An overview of diagnostics and prognostics of rotating machines for timely maintenance intervention

Abstract

Failure of mechanical system can primarily be attributed to failure of timely intervention by the maintenance crew. Mechanical failure of mechanical system is mostly attributed to damage to mechanical systems due to wearing of mechanical components due to improper lubrication. Various instruments and systems are generally installed to monitor the condition of mechanical systems like steam turbines especially where reliability of system is critical like nuclear plants. This is commonly termed as ‘Condition Monitoring’. It involves continuous monitoring of health of rotating machines say steam turbine system. Instruments installed to monitor the health of machines are designed to provide an alarm through Distributed Control Systems, which are followed by a series of machine tripping systems thus keeping the operator free from the task of manually tripping the systems. The unexpected anomalies of instruments along its abnormal behaviour of equipment, decreases the availability of the machine. Condition based Monitoring (CBM) is critical to nuclear industry and it is done to gather data about the health of a machine and then analysing that data by taking proper maintenance action on components under abnormal behaviour. The information from the plant operations and maintenance i.e. real time data is key to monitoring the health of said rotating machine. Thus, CBM techniques increase the reliability of the machine by accurately estimating the condition of critical components in real-time especially in case of rotating machines in a nuclear plant. This paper discusses the diagnostics and prognostics of rotating machines using analysis of lubricants and bearings as these components are inevitable to any rotating machine.