Intelligent general module design for machinery fault diagnosis

Electric power fault happens suddenly, so fault monitoring requirements of power plant and power equipment become increasingly strict. It not only needs the continuous power supply of the vessel even in the worst environment, but also requires the normal and stable work of equipment in complex conditions. Through the analysis of the advantages and disadvantages of fuzzy logic, neural network and expert system respectively, we establish a fault-diagnosis expert system with fuzzy neural network. Furthermore, we study the conventional method of data collection, and as single-chip microcomputer data acquisition system lacks data processing ability, we put forward a multi-channel data acquisition solution, which uses Field Programmable Gate Array, FPGA, with appropriate logic to control the A/D chip. This system design has been applied to the real-time monitoring and fault diagnosis of ship operation condition, and has greatly improved the safety and automation level of ship navigation. © 2016, UK Simulation Society. All rights reserved.