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- W147374706 abstract "The main types of existing Condition Monitoring methods (MCSA, GA, IAS) for electrical drives aredescribed. Then the steps for the design of expert systems are presented: problem identification and analysis, system specification, development tool selection, knowledge based, prototyping and testing. The employment of SOMA (Self-Organizing Migrating Algorithm) used for the optimization of ambientvibration energy harvesting is analyzed. The power electronics devices are becoming smaller in size and consume less power so they are well suited for ambient vibration conversion systems for charging batteries or supplying power directly. The springless resonance mechanism has a mechanical part (mass, spring, damper), an electromagnetic energy converter (coils) and electrical load. SOMA is an artificial intelligence algorithm which is used to find the best combination of independent parameters tooptimize the device and obtain the maximum amount of electrical power. Future research will be doneto improve the quality factor of the model and to use it for a new harvester design for wirelessapplications." @default.
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- W147374706 date "2012-03-01" @default.
- W147374706 modified "2023-09-27" @default.
- W147374706 title "Artificial intelligence-based condition monitoring for practical electrical drives" @default.
- W147374706 hasPublicationYear "2012" @default.
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