基于FNN算法的机械设备远程故障检测系统研究

Research on remote fault detection system of mechanical equipment based on FNN algorithm

模糊神经网络越来越受到学者的关注,许多专家预测模糊的神经网络技术很可能成为21世纪智能管理领域的核心技术。为解决硬件故障诊断过程中的非线性输入问题,设计了一种基于FNN算法的硬件诊断系统。文章结合实际需求,构建了数据采集系统、电信数据系统和远程控制成像系统的相关硬件系统,并使用MATLAB作为编程软件开发了相应的测试模块,以了解机械设备的远程分析。系统开发完成后,对数据进行仿真、实验室测试和现场试验,可以连续正确地传输数据,并可以实时检测设备的运行状态,从而确定系统的可行性。

Fuzzy neural network is attracting more and more attention from scholars.Many experts predict that fuzzy neural network technology is likely to become the core technology in the field of intelligent management in the 2lst century.In order to solve the nonlinear input problem in the hardware fault diagnosis process,a hardware diagnosis system based on FNN algorithm is designed.In this paper,combined with the actual requirements,the data acquisition system,telecommunications data system and remote control imaging system related hardware system,and the use of MATLAB as programming software to develop the corresponding test module,to understand the remote analysis of mechanical equipment.After the system development is completed,the data can be simulated,laboratory test and field test,and the data can be continuously and correctly transmitted,and the running state of the equipment can be detected in real time,so as to determine the feasibility of the system.