Time-dependent behavior of rock mass is important for long-term stability analysis in rock engineering. Extensive studies have been carried out on the creep properties and rheological models for variable kinds of rocks, however, the effects of initial damage state on the time-dependent behavior of rock has not yet been taken into consideration. In the present study, the authors proposed a creep test scheme with controlled initial damage to investigate the influence of initial damage on the time-dependent behavior of sandstone. In the test scheme, the initial states of damage were first determined via unloading the specimen from various stresses. Then, the creep test was conducted under different stress levels with specific initial damage. The experimental results show that there is a stress threshold for the initial damage to influence the behavior of the rock in the uniaxial compressive creep tests, which is the stress threshold of dilatancy of rock. When the creep stress is less than the stress threshold, the effect of the initial damage seems to be insignificant. However, if the creep stress is higher than the stress threshold, the initial damage has an important influence on the time-dependent deformation, especially the lateral and volumetric deformation. Moreover, the initial damage also has great influence on the creep failure stress and long-term strength, i.e., higher initial damage leading to lower creep failure stress and long-term strength. The experimental results can provide valuable data for the construction of a creep damage model and long-term stability analysis for rock engineering.

Inter-turn short circuit (ITSC) is a frequent fault of interior permanent magnet synchronous motors (IPMSM). If ITSC faults are not promptly monitored, it may result in secondary faults or even cause extensive damage to the entire motor. To enhance the reliability of IPMSMs, this paper introduces a fault diagnosis method specifically designed for identifying ITSC faults in IPMSMs. The sparse coefficients of phase current and torque are solved by clustering shrinkage stage orthogonal matching tracking (CcStOMP) in the greedy tracking algorithm.The CcStOMP algorithm can extract multiple target atoms at one time, which greatly improves the iterative efficiency. The multiple features are utilized as input parameters for constructing the random forest classifier. The constructed random forest model is used to diagnose ITSC faults with the results showing that the random forest model has a diagnostic accuracy of 98.61% using all features, and the diagnostic accuracy of selecting three of the most important features is still as high as 97.91%. The random forest classification model has excellent robustness that maintains high classification accuracy despite the reduction of feature vectors, which is a great advantage compared to other classification algorithms. The combination of greedy tracing and the random forest is not only a fast diagnostic model but also a model with good generalisation and anti-interference capability. This non-invasive method is applicable to monitoring and detecting failures in industrial PMSMs.