Matlab-Based Fault Diagnosis of Industrial Rotor-Bearing Systems

Mahesh Joshi, K. Pujar
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Abstract

Continuous monitoring of critical rotor-bearing systems is crucial in order to prevent machine downtime, which would otherwise lower the overall output and quality. Complex modern machinery demands an upgraded intelligent fault diagnosis method that leaves minimal room for human error. This paper presents a MATLAB-based condition monitoring and fault diagnosis method for rotating machines used in sugar factories. The vibration responses are acquired through the use of data acquisition and the fast Fourier transform (FFT) analyser on real industrial machines. These signals are supplied as the input to a specially developed MATLAB program for processing in order to detect the fault and help to suggest remedies. The simple and user-friendly approach saves time and increases the effectiveness of condition monitoring in the reduction of downtime and the avoidance of catastrophic failure in industrial machines.
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基于matlab的工业转子-轴承系统故障诊断
持续监测关键的转子-轴承系统是至关重要的,以防止机器停机,否则会降低整体产量和质量。复杂的现代机械需要一种升级的智能故障诊断方法,以尽量减少人为错误的空间。提出了一种基于matlab的糖厂旋转机械状态监测与故障诊断方法。利用数据采集和快速傅立叶变换(FFT)分析仪在实际工业机器上获取振动响应。这些信号作为输入提供给一个专门开发的MATLAB程序进行处理,以检测故障并帮助提出补救措施。简单和用户友好的方法节省了时间,提高了状态监测的有效性,减少了停机时间,避免了工业机器的灾难性故障。
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