Biblio

The transmission line tower is affected by the surface subsidence in the mined out area of coal mine, which will appear the phenomenon of subsidence, inclination and even tower collapse, threatening the operation safety of the transmission line tower in the mined out area. Therefore, a Safety and Damage Assessment Method of Transmission Line Tower in Goaf Based on Artificial Intelligence is proposed. Firstly, the geometric model of the coal seam in the goaf and the structural reliability model of the transmission line tower are constructed to evaluate the safety. Then, the random forest algorithm in artificial intelligence is used to evaluate the damage of the tower, so as to take protective measures in time. Finally, a finite element simulation model of tower foundation interaction is built, and its safety (force) and damage identification are experimentally analyzed. The results show that the proposed method can ensure high accuracy of damage assessment and reliable judgment of transmission line tower safety within the allowable error.

This scientific paper reveals an intelligent system for data acquisition for dam monitoring and diagnose. This system is built around the RS485 communication standard and uses its own communication protocol [2]. The aim of the system is to monitor all signal levels inside the communication bus, respectively to detect the out of action data loggers. The diagnose test extracts the following functional parameters: supply voltage and the absolute value and common mode value for differential signals used in data transmission (denoted with “A” and “B”). Analyzing this acquired information, it's possible to find short-circuits or open-circuits across the communication bus. The measurement and signal processing functions, for flaws, are implemented inside the system's central processing unit. The next testing step is finding the out of action data loggers and is being made by trying to communicate with every data logger inside the network. The lack of any response from a data logger is interpreted as an error and using the code of the data logger's microcontroller, it is possible to find its exact position inside the dam infrastructure. The novelty of this procedure is the fact that it completely automates the diagnose procedure, which, until now, was made visually by checking every data logger.