent distribution automation, because of the limited actual hardware configuration of the underlying conditions and the relatively large capital requirements, makes the overall construction requirements difficult to meet. The drop-out fuse is a short-circuit protection switch most commonly used for a 10kV distribution line branch line and a distribution transformer, has the characteristics of economy, convenience in operation, strong adaptability to outdoor environments and the like, and is widely applied to the primary side of the distribution line and the distribution transformer as protection and equipment switching operation. The conventional manual inspection has the problems of untimely operation and maintenance, poor inspection work quality, lagged management level and the like, and cannot be effectively monitored, so that the real-time operation state of each fuse can be timely obtained, certain randomness is formed in monitoring, the power supply recovery time is difficult to be ensured, and the gap between the conventional manual inspection and the management requirement of a modern power supply enterprise is large. Disclosure of Invention The invention aims to solve the technical problems that the traditional manual inspection is not timely and in place in operation and maintenance, the inspection work quality is poor, and the effective monitoring cannot be performed due to the lag of the management level. In order to solve the technical problems, the technical scheme provided by the invention is that the online fuse monitoring system based on the Internet of things is characterized by comprising a sensor module, a remote terminal module, a fuse state monitoring module, an electric power Internet of things local server module, an intelligent terminal device/APP module, a background analysis system module, a LoRaWAN module and an Internet of things cloud server; The sensor module collects real-time state signals of the fuse and transmits the signals to the remote terminal module; the fuse state monitoring module uploads the collected fuse information to a local server module of the electric power Internet of things; The intelligent terminal equipment/APP module is respectively and bidirectionally interconnected with the electric power Internet of things local server module and the background analysis system module, and is used for receiving and displaying information sent by the electric power Internet of things local server module and the background analysis system module and sending information to the electric power Internet of things local server module and the background analysis system module; The background analysis system module is respectively and bidirectionally interconnected with the electric power Internet of things local server module, and is bidirectionally interconnected with the Internet of things cloud server through the LoRaWAN module, and is used for receiving and processing information sent by the electric power Internet of things local server module and the Internet of things cloud server and sending information to the display electric power Internet of things local server module and the Internet of things cloud server. In order to solve the technical problems, the invention provides another technical scheme that an online fuse monitoring method based on the Internet of things based on the system comprises the following steps: s1, acquiring basic information of all fuses to be detected; S2, performing qualitative analysis on each fuse through a fuzzy analytic hierarchy process to obtain qualitative weight W Qul,F of each fuse; S3, quantitatively analyzing the reliability influence of the fuse, which is not suitable for qualitative analysis, in the whole system by utilizing a reliability index to obtain the quantitative weight W Qun,F of the fuse; S4, combining qualitative and quantitative weighting coefficients, determining the accumulated weight W F,i of each fuse, sequencing the accumulated weights, and determining the detection priority of the fuses according to the sequencing result. Further, in the step S1, the fuse information includes fuse drop information, fuse tube temperature information, environmental humidity information, and fuse position geographical information. Further, in the step S2, the process of obtaining the qualitative weight W Qul,F of each fuse is: 1) Determining the most important standard and the sub-standard related to the standard in the obtained fuse information, and defining the standard and the sub-standard; 2) Normalizing the d