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

Abstract

This technical paper 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 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 BER is achieved at a communication distance of 2 m.

Design and Implementation of Remote Controlling System Using GAN in Optical Camera Communication

“…Due to the mobility image become blur [15] or its stripe pattern may deform [19]. As a result, the data decoding become very difficult.…”

“…However, their BER is quite high. On the contrary, neural blind deconvolution is used to improve the BER from blurry images, but without considering the changing position of the transmitter [15]. Our device is a remote controlling system, so we have considered motion.…”

Mesh-Based Consensus Distributed Particle Filtering for Sensor Networks

“…In a sensor network, each sensor node can collect measurements, process the data, and exchange information with its neighboring nodes under a given communication topology, making the sensor network suitable to deal with systems or processes in large scales or spatially distributed [1], [2]. Some successful practical applications can be found in forest fire detection [3], air pollution surveillance [4], [5], and industrial valve monitoring [6], etc.…”

Optimization and design of a diffuse optical wireless sensor network

“…However, due to the limitations of line-of-sight (LOS), energy-efficient network models and routing protocols must be used. In [19], an industrial monitoring system based on an optical camera communication system with an artificial neural network-based group detection mechanism for industry applications was proposed and implemented. In [20] and [21], channel modeling and characterization of indoor visible light communication for medical body-area networks were investigated.…”