Application of VOC Monitoring Technologies and BP Neural Network Prediction Models in Ship Painting Workshops

Abstract

The problem of VOCs(volatile organic compounds) pollution is one of the significant challenges encountered in China's environmental protection. Controlling and reducing the emission of VOCs is not only a requirement of the increasingly strict environmental protection standards but also an inherent requirement for building a green production system in the shipbuilding industry. The monitoring of VOCs in different environments entails differences in terms of connotations, monitored elements and monitoring methods, which can lead to confusion. In this paper, the relevant concepts of VOC monitoring and concentration distribution were clarified. Based on the specific working conditions of a certain shipyard's painting workshop, a monitoring scheme for VOCs emissions from the ship's painting workshop was provided, as well as the application of PID sensor technology and the composition of an online monitoring system in the VOCs monitoring scenario. A neural network approach was utilized to construct a relationship model between the VOCs data collected at a monitoring point and the VOCs data from any location within the painting workshop space. Data support was provided for the implementation of a connected green manufacturing workshop.

Keywords

• vocs monitoring; ship painting workshop; vocs concentration distribution; pid sensor; bp neural network