Research on prediction and estimation of operational states of power electronic equipment in bioreactor fields based on discrete Kalman filter algorithm and biomolecular markers
Abstract
The prediction and evaluation of the states of electronic and electrical equipment hold significant research value across various fields. Kalman filter algorithm is used to identify, predict and estimate the parameters of some electronic components in the electronic equipment are tested. Rate the common failure level, adjust the appropriate Kalman filter algorithm, to ensure that the electronic equipment is always in the best operation state, and can avoid the damage of power engineering equipment. Biological thermal response significantly impacts the thermal management of electronic devices. By simulating the thermal conductivity of biological tissues, the heat dissipation design is optimized to ensure device temperature remains below the thermal damage threshold. The expression of Heat Shock Proteins (HSP) and cell viability serve as biomarkers to evaluate the thermal effects of devices on biological tissues, enhancing safety and reliability. This paper discusses the necessity of prediction and estimation of power devices, and then combines the actual scientific research, mainly for the temperature of semiconductor power devices and the DC (Direct Current) voltage of the main circuit of the inverter, from the mathematical model, the realization of state prediction algorithm and thermal effects of devices on biological tissues. This study effectively avoids damage and failures caused by high temperatures, addresses the challenge of output voltage accuracy in complex environments, and offers new insights into equipment states estimation from a biomechanical perspective, thereby enhancing safety and reliability.
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