Abstract
In order to deal with the maintenance problems of life-supporting medical instruments, and to improve their utilization, a prognostics and health management (PHM) system is designed. The implementation framework of PHM system is proposed. A experiment platform for critical components of life-supporting medical instruments is built. A fault is injected into the component. The model for critical components of medical instruments is established based on Lagrange method model. Using the reduced particle group to represent the state of the probability density function, the probability of failure in real-time can be calculated by particle filter algorithm. The simulation results match the experimental data. It diagnoses the faults and predicts the remaining useful life. Then appropriate maintenance advice can be given.
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Funding was provided by High-speed Automatic Screw-tightening Workstation (Grant No. 14cxy38).
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He, C., Wu, Y. & Chen, T. Prognostics and health management of life-supporting medical instruments. J Comb Optim 37, 183–195 (2019). https://doi.org/10.1007/s10878-017-0218-x
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DOI: https://doi.org/10.1007/s10878-017-0218-x