Transmission tower bolt fastening detection method and system based on long short-term memory network
A long-short-term memory and detection method technology, applied in the direction of measuring torque/torsional force, measuring force, measuring device, etc. during tightening, can solve the problems of large manpower and time, and achieve the effect of solving the problem of manpower and time
Active Publication Date: 2021-10-15
SHANGHAI ELECTRIC POWER HIGH PRESSURE IND CO LTD
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[0003] The purpose of the embodiments of the present invention is to provide a long-short-term memory network-based detection method and system for bolt fastening of transmission poles and towers, so as to solve the traditional problem of a large amount of manpower and time required for fastening detection of high-voltage transmission line bolts
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[0039] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.
[0040] In order to better understand the embodiments of the present invention, the technical terms involved in the following description are explained as follows:
[0041] Mel Frequency Cepstral Coefficients (MFCC)
[0042] Long Short-Term Memory Network (Long Short-Term Memory, LSTM)
[0043] The working principle of the embodiment of the present invention is as follows:
[0044] Based on the current situation, it has become a new idea to use t...
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The embodiment of the present invention discloses a long-short-term memory network-based bolt fastening detection method and system for transmission pole towers. The method includes: obtaining original acoustic wave data; preprocessing the original acoustic wave data to obtain processed data; dividing the processed data into Training samples and test samples; extract the formant and 13th-order MFCC features of the training samples, and construct feature vectors; train the long-short-term memory network classification model according to the feature vectors; input the test samples into the long-short-term memory network classification model for prediction to obtain predictions results, and output prediction results. Implementing the embodiment of the present invention, a set of operation methods for iron tower acoustic data collection is constructed, and machine learning technology is used to realize the detection of bolt fastening status, which solves the traditional large amount of manpower required for high-voltage transmission line bolt fastening detection and timing issues.
Description
technical field [0001] The invention relates to the technical field of audio processing, in particular to a method and system for detecting fastening of transmission tower bolts based on a long-short-term memory network. Background technique [0002] In the construction of the power transmission system, a large number of bolts are used to connect and fix different components. In such scenarios, the reliable connection and fixation of different components is particularly important, and it is a necessary measure to eliminate potential safety hazards during regular inspections of the bolts used for installation. The traditional inspection method needs to be implemented manually, and the method of working at heights or collecting images with the naked eye often has certain dangers. The method of using vision often requires the use of drone inspections, shooting on-site pictures, and using image processing and target detection related technologies to judge the fastening of bolts...
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IPC IPC(8): G01L5/24G01L1/25G01H9/00
CPCG01H9/004G01L1/255G01L5/246
Inventor 骆昊骏金春峰朱炜沈华峰王晶冯晔陆新卓亚光何渊陈伟俊
Owner SHANGHAI ELECTRIC POWER HIGH PRESSURE IND CO LTD