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Tunnel safety monitoring system based on big data

A technology of safety monitoring and big data, applied in the field of safety detection, can solve the problems of difficult to accurately reflect the abnormal data changes of magnetic flux leakage and easy to cause safety accidents.

Pending Publication Date: 2022-06-21
国网甘肃省电力公司兰州供电公司 +3
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  • Description
  • Claims
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Problems solved by technology

[0002] Existing pipeline magnetic flux leakage solutions for power systems use data collection methods at equal time intervals, which is difficult to accurately reflect the current abnormal data changes of magnetic flux leakage, which is likely to cause safety accidents

Method used

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  • Tunnel safety monitoring system based on big data
  • Tunnel safety monitoring system based on big data
  • Tunnel safety monitoring system based on big data

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Embodiment Construction

[0095] It should be understood that the specific embodiments described herein are only used to explain the present invention, but not to limit the present invention.

[0096] S1: Determine the influencing factors of the magnetic flux leakage detection of the power system tunnel, and determine the fluctuation degree of the tunnel voltage data based on the influencing factors of the magnetic flux leakage detection of the power system tunnel.

[0097] In the step S1, the fluctuation degree of the tunnel data is determined based on the influence factors of the power system tunnel flux leakage detection, including:

[0098] In a specific embodiment of the present invention, the present invention sets a magnetic sensor and a wireless router in the power system tunnel, and the magnetic sensor performs the collection of voltage data in the tunnel according to the set collection time interval to obtain a number of tunnel voltage data. The tunnel safety detection device Taking the k col...

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Abstract

The invention relates to the technical field of safety monitoring, and discloses a tunnel safety monitoring system based on big data, which comprises a sensor, a wireless router and a tunnel safety monitoring device, and discloses a tunnel safety monitoring method based on big data, and the method comprises the steps: determining tunnel magnetic flux leakage detection influence factors of a power system, determining the fluctuation degree of the tunnel voltage data based on the power system tunnel magnetic flux leakage detection influence factors; dynamically adjusting the acquisition time interval of the tunnel voltage data according to the determined fluctuation degree; acquiring tunnel voltage data by using the adjusted acquisition time interval to form tunnel time sequence data; and performing similarity comparison on the preprocessed tunnel time sequence data and the time sequence without magnetic flux leakage, and if the similarity is higher than a threshold value, indicating that no magnetic flux leakage occurs. According to the method, by dynamically adjusting the acquisition time interval, the problem that the tunnel voltage data acquisition interval is disordered due to fluctuation signals and disturbance signals in the tunnel is avoided.

Description

technical field [0001] The invention relates to the technical field of security detection, and in particular, to a tunnel security monitoring system based on big data. Background technique [0002] The existing solution for MFL of power system pipeline adopts the data collection method of equal time interval, which is difficult to accurately reflect the current abnormal data changes of MFL, which is easy to cause safety accidents. Aiming at this problem, this patent proposes an efficient collection method for abnormal data of MFL detection in power system pipelines based on sparse sampling. By adopting a double judgment method, the fluctuation degree of the MFL detection disturbance signal is judged, and the adjustment of the time interval of MFL detection data collection is excluded. Then, according to the proportional relationship between the data collection interval and the data change, dynamically adjust the change scale of the data collection time interval, so as to rea...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N27/83G01R19/00
CPCG01N27/83G01R19/0084
Inventor 刘滨邵必飞杨郭明刘春苟军景宁黄贵武苏伟强
Owner 国网甘肃省电力公司兰州供电公司
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