Review of Fault-tolerant Control for Motor Inverter Failure with Operational Quality Considered

In recent years,motor drive systems have garnered increasing attention due to their high efficiency and superior control performance.This is especially apparent in aerospace,marine propulsion,and electric vehicles,where high performance,efficiency,and reliability are crucial.The ability of the drive system to maintain long-term fault-tolerant control(FTC)operation after a failure is essential.The likelihood of inverter failures surpasses that of other components in the drive system,highlighting its critical importance.Long-term FTC operation ensures the system retains its fundamental functions until safe repairs or replacements can be made.The focus of developing a FTC strategy has shifted from basic FTC operations to enhancing the post-fault quality to accommodate the realities of prolonged operation post-failure.This paper primarily investigates FTC strategies for inverter failures in various motor drive systems over the past decade.These strategies are categorized into three types based on post-fault operational quality:rescue,remedy,and reestablishment.The paper discusses each typical control strategy and its research focus,the strengths and weaknesses of various algorithms,and recent advancements in FTC.Finally,this review summarizes effective FTC techniques for inverter failures in motor drive systems and suggests directions for future research.

The Work of JTCA in Standardizing and Improving the Quality of Operating Information in Japan

Main Activities of JTCA JTCA activities cover the following five areas: ……

Impact factors and improvement measures of enviroment quality in cleaning operating room

Objective To analyze the factors that impact the environment quality of cleaning operating room and to discuss improvement measurement. Methods Environment bacteria testing results and prevalence of surgical incision infection in cleaning operating room were retro-

Application research of multivariate linkage fluctuation analysis on condition evaluation in process industry

Abnormal conditions are hazardous in complex process systems, and the aim of condition recognition is to detect abnormal conditions and thus avoid severe accidents. The relationship of linkage fluctuation between monitoring variables can characterize the operation state of the system. In this study,we present a straightforward and fast computational method, the multivariable linkage coarse graining(MLCG) algorithm, which converts the linkage fluctuation relationship of multivariate time series into a directed and weighted complex network. The directed and weighted complex network thus constructed inherits several properties of the series in its structure. Thereby, periodic series convert into regular networks, and random series convert into random networks. Moreover, chaotic time series convert into scale-free networks. It demonstrates that the MLCG algorithm permits us to distinguish, identify, and describe in detail various time series. Finally, we apply the MLCG algorithm to practical observations series, the monitoring time series from a compressor unit, and identify its dynamic characteristics. Empirical results demonstrate that the MLCG algorithm is suitable for analyzing the multivariable linkage fluctuation relationship in complex electromechanical system. This method can be used to detect specific or abnormal operation condition, which is relevant to condition identification and information quality control of complex electromechanical system in the process industry.

Influence of staff number and internal constellation on surgical site infection in an operating room

Prediction of bacteria-carrying particle （BCP） dispersion and particle distribution released from staffmem- bers in an operating room （OR） is very important for creating and sustaining a safe indoor environment. Postoperative wound infections cause significant morbidity and mortality, and contribute to increased hospitalization time. Increasing the number of personnel within the OR disrupts the ventilation airflow pattern and causes enhanced contamination risk in the area of an open wound. Whether the amount of staffwithin the OR influences the BCP distribution in the surgical zone has rarely been investigated. This study was conducted to explore the influence of the number of personnel in the OR on the airflow field and the BCP distribution. This was performed by applying a numerical calculation to map the airflow field and Lagrangian particle tracking （LPT） for the BCP phase. The results are reported both for active sampling and passive monitoring approaches. Not surprisingly, a growing trend in the BCP concentration （cfu/ms） was observed as the amount of staff in the OR increased. Passive sampling shows unpredictable results due to the sedimentation rate, especially for small particles （5-10 i^m）. Risk factors for surgical site infections （SSls） must be well understood to develop more effective prevention programs.