Early-stage identification of indoor leakage sources in factories

Identifying the leakage source in industrial factories as soon as an incident happens is crucial for controlling the leak in time and safeguarding lives and property. This study developed a rapid source identification method for factories, aiming to identify the characteristics of leakage sources at the early stage of the leakage event. The approach integrates pollutant diffusion theory, sliding window method, correlation coefficient method, and data fitting method. Based on an experimental cabin, 162 verification conditions were established, encompassing constant sources as well as two time-varying sources: linear and non-linear ones. Additionally, various aspects of the method were evaluated. It was found that considering the error and noise in sensor monitoring data, the method exhibits identification accuracies of 83.3%, 79.6%, and 74.1% for constant sources, linear sources, and non-linear sources, respectively. In the case of non-linear sources, the coefficient “b” must be taken into account when generating the dimensionless concentration vector. A sliding window containing 50 to 60 valid data points can achieve the highest source identification accuracy. This research can provide help in quickly locating leakage sources in factories, help with the timely control of leaks, and protect workers’ health and property safety.