Journal Article

Multi-sensor information fusion detection system for fire robot through back propagation neural network

Ye, ZiYang, Li, KaiFeng, Zhang, JunJie

2020

Overview

To reduce the danger for firefighters and ensure the safety of firefighters as much as possible, based on the back propagation neural network (BPNN) the fire sensor multi-sensor information fusion detection system is investigated. According to previous studies, the information sources and information processing methods for the design of this study are first explained. Then, the basic structure and flowchart of the research object in this study are designed. Based on the structure diagram and flowchart, the BPNN is selected to fuse the feature layers in this study, and the fuzzy control is selected to fuse the decision layers in this study. The multi-sensor information fusion detection system collects information for the sensors first, processes the collected information, and sends it to the processor of the robot. The processor analyzes and processes the received signal, and transmits the obtained information to the control terminal through the wireless communication system. Through the tests in this study, it is found that when the number of hidden layer nodes of the BPNN is 7, the optimal training result is obtained. On this basis, the test of BPNN in this study is performed. The test results show that after 127 iterations, the error of the BPNN reaches the lowest target value, indicating that the BPNN achieves an excellent level of accuracy. The trained BPNN has a running time of 0.0276 s and a mean square error of 0.0013. The smaller the mean square error value is, the higher the accuracy of the BPNN is, which shows that the BPNN meets the high precision requirements of this study. The research on the multi-sensor information fusion detection system of fire robots in this study can provide theoretical support for the research on forest fire detection in China. Since the proposed BPNN-based robot is applied to the inspection and processing of forest remaining fire, the results are applicable to the forests of various countries, with a wide range of applications.

• Publisher: Public Library of Science,Public Library of Science (PLoS)
• Subject: Accuracy / Algorithms / Artificial neural networks / Back propagation / Back propagation networks / Biology and Life Sciences / Carbon monoxide / China / Communications systems / Data integration / Data processing / Design / Ecology and Environmental Sciences / Electrical engineering / Engineering and Technology / Environmental Monitoring - methods / Errors / Firefighters / Firefighting equipment / Flow charts / Forest & brush fires / Forest fire detection / Forest fires / Forestry research / Forests / Fuzzy control / Information processing / Information sources / Information systems / Inspection / Mean square errors / Medicine and Health Sciences / Methods / Microprocessors / Multisensor fusion / Neural networks / Neural Networks, Computer / Propagation / Research and Analysis Methods / Robotics - methods / Robots / Sensors / Signal processing / Studies / Technology application / Wildfires - prevention & control / Wireless communication systems / Wireless communications