Continuous Status Monitoring of Industrial Valve Using OCC-Enabled Wireless Sensor Network

This technical article proposes an instrumentation valve (IV) status monitoring system based on optical camera communication (OCC). A transmitter circuit equipped with a temperature sensor is integrated into each IV. Each transmitter also includes two light-emitting diodes (LEDs) forming an LED group, where one of the LEDs is used to transmit the data. During the reception process, each LED group is recognized and classified using a neural network. Then, the LEDs are individually identified using the region-of-interest detection mechanism. A close circuit television (CCTV) camera is employed to receive the data, which are henceforth stored in a cloud server for further monitoring. An angle measurement algorithm capable of determining the angle generated due to unwanted failure related to the proper closing or opening of the IV is proposed. Additionally, a neural blind deconvolution algorithm is proposed to alleviate the blur effect in the received images. In short, the data transmitted by the LED contain information including valve ID, temperature, and the amount of inflection produced by the IV. The entire OCC system is implemented, and its performance is evaluated using Python 3.7. Data with blurry images are successfully received up to a communication distance of 10 m, whereas the lowest bit error rate (BER) is achieved at a communication distance of 2 m.