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An on-line model update scheme is developed to adapt the Markov process changes to machine health dynamics quickly.
After that, frequency spectrum growth index (FSGI) is proposed to serve as a quantitative description of machine health condition.
Bayesian inference-based probability (BIP) derived from the baseline SOM is developed as a quantification indication of machine health degradation.
Zhao, R. Deep learning and its applications to machine health monitoring.
Recently, deep learning algorithms have been applied widely in machine health monitoring.
A novel framework for remote machine health condition monitoring was then developed via the proposed algorithm and the advancements in wireless communication.
Similar(29)
Implemented by the municipal body, the mission aimed to boost the capacity of diagnostic machines, health workers and treatment facilities in the city, and was the first programme of its kind in the India.
A majority of these devices will be industrial equipment and machinery such as jet engines, vending machines, health monitoring systems, and other industry-specific devices.
A case study was used in the implementation of the developed system, and the results show that it can monitor the machine's health condition effectively by displaying machines' health status, gives repair suggestions to probable faults, decides strategy for both production methods and maintenance, and, thus, can enhance maintenance performance obviously.
The production and machine condition monitoring software (PMCMS) was developed to aid in monitoring the condition of production machines, suggesting production strategies to adopt, computing market share values, cost of production after certain parameters have been specified, and displaying the status of the machines' health behavior over a specified period of time.
After validation, the FFNN was applied to predict the machine component health of individual units.
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