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Rub-impact fault is one of the most common and severe failure modes for rotating machinery. Disclosing the changing dynamic in rub-impact fault signal could provide a basic foundation for rub-impact detection of rotor systems. In this study, a dynamic model of a flexible rotor system is established to simulate the rub-impact fault signal to help us understand the dynamic characteristics of rub-impact fault signal. Meanwhile, considering that an advanced time-frequency analysis method is of vital importance in an effective rub-impact fault detection method. A new time-frequency analysis algorithm termed as second order multi-synchrosqueezing transform is also proposed in this study, in which a second order two-dimensional instantaneous frequency estimation is embedded into a multi-synchrosqueezing framework. It is shown that the proposed method could produce a time-frequency representation result with a high time-frequency resolution. Assisted by the proposed method, the impulse shaped amplitude modulated phenomenon in high frequency band and the fast varying frequency modulated phenomenon around the rotation frequency and its fractional or super harmonics are clearly revealed through the analysis of rub-impact fault signals from both dynamical simulation and experimental cases.

Considering the flexibility of gear foundations and rotational effects, a geared rotor dynamic model for thin-rimmed helical gears is established. The deformable shafts and gear foundations are modelled by Timoshenko beam elements and Mindlin-Reissner shell elements, respectively. The beam element and the shell element are connected using the ‘interfacial coupling element’. Then the modal superposition method is adopted to improve the computational efficiency. The proposed dynamic model is verified through the comparison between the simulated responses and experimental results in a published literature. Based on the proposed dynamic model, the effects of the web thickness, the rotational effects and the helix angle on the dynamic behaviors are discussed. The results show that the dynamic responses of thin-rimmed gears obtained from the traditional dynamic model and the proposed model are quite different, which emphasizes the significances of the flexible body modeling. Compared to the centrifugal stiffening and the spin softening, the gyroscopic effect has more significant effect on dynamic characteristics. The nodal diameter vibration cannot be excited due to the absence of the axial exciting force when helix angle is zero. The increase of the helix angle will lead to more significant out-of-plane vibration of the gear foundation.

Transient impulsive feature detection is of vital importance in fault diagnosis of rolling bearing. However, the transient impulsive feature of rolling bearing is always heavily buried in the noise contaminated signal, which makes it difficult to be detected. Robust principal component analysis (PRCA) is an effective approach to exploit the underlying structure from the corrupted observation, where the decomposed low-rank matrix (LRM) and the sparse matrix can represent the useful diagnostic information and the unwanted background noise respectively. In this study, a Frobenius and nuclear hybrid norm penalized RPCA (FNHN-RPCA) is served as a specific RPCA solver on account of it has a great ability to approach to the rank of the LRM and make the execution procedure efficiently To make the recorded signal suitable for the input criterion of the RPCA solver, a fault information matrix (FIM) construction method is proposed to arrange the recorded signal into a matrix form. After the RPCA solver is conducted on it, a reversed recovery operation is also proposed to rearrange the two dimensional LRM into a one-dimensional signal form. To confirm all recorded data is processed by the RPCA solver, both the forward and backward FIMs are constructed and a synthesis of the recovered signals from both the forward and backward FIMs is served as the final transient impulsive feature enhanced signal. The diagnostic results on simulated and experimental case studies verify that the presented technique is suitable for transient impulsive feature detection of rolling bearings even when the test bearing works in a low speed operating condition or the operating environment is in the presence of random impact interference.

Considering the influence of roughness on the normal contact stiffness of gears, a fractal contact model suited for gear pair contact has been established. On the basis of modified fractal contact model, the asperity contact stiffness is calculated, thus the fractal contact compliance can be obtained. By substituting the nonlinear Hertz contact compliance with the fractal contact compliance, the effects of roughness on the time-varying mesh characteristics (including mesh stiffness (TVMS), loaded static transmission error (STE), load sharing ratio (LSR) and contact stress (CS)) of gears then can be discussed. The numerical simulation results show that the contact stiffness increases with the increment of the fractal dimension and the reduction of the fractal scale characteristic coefficient. In addition, the effect of friction on the mesh characteristics has also been investigated. As the coefficient of friction increases, the variation of the mesh characteristics in the single-tooth engagement region will increase correspondingly. Besides, the influence of multi-parameters on the mesh characteristics of gear pairs has been conducted. It can be found from the parametric studies that the amplitudes of gear mesh stiffness and contact stress are nonlinear with the changes of fractal parameter and friction coefficient.

Based on the loaded tooth contact analysis method, the time-varying mesh stiffness of planetary gear set considering gear crack fault are calculated. The real crack path of gear tooth is simulated based on the fracture mechanics theory. Meanwhile, an improved lumped parameter dynamic model is also established, which can effectively consider the time-varying distance between the planet gear and the transducer mounted on the fixed ring gear. The correctness of the proposed dynamic model is verified with the simulation results in literatures and also the experimental result on a planetary gear test rig. The amplitude modulations phenomenon and the frequency modulation phenomenon can be clearly observed in the simulated results. Using the proposed dynamic model, the fluctuation of the dynamic load sharing factors which considering the crack faults of gears are revealed, the result shows that the ring gear crack fault can rarely affect the dynamic load sharing among the external meshing gear pairs. The analysis in this study can help better understand the internal laws of crack fault for planetary gear set.

Conventional intelligent diagnostic model is built on the foundation that the training data and testing data are recorded under the same operating condition, which neglects the fact that the operating condition of the rotating machinery usually varies. The feature distribution of the recorded data in one operating condition may be inconsistent with the feature distribution of the recorded data in another operating condition. It is easy to cause a significant distribution discrepancy between the training data and testing data. To address this issue, an unsupervised domain adaptation approach based on a symmetric co-training framework is proposed in this study. In the proposed symmetric co-training framework, a universal feature extractor and two individual classifiers are built as the main elements. The structures of the two classifiers are symmetric and its parameters are updated in a co-training style. The parameters of the feature extractor and two classifiers are continuously updated via an adversarial training process. The cosine similarity of the predictions from two classifiers is introduced to guide the adversarial training process, which can not only minimize the distribution discrepancies between source domain data and target domain data, but also push the feature subspaces for different healthy conditions away from the class boundaries. The application of the proposed method on two sets of experimental bearing fault data validates that the proposed method can successfully address the domain shift phenomenon between the recorded data under different operating conditions.

Considering the thin rim structure and gear tooth modifications, a three-dimensional wear prediction model is proposed. Unitizing the proposed model, the contact pattern and the wear distribution are analyzed. For gear pairs with asymmetric rim structure, obvious stress concentration will lead to the severe wear on one edge of the gear tooth. Aiming at balancing the wear distribution and reducing vibration, an optimization scheme of the tooth modification (including the tip relief and the helix angle modification) is proposed. After adopting tooth modifications, the severe wear at one edge is almost eliminated. The fluctuation of the transmission error decreases significantly. The dynamic characteristics of thin-rimmed gears over the whole wear process are analyzed. It is found that the tooth modification is beneficial to shorten the running-in period and decelerate the failure process in the period of performance degradation.

Considering the realistic spalling morphology obtained from the fatigue experiment, a novel dynamic model for spalled gear pairs is established in this paper. Loaded tooth contact analysis method is utilized to evaluate the meshing characteristics of spalled gear pairs. In order to verify the proposed method, the mesh stiffness and contact stress obtained from the proposed method are compared with those obtained from the finite element method and the method in published literature. The mesh stiffness and the non-loaded static transmission error are imported into the geared rotor dynamic model to acquire the dynamic responses. The spectrum characteristics and statistical indicators under different spalling patterns are acquired by the proposed model. A comparison between simulation and experiment is performed to verify the proposed dynamic model. The results show that the simulated fault features agree well with that obtained from the experiment, which indicates that the proposed model is a promising tool for the fault mechanism study of gears with realistic spalling patterns.

Excavating trajectory impact the production efficiency and overall performance of excavator directly [1]. Hence, it’s of very realistic significance to obtain the optimal excavating trajectory. Based on site test data, the point of tangency of the rack pitch line of the bucket rod and the pitch circle of the crowd gear were determined as the rotating center and the dynamic model of working mechanism was derived; due to the change law of the current and voltage of the hoist motor, the excavating process sections was separated from the excavating trajectory; log spiral model was chosen as the fitting function, and according to the following three judgment rules: maximizing soil volume in bucket, rationalizing the excavating time and minimizing the energy consumption of unit mass of soil in bucket, the optimal excavating trajectory was obtained and provided basis for the operation and design of the large mining excavator [2].