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In this article, a new data-driven diagnosis method is proposed for mixed eccentricity (ME) in the external rotor permanent magnet motors (ERPMMs). Differently from the previous articles, the proposed method has the advantages of large sample size, high sample diversity, high efficiency, and strong generalization ability. First, the improved parametric analytical model (AM) of back electromotive force (EMF) of the ERPMMs is established. Then, the characteristics of the back EMF are analyzed. Accordingly, its amplitudes of fundamental waves and sideband harmonics are selected as the ME indexes. Afterwards, by using the proposed parametric AM, a database of ME signals is established efficiently, which contains tens of thousands of labeled samples. Furthermore, based on the back propagation neural network, a high-precision diagnosis model for ME in the ERPMM is established. Interference faults, such as unbalanced stator windings and uneven magnetization are also discussed. Finally, an experimental prototype for simulating the ME is manufactured and the effectiveness of the proposed method is verified. The maximum absolute diagnostic error is less than 4.0%. It provides a new idea for multiparameter diagnosis for ME.

Although the increase in the frequency of mass wasting events in the Sedongpu gully in recent years indicates that the Sedongpu gully has entered an intense mass wasting period, the current literature focuses only on ice‒rock avalanche events and lacks comprehensive knowledge of Sedongpu gully activity. To clarify the spatiotemporal distribution and scales of mass wasting events, we analysed multiple images from 1969 to present (including optical images and synthetic aperture radar (SAR) images) and topography data from 2013 to present. Since 1969, there have been at least 19 obvious mass wasting events that can be divided into 3 subpatterns: ice‒rock avalanches (IRAs, 8 events), ice‒moraine avalanches (IMAs, 2 events), and glacier debris flows (GDFs, 9 events). Since 2017, the Sedongpu gully has entered the most active period, i.e. more than 68% of events occurred after 2017, and approximately 530 Mm3and 185 Mm3of materials were removed from mixtures of glacial and moraine (MGM) and glacial source areas (GSAs). Recent continuous warning states that the temperature of the Sedongpu gully area exceeded 0 °C from April to July 2012, and the 2017 Mw6.4 Nyingchi earthquake was critical in the current intense erosion state.

The influence of hub motor unbalanced magnetic force (UMF) on the vibration of electric vehicle under steady state conditions has been known, but under unsteady conditions, the hub motor UMF will change with the vehicle operation condition, and there would exist complex coupling vibration for the hub motors driven electric vehicle. Here, the longitudinal-vertical coupling dynamics of the four hub motors driven electric vehicle under unsteady condition is studied. Integrating the motor electromagnetic excitation and electric vehicle dynamics, a longitudinal-vertical coupling dynamics model of the four hub motors driven electric vehicle is established. Based on the variable switching frequency field-oriented control model, analytical model of the UMFs acting on the motor stator and rotor parts under unsteady condition are developed. For model validation, a four hub motors driven electric vehicle has been tested, the accuracy of the longitudinal-vertical coupling dynamics model established in this paper was verified. Then, longitudinal-vertical coupling vibration characteristics of the four hub motors driven electric vehicle under road excitation and coupling excitation are analyzed. The results show that the longitudinal and vertical movement of the four hub motors driven electric vehicle is coupled by hub motor. In addition, under unsteady condition, the motor UMFs will cause vertical vibration of the electric vehicle body and hub motor stator, the vibration shows order characteristics including low order harmonic hfcand inverter switching frequency sideband harmonic k1fs±k2fc(fc= pn/60, fsis inverter switching frequency, k1and k2are positive integers, pis the number of pole pairs and nis motor speed.). The motor electromagnetic torque will cause longitudinal vibration of the electric vehicle body, the vibration shows order characteristics including harmonics fs±3fcand 2fs. The main harmonic of vehicle body pitch angle acceleration is 2fs.