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The application discloses a method for analyzing inter-turn short circuit fault characteristics of a parallel winding permanent magnet synchronous motor, and comprises the following steps: step one, obtaining the parameter relationship of each branch circuit according to the equivalent circuit of the PCW PMSM under the ITSC; step two, selecting the negative sequence voltage component, the three-order harmonic of the phase current and the circulating current as the fault characteristics and constructing the model of the negative sequence voltage, the three-order harmonic of the phase current and the circulating current; step three, analyzing the influence of the parallel winding on the ITSC characteristics according to the model of the negative sequence voltage component, the three-order harmonic of the phase current and the circulating current, then analyzing the influence of the fault mode on the phase current and phase voltage characteristics and the influence of the short circuit position on the phase current and phase voltage characteristics according to the model of the negative sequence voltage and the three-order harmonic of the phase current, and finally analyzing the circulating current fault characteristics according to the model of the circulating current. The method has the beneficial effects that the winding configuration, the fault mode and the short circuit position of the ITSC characteristics can be accurately detected, and the evaluation accuracy of the ITSC is improved.

This application discloses methods, apparatus, equipment, and media for interlaboratory quality assessment or data analysis in medical laboratories, relating to the field of medical laboratory testing technology. The methods include: generating a corresponding reference standard deviation based on randomly generated reference target values ​​and reference coefficients of variation; performing normal distribution random sampling to obtain reference reported values; linearly fitting the reference target values ​​and reference reported values ​​to obtain reference coefficients of determination; determining a new step size for the reference coefficient of variation to initiate a new external loop until the external loop ends; generating relative coefficients of variation based on the reference standard deviation; constructing a target mapping relationship matrix between each relative coefficient of variation and the reference coefficient of determination; determining the target relative coefficient of variation based on the target mapping relationship matrix and using the actual coefficients of determination of each actual sample; and obtaining the target sigma metric value using the target relative coefficient of variation, thereby obtaining the analytical and quantitative results of the actual interlaboratory quality assessment. This improves the accuracy and efficiency of interlaboratory quality assessment analysis.