CN-121981514-A - Automatic high-altitude cable inspection system based on multidimensional decision algorithm

CN121981514ACN 121981514 ACN121981514 ACN 121981514ACN-121981514-A

Abstract

The invention relates to the technical field of intelligent monitoring of communication facilities, in particular to an automatic high-altitude cable inspection system based on a multi-dimensional decision algorithm, which is used for collecting equipment data of an Internet of things and various subsystem data and cleaning the data, wherein the multi-dimensional decision module is used for acquiring the data of the data collecting and processing module so as to evaluate the equipment state of the Internet of things, the cable risk and the regional risk, the alarm and automatic dispatch module is used for giving an accident alarm for generating the cable risk and dispatching a work order to corresponding operation and maintenance personnel according to the matching degree of the information of the operation and maintenance personnel and the cable risk accident, and the thermodynamic diagram generating module is used for generating a thermodynamic diagram. The invention realizes the automatic inspection of the communication cable and other similar high-altitude cables by utilizing a multidimensional decision algorithm, reduces the communication interruption risk, reduces the response time after the cable accident occurs, and reduces the financial loss and the casualties caused by the accidents such as falling, electricity leakage and the like after the cable is broken.

Inventors

TAN ZHENG
MA XUELIN
LIANG FENG
WENG XIANG
Guo Kexian
LEI JUN

Assignees

广西壮族自治区公众信息产业有限公司

Dates

Publication Date: 20260505
Application Date: 20251202

Claims (10)

1. An automatic high-altitude cable inspection system based on a multi-dimensional decision algorithm is characterized by comprising a data collection and processing module (1), a multi-dimensional decision module (2), an alarm and automatic dispatch module (3) and a thermodynamic diagram generation module (4), The data collection and processing module (1) is used for collecting the data of the equipment of the Internet of things and various subsystem data, and the data collection and processing module (1) is also used for cleaning the data of the equipment of the Internet of things and the various subsystem data so as to obtain standard data; the multidimensional decision module (2) is used for acquiring the data of the data collection and processing module (1) so as to evaluate the equipment state, the cable risk and the regional risk of the Internet of things; The alarming and automatic dispatching module (3) is used for acquiring data of the multidimensional decision module (2), the alarming and automatic dispatching module (3) generates accident alarming according to the cable risk, and the alarming and automatic dispatching module (3) dispatches a work order to corresponding operation and maintenance personnel according to the matching degree of the operation and maintenance personnel information and the cable risk accident; The thermodynamic diagram generation module (4) is used for data acquisition of the multi-dimensional decision module (2) and the alarming and automatic dispatch module (3) so as to generate thermodynamic diagrams with different color levels according to the regional accident probability.
2. The automatic high-altitude cable inspection system based on the multi-dimensional decision algorithm of claim 1, wherein the data of the Internet of things equipment comprises cable vibration amplitude and cable position change detected by a falling detector, and leakage current and voltage detected by a leakage detector; The data of various subsystems comprise environmental parameters in a weather information management system, wherein the environmental parameters comprise wind speed, humidity, air temperature and historical extreme weather data, and skill labels of operation and maintenance personnel in an operation and maintenance personnel management system, matching degree with fault types and historical similar work order processing time length data.
3. The automatic high-altitude cable inspection system based on the multi-dimensional decision algorithm according to claim 2, wherein the data cleaning of the data collection and processing module (1) comprises false alarm detection and repeated alarm detection, The false alarm detection judges whether the detection data of the falling detector and the electric leakage detector belong to false alarm or not according to the change of the measured value in unit time; And comparing the difference value of the equipment ID and the alarm time stamp with a third time window to judge whether the alarm belongs to the repeated alarm.
4. The automatic high-altitude cable inspection system based on a multi-dimensional decision algorithm according to claim 3, wherein a first time window, a vibration amplitude threshold and a false alarm judgment number threshold are set for the falling detector in false alarm detection, the number of times that vibration amplitude exceeds the vibration amplitude threshold is counted and obtained in the first time window, and false alarm is judged when the number of times that the vibration amplitude exceeds the vibration amplitude threshold is larger than the false alarm judgment number threshold: Formula (1), Wherein, the The unit is second for the first detection moment; For a first time window, in seconds; is a vibration amplitude threshold; a threshold value for false alarm judgment times; In the false alarm detection, a leakage current threshold and a false alarm duration threshold are set for the leakage detector, the fluctuation times are counted in a second window time, and when short abnormal fluctuation occurs for many times in a short time, false alarm is judged: Formula (2), Wherein, the Is a leakage current threshold; is a false positive duration threshold; Is the first The secondary detected leakage current value; Is the first The duration of the secondary leakage current exceeding the leakage current threshold; the total detection times in the second window time are obtained; and in order to trigger the fluctuation frequency threshold value of false alarm judgment, judging that false alarm occurs when short abnormal fluctuation occurs for a plurality of times in a short time.
5. The automatic high-altitude cable inspection system based on the multi-dimensional decision algorithm of claim 3, wherein in the repeated alarm detection, when the device IDs are the same and the difference between the two alarms is smaller than a set third time window, the repeated alarm is determined as: formula (3), Wherein, the The judgment result is repeated alarming; is a third time window; Is a device ID; is the difference between the two alarm times.
6. The automatic high-altitude cable inspection system based on the multi-dimensional decision algorithm of claim 2, wherein in the cable risk assessment of the multi-dimensional decision module (2), the multi-dimensional decision module (2) calculates real-time risk coefficients of cables according to the data of the internet of things equipment and various subsystem data through a risk assessment algorithm: Equation (4), Wherein, the The real-time risk coefficient of the cable; weighting the amplitude of the cable to the risk value; weighting the risk value for the current of the cable; the weight of the environmental risk coefficient to the risk value; For the ratio of the vibration amplitude to exceed the threshold value, ; For the proportion of leakage current exceeding the threshold value, ; Is an environmental risk coefficient; the environmental risk coefficient is as follows: Equation (5), Wherein, the Is the weight of wind speed; is the weight of humidity; weights for historic extreme weather; Real-time wind speed detected for the device; real-time air humidity detected for the device; in the weather information database, the number of times extreme weather occurs in the region where the equipment is located.
7. The automatic high-altitude cable inspection system based on the multi-dimensional decision algorithm of claim 6 is characterized in that in the regional risk assessment of the multi-dimensional decision module (2), cables are divided according to administrative areas or functional areas, and the multi-dimensional decision module (2) calculates and obtains a regional risk coefficient according to real-time risk coefficients and regional characteristics of single cables: Equation (6), Wherein, the Is a patch risk coefficient; The weight of the cable risk average value in the area; Weighting the extreme risk values; Weight for cable density; Weight for cable density; Grabbing extreme risk points for the highest risk value in the region; is the cable density within the area.
8. The automatic high-altitude cable inspection system based on the multi-dimensional decision algorithm of claim 7, wherein in the alarming and automatic dispatch module (3), when the real-time risk coefficient of the cable and the zone risk coefficient are larger than corresponding alarming thresholds, accident alarming is generated according to the data of the multi-dimensional decision module (2).
9. The automatic high-altitude cable inspection system based on the multi-dimensional decision algorithm of claim 7, wherein the thermodynamic diagram generation module (4) aggregates single-cable risk values into geographic grid risk values according to the real-time cable risk coefficients and the segment risk coefficients, and the thermodynamic diagram generation module (4) displays the visual risk levels in different colors through a GIS technology.
10. The automatic high-altitude cable inspection system based on the multi-dimensional decision algorithm of claim 7, wherein in the alarm and automatic dispatch module (3), when the historical data of the type of faults is insufficient, the total matching degree is calculated through the skill condition of operation and maintenance personnel and the speed of processing the similar faults: equation (7), Wherein, the The overall matching degree between operation and maintenance personnel and accidents is achieved; similarity of skill types owned by the operation and maintenance personnel and skills required by the accident; The similarity between the average accident handling speed and the ideal accident handling speed for operation and maintenance personnel; Weights for skill similarity; the weight of the speed similarity is processed for the accident; for operation and maintenance personnel Skill score for class fault; Is that Skills requirements of the class faults are divided; for handling operation and maintenance personnel Average speed of class failure; Is that Ideal speed of the class fault; When the historical data of the type of faults are sufficient, the matching degree calculation method is that: equation (8), Wherein, the Matching degree between operation and maintenance personnel and current accidents; skill matching scores for the operation and maintenance personnel for the type of accidents; the processing speed score of the operation and maintenance personnel on the accidents is higher, and the processing speed is higher as the value is larger; Weights for skill similarity; The weight of the accident handling speed; the average speed of handling the type of accidents for operation and maintenance personnel; historical optimal values for handling similar incidents; for handling the same kind of incidents, the longest time is acceptable.

Description

Automatic high-altitude cable inspection system based on multidimensional decision algorithm Technical Field The invention relates to the technical field of intelligent monitoring of communication facilities, in particular to an automatic high-altitude cable inspection system based on a multidimensional decision algorithm. Background In the field of high-altitude cable inspection, the traditional operation and maintenance method has a remarkable technical bottleneck. The current mainstream scheme relies on manual inspection or fixed camera monitoring to face three core challenges, namely firstly, the problem that extreme environment detection fails, such as the problem that in the weather of heavy rain, strong wind and the like, the camera vision is fuzzy or the power supply of equipment is interrupted, weak electric leakage (such as 5 mA-level current abnormality caused by breakage of an insulating layer) and slight vibration change of a cable cannot be identified, secondly, the problem that a traditional system is based on geographical position dispatch, neglects key dimensions such as skill matching degree of operation staff, historical processing efficiency (such as failure average time) and the like, and causes the problems that repeated dispatch rate is high, operation staff cannot process the work order or processing time is long and the like, thirdly, the problem that risk prejudging capability is lacking, dynamic assessment of the health state of the cable is not available, and passive response can be achieved only after failure occurs. Disclosure of Invention In order to solve the problems, the invention provides an automatic high-altitude cable inspection system based on a multi-dimensional decision algorithm, which utilizes the multi-dimensional decision algorithm to realize automatic inspection of communication cables and other similar high-altitude cables, reduces the risk of communication interruption, reduces the response time after cable accidents occur, and reduces financial loss and casualties caused by accidents such as falling, electricity leakage and the like after cable breakage. In order to achieve the above purpose, the technical scheme adopted by the invention is as follows: an automatic high-altitude cable inspection system based on a multi-dimensional decision algorithm comprises a data collection and processing module, a multi-dimensional decision module, an alarm and automatic dispatch module and a thermodynamic diagram generation module, The data collection and processing module is used for collecting the data of the equipment of the Internet of things and various subsystem data, and is also used for cleaning the data of the equipment of the Internet of things and the various subsystem data so as to obtain standard data; The multidimensional decision module is used for acquiring data of the data collecting and processing module so as to evaluate the equipment state, the cable risk and the regional risk of the Internet of things; The alarming and automatic dispatching module is used for acquiring data of the multi-dimensional decision module, generating accident alarming according to the cable risk, and dispatching a work order to corresponding operation and maintenance personnel according to the matching degree of the operation and maintenance personnel information and the cable risk accident; The thermodynamic diagram generation module is used for acquiring data of the multi-dimensional decision module and the alarming and automatic dispatching module so as to generate thermodynamic diagrams with different color grades according to the regional accident probability. Further, the data of the Internet of things equipment comprise cable vibration amplitude and cable position change detected by a falling detector, and leakage current and voltage detected by a leakage detector; The data of various subsystems comprise environmental parameters in a weather information management system, wherein the environmental parameters comprise wind speed, humidity, air temperature and historical extreme weather data, and skill labels of operation and maintenance personnel in an operation and maintenance personnel management system, matching degree with fault types and historical similar work order processing time length data. Further, the data cleaning of the data collecting and processing module comprises false alarm detection and repeated alarm detection, The false alarm detection judges whether the detection data of the falling detector and the electric leakage detector belong to false alarm or not according to the change of the measured value in unit time; And comparing the difference value of the equipment ID and the alarm time stamp with a third time window to judge whether the alarm belongs to the repeated alarm. Further, in the false alarm detection, a first time window, a vibration amplitude threshold value and a false alarm judgment frequency threshold value are set for the falling de