Emission source tracing based on bionic algorithm mobile sensors with artificial olfactory system

The leakage of hazardous chemicals and toxic volatile substances in the atmosphere may cause serious consequences such as explosion and poisoning. To identify the unknown leakage locations and gas compositions, a mobile robot system to trace the leak source in the outdoor was investigated. First, two bionic searching algorithms, Zigzag and Silkworm algorithms, were tested with outdoor experiments for locating the leak source. The results showed that the locating errors of these two algorithms were within 0.5 m in 10 by 20 m search space, but the failing ratio of Zigzag and Silkworm algorithm was still high (about 40-50%). Therefore, an improved tracing algorithm combining the Silkworm and Zigzag algorithm, called as zigzag-Silkworm algorithm, was proposed. Compared with Silkworm and Zigzag algorithms, zigzag-Silkworm algorithm had a higher success ratio of 80% in outdoor source tracing tests, and the searching efficiency was enhanced, the efficiency parameter L: L ( 0 ) has improved from 2.58 for Silkworm and 2.66 for Zigzag to 2.17 for zigzag-Silkworm. Then, in order to identify the composition of the leaked gases during the source tracing, an artificial olfaction system (AOS) based on the gas sensor array and support vector machine was set on the mobile robot. The test results in the source tracing experiments with ammonia and ethanol emissions indicated that the recognition accuracy of emission gases reached to 99% with AOS equipped on the robot. Therefore, the mobile robot system equipped with the zigzag-Silkworm algorithm and the AOS is feasible to trace the leakage source and identify the emission composition in the outdoor leakage event with good performance in efficiency and accuracy although some underlying problems still need to be addressed in future work.

Automated summary

This study investigates a mobile robot system for tracing outdoor leak sources. The system utilizes two bionic searching algorithms and an artificial olfaction system to identify the composition of leaked gases. The results show that the improved algorithm achieves good performance in locating and searching efficiency.