Automatic Damage Identification Using Wireless Sensors, Built on a Cheap Element Base
DOI:
https://doi.org/10.31649/1997-9266-2023-169-4-6-15Keywords:
real time dynamic systems, cheap wireless sensor, accelerometer, monitoring system, damage identificationAbstract
The importance of research aimed at structural monitoring of architectural constructions is determined by the density of buildings, aging and the influence of aggressive operating conditions of the environment . This work is aimed at developing of a sensor assembly, on the one hand, economically cheap and appropriate for use in monitoring systems. On the other hand, the sensor node should not be inferior to existing solutions in terms of technical characteristics and computing capabilities. First of all, the existing microprocessor and microcontroller sensor nodes were analyzed in order to select the most used architectural solutions for wireless sensor nodes. Thus, the ST Microelectronics STM32WB55CG microcontroller with a built-in wireless communication core was chosen for the sensor node prototype for the first time. A combination of three accelerometers ST Microelectronics LIS3DSH was used in one sensor node in order to increase the fault tolerance of the prototype. A distinctive feature of this work is the search and application of effective algorithms for the identification and monitoring of the state of the structure for inexpensive sensor nodes. The study proves that the use of neural network algorithms requires the presence of a large database in an intact state for training, and the time spent on both training and identification requires significant computing power from the microcontroller, which makes such algorithms unsuitable for the use in dynamic systems of real time. Therefore, a prototype of a wireless sensor was assembled, which was accordingly tested on an architectural structure near the railway to check the sensitivity of the sensor node. The research also provides comparison results of two statistical damage identification algorithms, such as Euclidean norm and Mahalanobis distance.
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