Fault Prediction and Health Management Solution

Prognostics and Health Management (PHM) is a health management technology that uses advanced sensor integration and various algorithms and models to achieve fault detection, state evaluation and fault prediction. It has been widely used in the military and civilian fields, and has played an important role in improving equipment availability, reliability and safety, and reducing operation and maintenance costs.

PHM uses intelligent algorithms to comprehensively analyze the real-time monitoring data of equipment, detect abnormal performance and early failure of equipment in real time, evaluate the health status of equipment, and predict the remaining useful life of equipment, which provides important technical support for equipment to realize independent health management, Condition based Maintenance (CBM) and intelligent guarantee.
 

On the basis of using advanced sensor technology to obtain the operating status data of industrial equipment, PHM comprehensively uses intelligent algorithms and models to mine and analyze industrial big data with hidden, fragmented and low-quality characteristics, obtains quantitative knowledge of the health status of industrial equipment, and provides support for the optimization of equipment operation and maintenance support.

For the fault that can be monitored, its evolution process can be represented by the monitoring parameters or the development trajectory of the extracted characteristic values, which provides the basis for the time to failure (TTF) prediction.

baseline model:the temperature deviation value sequence is obtained through the performance baseline, and the temperature anomaly is very obvious.

mechanism model:, the motion process of aircraft landing gear landing phase is regarded as a damping vibration process, and the corresponding damping vibration equation is established.

ML:can be seen to follow a bimodal distribution, so it can be assumed that this is due to different operating conditions.