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The inter-shaft bearing is the core component of a high-pressure rotor support system of a high-thrust aero engine. One of the most challenging tasks for a PHM is monitoring its working condition. However, considering that in the bearing rotor system of a high-thrust aero engine bearings are prone to wear failure due to unbalanced or misaligned faults of the rotor system, especially in harsh environments, such as those at high operating loads and high rotation speeds, bearing wear can easily evolve into serious faults. Compared with aero engine fault diagnosis and RUL prediction, relatively little research has been conducted on bearing condition monitoring. In addition, considering how to evaluate future performance states with limited time series data is a key problem. At the same time, the current deep neural network model has the technical challenge of poor interpretability. In order to fill the above gaps, we developed a new framework of a residual space–time feature fusion focusing module named RTCA-Net, which focuses on solving the key problem. It is difficult to accurately monitor the wear state of aero engine inter-shaft bearings under special working conditions in practical engineering. Specifically, firstly, a residual space–time structure module was innovatively designed to capture the characteristic information of the metal dust signal effectively. Secondly, a feature-focusing module was designed. By adjusting the change in the weight coefficient during training, the RTCA-Net framework can select the more useful information for monitoring the wear condition of inter-shaft bearings. Finally, the experimental dataset of metal debris was verified and compared with seven other methods, such as the RTC-Net. The results showed that the proposed RTCA-Net framework has good generalization, superiority, and credibility.

The squeeze film damper (SFD) is proven to be highly effective in mitigating rotor vibration as it traverses the critical speed, thus making it extensively utilized in the aeroengine domain. In this paper, we investigate the stiffness and damping of SFD using the Reynolds equation and neural network models. Our specific focus includes examining the structural and operating parameters of SFDs, such as clearance, feed pressure of oil, rotor whirl, and rotational speed. Firstly, the pressure distribution analytical model of the oil film inside the SFD based on the hydrodynamic lubrication theory is established, as described by the Reynolds equation. It obtained oil film forces, pressure, stiffness, and damping values under various sets of structural, lubrication, and operating parameters, including length, clearance, boundary pressure at both sides, rotational speed, and whirling motion, by applying difference computations to the Reynolds equation. Secondly, according to the significant analyses of the obtained oil film stiffness and damping, the following three parameters of the most significance are found: clearance, rotational speed, and rotor whirl. Furthermore, neural network models, including GA-BP and decision tree models, are established based on the obtained results of difference computation. The numerical simulation and calculation of these models are then applied to show their validity with all given parameters and the three significant parameters separately as two sets of model input. Regardless of either set of model inputs, these established neural network models are capable of predicting the nonlinear stiffness and damping of the oil film inside an SFD. These sensitive parameters merely require measurement, followed by the utilization of a neural network to predict stiffness and damping instead of the Reynolds equation. This process serves structural enhancement, facilitates parameter optimization in SFDs, and provides crucial support for refining the design parameters of SFDs.

Abstract The rigid-flexible coupling cable system under large deformation is studied, and the beam element from absolute node coordinate formulation is used to establish flexible cable body of the system. Different numerical integral algorithms are discussed for solving the rigid-flexible cable system and an integration strategy which combines Implicit Euler with Minimum Residual Method (MINRES) is proposed. The influence of the position and number of rigid components and different the lengths of the flexible elements on the system dynamics are analyzed. With constant total mass of the system, higher number of rigid components and their uniform distribution contribute to stabilization of the swing of the flexible cable body. When the total length of the cable is constant, increasing the number of beam elements enhances the nonlinear characteristics of the swing motion and damages the stability. The influence of different factors on the movement of large deformation flexible cable body is obtained through modeling and simulation of the rigid-flexible coupling cable system.

Intelligent diagnosis of faults in an aero-hydraulic pipeline is important for condition monitoring of its systems. However, there are no more qualitative formulas or feature indicators to describe the faults of aero-hydraulic pipelines because of the complexity and diversity of aero-hydraulic pipeline systems, which leads to a very complex pipeline fault mechanism. In addition, although it is well known that the expression of interpretable and representable pipeline intelligent diagnosis models with pipeline fault characteristics are buried in high background noise and strong noise disturbance conditions in practical industrial scenarios, this has yet to be discussed. Inspired by the demand, this paper proposes a novel diagnosis strategy: the 1D-convolutional space-time fusion strategy for aero-engine hydraulic pipelines. Firstly, by optimizing the convolutional neural network and using it to design a one-dimensional convolutional neural network (1DCNN) with a wide input scale to expand the input field of perception, thereby obtaining more comprehensive spatial information of the pipeline data, which can effectively extract richer short sequence features. Secondly, a network of bidirectional gated recurrent Unit (Bi-GRU) is proposed, which integrates a short sequence of high-dimensional features for temporal information fusion, resulting in a certain degree of avoiding memory loss and gradient dispersion caused by the too-large step size. It is demonstrated that, for the noise signal and variable pressure signal, the fault identification accuracy approximated 95.9%, proving the proposed strategy’s robustness. By comparing with the other five methods, the proposed strategy has the ability to identify 10 different fault states in the aero-hydraulic pipeline with higher accuracy.

Due to the development of aviation hydraulic systems towards high pressure and high flow, the frequency range of pressure pulsation becomes wider, and the amplitude of pulsation increases. This puts higher requirements on the attenuation characteristics of the pressure pulsation attenuator. To reduce the damage caused by pressure pulsation to the pipeline, a Helmholtz-type pulsation attenuator (HTPA) is designed, which works through the Helmholtz resonant chamber. The theoretical model of HTPA is established by the method of lumped parameter method and distribution parametric method. The insertion loss is adopted to evaluate its attenuation characteristics. The internal pressure dynamic characteristics and attenuation effect of the HTPA are analyzed by simulation and experimentation. The results show that the pulsation attenuation rate δ was 40% after the installation of the attenuator. In the frequency range of 0–1000 Hz, the maximum insertion loss is 19 dB, which verifies the validity and correctness of the theoretical model.

In this paper, the thermomechanical characteristics of microturbine bearing during the process of bearing performance decay due to abrasive particles are theoretically and experimentally researched, such as contact characteristic, temperature characteristics, and stiffness characteristic, are illustrated. The results is that the evolution law of contact deformation and contact stiffness over the whole life of bearing is the same, whose amplitude is slightly different. The curve shape and amplitude of contact angular between ball and outer/inner ring has the obvious diversity. M CR are dominant in heat production of bearing, the temperature of inner ring and contact zone between ball and inner ring is the maximum. The variation curve of bearing dynamic stiffness agrees with that of temperature in general.

During the service of rotating machinery, the pedestal bolts are prone to looseness due to the vibration environment, which affects the performance of rotating machinery and generate potential safety hazard. To monitor the occurrence and deterioration of the pedestal looseness in time, this paper proposes a data-driven diagnosis strategy for the rotor-bearing system. Firstly, the finite element model of a rotor-bearing system is established, which considers the piecewise nonlinear force caused by pedestal looseness. Taking the vibration response as output and periodic unbalanced force as input, the system’s NARX (Nonlinear Auto-Regressive with exogenous inputs) model is identified. Then GALEs (Generalized Associated Linear Equations) are used to evaluate NOFRFs (Nonlinear Output Frequency Response Functions) of the NARX model. Based on the first three-order NOFRFs, the analytical expression of the second-order optimal weighted contribution rate is derived and used as a new health indicator. The simulation results show that compared with the conventional NOFRFs-based health indicator, the new indicator is more sensitive to weak looseness. Finally, a rotor-bearing test rig was built, and the pedestal looseness was performed. The experiment results show that as the degree of looseness increases, the new indicator SRm shows a monotonous upward trend, increasing from 0.48 in no looseness to 0.90 in severe looseness, a rise of 89.7%. However, the traditional indicator Fe2 has no monotonicity, which further verifies the sensitivity of the first three-order NOFRFs-based second-order optimal weighted contribution rate and the effectiveness of the proposed data-driven feature extraction strategy.

Double-row tapered roller bearings have been widely used in various equipment recently due to their compact structure and ability to withstand large loads. The dynamic stiffness is composed of contact stiffness, oil film stiffness and support stiffness, and the contact stiffness has the most significant influence on the dynamic performance of the bearing. There are few studies on the contact stiffness of double-row tapered roller bearings. Firstly, the contact mechanics calculation model of double-row tapered roller bearing under composite loads has been established. On this basis, the influence of load distribution of double-row tapered roller bearing is analyzed, and the calculation model of contact stiffness of double-row tapered roller bearing is obtained according to the relationship between overall stiffness and local stiffness of bearing. Based on the established stiffness model, the influence of different working conditions on the contact stiffness of the bearing is simulated and analyzed, and the effects of radial load, axial load, bending moment load, speed, preload, and deflection angle on the contact stiffness of double row tapered roller bearings have been revealed. Finally, by comparing the results with Adams simulation results, the error is within 8%, which verifies the validity and accuracy of the proposed model and method. The research content of this paper provides theoretical support for the design of double-row tapered roller bearings and the identification of bearing performance parameters under complex loads.

The quantitative diagnosis of rolling bearings is essential to automating maintenance decisions. Over recent years, Lempel–Ziv complexity (LZC) has been widely used for the quantitative assessment of mechanical failures as one of the most valuable indicators for detecting dynamic changes in nonlinear signals. However, LZC focuses on the binary conversion of 0–1 code, which can easily lose some effective information about the time series and cannot fully mine the fault characteristics. Additionally, the immunity of LZC to noise cannot be insured, and it is difficult to quantitatively characterize the fault signal under strong background noise. To overcome these limitations, a quantitative bearing fault diagnosis method based on the optimized Variational Modal Decomposition Lempel–Ziv complexity (VMD-LZC) was developed to fully extract the vibration characteristics and to quantitatively characterize the bearing faults under variable operating conditions. First, to compensate for the deficiency that the main parameters of the variational modal decomposition (VMD) have to be selected by human experience, a genetic algorithm (GA) is used to optimize the parameters of the VMD and adaptively determine the optimal parameters [k, α] of the bearing fault signal. Furthermore, the IMF components that contain the maximum fault information are selected for signal reconstruction based on the Kurtosis theory. The Lempel–Ziv index of the reconstructed signal is calculated and then weighted and summed to obtain the Lempel–Ziv composite index. The experimental results show that the proposed method is of high application value for the quantitative assessment and classification of bearing faults in turbine rolling bearings under various operating conditions such as mild and severe crack faults and variable loads.

Long service time and excessive vibration of aero-engine will cause failure of clamps, which usually fix pipelines on the outside of an aero-engine. In this paper, the nonlinear vibration characteristics caused by loosening clamps in aero-engine pipeline are determined. According to the real parameters of an aero-engine clamp-pipeline test rig, the clamp is simplified into a nonlinear spring-damping. Thus, a clamp-pipeline nonlinear model based on cubic stiffness is established. The multi-scale method is used to obtain the analytical solution of the nonlinear model. Based on the real test data, the model parameters of the clamp-pipeline nonlinear system are identified, and then the nonlinear vibration characteristics of the system are obtained. Finally, using the vibration transmissibility method, the influence of the severity of clamp loosening on the nonlinear vibration characteristics of the system is obtained.

Based on the Bouc-Wen model, a nonlinear hysteretic restoring force model is established with dynamic equations. The hardening and softening of the material after reaching the yield limit are described by the nonlinear restoring force-displacement hysteretic curve. The Gamultiobj algorithm and the group search optimization (GSO) algorithm are used to fit and identify the material softening and hardening hysteresis curves, respectively. The effectiveness of the optimization algorithm for identifying the parameters of the hysteretic model is verified, and the optimization effects of the two algorithms are compared. The results show that the Gamultiobj algorithm has better parameter identification ability and curve fitting ability for the hysteretic model. Then, the hysteresis curve describing the nonlinear characteristics of a clamp is obtained through the static stiffness experiment of the clamp. The experimental curve is fitted by the Gamultiobj algorithm. As a result, the nonlinear Bouc-Wen model parameters of the clamp are obtained, and the stiffness and damping of the clamp are recognized. The distribution statistics of the obtained parameters are performed, and it is found that each parameter satisfies a certain probability distribution, which indicates that the parameter identification result is reasonable.

For the nonlinear vibration problem of spur gear transmission system caused by friction and gear backlash, the dynamic model of gearbox with 16-degree-of-freedom (16-DOF) considering time-varying meshing stiffness is established by Lagrange equation. The dynamic equations of the gear system are solved by the Newmark-β method. The effects of friction coefficient, error fluctuation and meshing stiffness on the vibration response are investigated. In order to verify the validity of the model, a spur gear transmission rotor test bench was built by simulating the actual working conditions. The root mean square (RMS) is used to verify the accuracy of the model at multiple speeds, and makes up for the shortcomings of many researches without experimental argumentation. The experimental research can provide a reference for the research of gear transmission system.

Due to manufacturing errors and material deteriorations in the metal rubber of clamps, the clamp stiffness of the pipeline is uncertain. This paper presents a non-intrusive multi-dimensional Chebyshev polynomial approximation method (M-CPAM) to evaluate uncertain characteristics of the frequency response function (FRF) of the clamp-pipeline system (CPS), where the clamp stiffness parameters are taken as unknown but bounded interval variables. Firstly, a finite element model of the clamp-pipeline system is established. Secondly, the variance-based global sensitivity analysis is implemented to determine significant stiffness parameters. Then, the uncertain intervals of the clamp stiffness are measured by experiments and the dispersion of the clamp stiffness is described. Finally, based on the measured stiffness interval, the uncertain frequency responses of the CPS under different tightening torques are analyzed by the proposed M-CPAM, and the effectiveness of simulation results is verified by experiments. Compared with the results obtained from the Monte Carlo simulation, the experimental measurements, and the polynomial chaos expansion, the proposed M-CPAM provides a more accurate, time-saving and practical method for solving the uncertain frequency responses of the CPS with interval stiffness variables. The results show that the clamp stiffness has great dispersion under the same tightening torque. A frequency shift phenomenon will be observed when the clamp stiffness is uncertain. Moreover, the dispersion of the frequency response of the CPS tends to be concentrated with the increase of the tightening torques.

The gear-bearing system is the most important part of integrally centrifugal compressors. According to statistics, the majority of integrally geared compressor accidents are caused by excessive vibration of the geared rotor. However, its complicated dynamic characteristics and inevitable vibration faults in actual operation present significant challenges throughout the analysis and design stages. In this paper, the coupled self-excited vibration of the gear system characterized by multipoint meshing and oil film bearing supporting is investigated. Firstly, the structure of the gear system in an integrally geared compressor is used as a research object. The modeling approach of meshing excitation, including time-varying mesh stiffness, gear meshing error, and tooth backlash are introduced. However, the variable stiffness and damping coefficient equations of journal bearing and oil film thrust bearing are modeled and utilized to approximate the variable bearing force and simplify the vibration computation under the assumption of Newtonian fluid. Then, a dimensionless modeling method of the gear system considering gyroscopic moment of gear disk, variable meshing force, as well as variable stiffness and damping coefficient is proposed. Based on the dynamic model, the influence of the bearing dynamic coefficients and load on the vibration of the entire gear system is studied. Among which, the vibration displacement and meshing force are examined using frequency-domain and time-domain analysis methods. The results suggest that the flexible support can restrain the system’s nonlinear motion, whilst increasing load on the gear system can improve gear operation stability and reduce load fluctuation.

The abnormal wear of a rolling element bearing caused by early failures, such as pitting and spalling, will deteriorate the running state and reduce the life. This paper demonstrates the importance of oil debris monitoring and its effective feature extraction for bearing health assessment. In this paper, a rolling bearing-rotor test rig with forced lubrication is set up and the nonferrous contaminants with higher hardness were introduced artificially to accelerate the occurrence of pitting and spalling. The early failure and abnormal wear of rolling bearings cannot be effectively detected only through the vibration signal; the temperature and oil debris monitoring data are also collected synchronously. Two features regarding the ferrous particle size distribution are extracted and fused with vibration based-features to form a feature set. The sensitive features are extracted from the features set using the Neighborhood Component Analysis method to avoid feature redundancy. Finally, the importance of the oil debris based-features for the diagnosis of abnormal bearing wear is analyzed with different machine learning algorithms. Taking SVM classifier as an example, the experiment results show that the introduction of oil debris based-features increases the diagnostic accuracy by 15.7%.

In this paper, a finite element model updating (FEMU) method is proposed based on the response surface model (RSM) and genetic algorithm (GA) to establish a high-precision finite element (FE) model of space station scientific experiment racks. First, the fine solid and mixed FE models are established, respectively, and a comparison of the modal test results is conducted. Then, an orthogonal experimental design is used to analyze the significance of the parameters, and the variables to be modified are determined. The design parameters are sampled via the Latin hyperbolic method and are substituted into the FE model to obtain the modal parameters of the scientific experiment rack. The mapping relationship between the design and modal parameters is fitted by constructing the Kriging function, and the RSM is established. The design parameters of the scientific experiment rack are optimized via GA, and the initial FE model is updated, which has the advantage of improving the computing efficiency. Finally, the updated FE model of the experiment rack is verified by frequency sweep and random vibration tests. The experimental results show that the proposed approach has high precision and computing efficiency, and compared with the test results, the modal frequency errors of the updated model are within 5%, and the vibration response errors under random excitation of the updated model are within 7%.

The occurrence of the motor shaft voltage and bearing current caused by the inverter will aggravate bearing damage and lead to the premature failure of bearings. Many types of equipment are being shut down due to bearing currents, such as filters, insulated bearings and grounding brushes. Traditional suppression measures cannot eliminate the bearing current and the bearing damage mechanism under the bearing current is not clear. In this paper, the damage caused by the bearing current to bearings is analyzed in detail. The influences of different working conditions on the bearing current and the damage caused are discussed. The source of bearing currents is introduced and the bearing current model under different working conditions is reviewed. An outlook for future studies is proposed, based on the current research status and challenges.

The driving mechanism of an axisymmetric vectoring exhaust nozzle (AVEN) is a 3-degrees-of-freedom (3-DOF) parallel manipulator (PM) with a centering device. According to the characteristics of the vectoring nozzle’s movement mechanism, the 3-DOF kinematics model of the 3SPS + 3PRS PM is established. The forward and inverse positional posture models are built based on the mechanism architecture of PM and the closed-loop vector method. The Jacobian matrix and Hessian matrix are derived using screw theory, and velocity and acceleration models are established. Based on the principle of virtual work and combined with the kinematics model of PM, a stiffness model was established to analyze stiffness performance. Finally, the effectiveness of the kinematics model of the PM was verified by a simulation, and the variation of stiffness performances with the positional posture of the PM was quantitatively analyzed. The results show that the translational stiffness decreases with forward axial translation of the moving platform and the rotational stiffness is mainly determined by the posture parameters. This study is expected to offer ideas for the kinematic modeling of 3-DOF PM and provide references for application and optimizing of the AVEN’s driving mechanism.

As a high-precision motion mechanism, the kinematics and dynamics of cascade thrust reverser are sensitive to the changes of nonlinear factors which are rarely considered in traditional dynamic modeling and optimization. In order to study the effect of nonlinear factors on the dynamics behavior of cascade thrust reverser mechanism, the dynamic model considering joint clearance and flexible component is established. Lankarani–Nikravesh and modified-Coulomb model are used to establish the contact force at the clearance, and the flexible component in the mechanism is modeled by the absolute node coordinate method. The effects of joint clearance value, clearance position, flexible component, and driving speed on the dynamic response of the mechanism are studied. Specifically, the nonlinear characteristics of the mechanism increase with the clearance value, and the joint clearance near the mobile fairing has greater influence on the kinematics and dynamics of blocker door. For the mechanical system with clearances, the flexible component can partially reduce the vibration of the system. The analysis of the motion synchronization of the thrust reverser actuators indicates that the asynchronous movement of actuators may increase the driving forces of actuators especially for the middle actuator.

In this paper, a parameter sensitivity analysis of mounting pedestals and a multi-objective optimization design for vibration reduction in a multi-support rigid body system, taking an aeroengine-lubricating oil tank supported by multiple mounting pedestals as an example, are conducted based on the third version of non-dominated sorting genetic algorithm (NSGA-Ⅲ) combined with Sobol’s sensitivity analysis method (SSAM). An aeroengine-lubricating oil tank with three mounting pedestals is simplified as a three-support dynamic system, and its dynamics model is established. Several structural parameters of mounting pedestals are taken as the design variables, and the system vibration response and the reaction force of the front and rear mounting pedestals are considered as the objective functions. The first-order results and total sensitivity index of different design parameters for each objective function are obtained via SSAM, and the five most sensitive parameters are selected. Based on the above five design parameters, multi-objective optimization designing for vibration reduction in a simplified lubricating oil tank system is conducted based on NSGA-Ⅲ, and the results of the above triple-objective optimization are obtained as a Pareto-front surface with an obvious frontier. It can be observed from the simulation results that the oil tank vibration of the optimized system is effectively suppressed under the unbalanced excitation of two typical engine speeds. The established method and the main results can provide guidance for designers of aeroengine external structural systems, which can help to achieve superior system dynamic performances in engineering applications.

To study the rub-impact fault between the dynamic and static parts of the rotor system of aeroengines, the dual-rotor system of a typical aeroengine is introduced and taken as the research object. The analytical kinetic model is established based on the Lagrange equation considering the structural characteristics of the dual-rotor system, the coupling effect of the intermediate bearing, and the rub-impact fault between the high-pressure turbine disc and the casing. The dynamic characteristics of the dual-rotor system under the rub-impact fault are analyzed, and the change rule of the rub-impact shape is obtained. The vibration coupling and transfer among the high-pressure rotor and the low-pressure rotor are revealed. The influence of the unbalanced position and the speed of high and low rotors on the vibration response of the dual rotor is obtained. The sensitivity of the vibration response of the dual rotor at different test points to rub-impact stiffness, clearance, and friction coefficient is compared. The simulation model is established based on the rigid-flexible coupling multibody dynamic simulation platform. The analytical results and simulation results are compared, which have a good consistency. The theoretical research can deepen the understanding of the nature and law of aeroengine rotor operation, expose the possible faults and design defects, greatly improve the development efficiency and quality, reduce repeated physical tests, reduce the development risk and cost, and accelerate the development process. This study can provide a theoretical basis for the monitoring and diagnosis of engine rub-impact faults and provide theoretical and practical reference for the establishment of the vibration fault test and analysis method system.

A misaligned rigid rotor system with flexible supports differing from the traditional flexible rotor system, which refers to its practical rotating center line determined by supports offset from the theoretical one, often suffers support structure damage risk. In the present work, the dynamic characteristics of a misaligned rigid rotor system with flexible squirrel cage supports are focused, and the vibrations and the stress of its support structures under different misaligned offsets are investigated with experimental and simulated analysis. The finite element model for a rigid rotor system with flexible supports in a scaled test rig is established, and its strain energy distribution is analyzed to find that the first two modes of the system are referred to rigid-body modes and the strain energy is mainly distributed on the squirrel cage supports. Based on the analysis results, a rigid-flexible coupling dynamic model is proposed through a data exchange between ADAMS and ANSYS and validated by measurements. The misaligned conditions are focused on, and the influences of misalignment on the vibrations of the rigid rotor system and the reaction force and stress of its support structures are investigated analytically and experimentally. The results from simulation agree very well with the measurements and reveal that the static stress of squirrel cage increases just about proportionally with misalignment levels, but the vibration displacement amplitudes and stress amplitudes show very little change. The more serious the misaligned condition, the higher the static stress of the squirrel cage. Because misalignment will bring out the additional reaction forces in the misaligned direction, it will further result in higher stress and even more serious damage risk for the flexible supports than other parts in the rigid rotor system.

In this paper, a pedestal looseness fault model of a rotor-bearing-seal system is established. Under two working conditions of the same direction eccentricity (Working Condition 1) and reverse eccentricity (Working Condition 2), rotor orbits, vibration waveforms, spectrum cascade, and Poincaré maps are used to study the dynamic characteristics of the system when the sliding bearing support is loosened. The influence of speed, the unbalance of two discs, the looseness clearance, and the mass of bearing support on system characteristics are analyzed. The study found that Working Condition 2 is more likely to cause looseness of the bearing support. Moreover, for the rotor system in this paper, the pedestal looseness fault is more likely to occur near the second-order critical speed. Through analysis of the spectrum, it is found that the spectrum of the looseness fault will show multiple frequencies or continuous spectra, and the rotor orbits will appear “cylindrical.”

The acoustic pressure signal generated by blades is one of the key indicators for condition monitoring and fault diagnosis in the field of turbines. Generally, the working conditions of the turbine are harsh, resulting in a large amount of interference and noise in the measured acoustic pressure signal. Therefore, denoising the acoustic pressure signal is the basis of the subsequent research. In this paper, a denoising method of micro-turbine acoustic pressure signal based on the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) and Variable step-size Normalized Least Mean Square (VSS-NLMS) algorithms is proposed. Firstly, the CEEMDAN algorithm is used to decompose the original signal into multiple intrinsic mode functions (IMFs), based on the cross-correlation coefficient and continuous mean square error (CMSE) criterion; the obtained IMFs are divided into clear IMFs, noise-dominated IMFs, and noise IMFs. Finally, the improved VSS-NLMS algorithm is adopted to denoise the noise-dominated IMFs and combined with the clear IMF for reconstruction to obtain the final denoised signal. Adopting the above principles, the acoustic pressure signals generated by a micro-turbine with different rotation speeds and different states (normal turbine and fractured turbine) are denoised, respectively, and the results are compared with the axial flow fan test (ideal interference-free signal). The results show that the denoising method proposed in this paper has a good denoising effect, and the denoised signal is smooth and the important features are well preserved, which is conducive to the extraction of acoustic pressure signal characteristics.

Internal combustion engines take up the major position in the power facility market and still encounter some challenges; one key issue is liner cavitation erosion. The impact vibration between piston and cylinder generates pressure fluctuation on the wet liner surface and leads to the occurrence of cavitation in the case that coolant pressure falls below its vapor pressure. Piston slap methodology has been improved by considering the dynamic characteristics of the piston. Water coolant passage acoustic features were investigated and the Helmholtz effect between cylinders was confirmed. In order to address the cavitation erosion potential of the engine cylinder, acoustic pressure in the cooling water passage was investigated by boundary element method analysis with the acceleration of the cylinder liner which was obtained from the piston slap program. This study revealed that a certain acoustic mode of the cooling water passage had a dominant effect on the amplitude of water coolant dynamic pressure induced by liner vibration. Measures of eliminating the acoustic mode are believed to be able to suspend pressure fluctuation and furthermore the potential of cavitation.

In order to study the influence of compliance parts on spatial multibody systems, a rigid-flexible coupling dynamic equation of a spatial crank-slider mechanism is established based on the finite element method. Specifically, absolute node coordinate formulation (ANCF) is used to formulate a three-dimensional, two-node flexible cable element. The rigid-flexible coupling dynamic equation of the mechanism is derived by the Lagrange multiplier method and solved by the generalized α method and Newton–Raphson iteration method combined. Comparison of the kinematics and dynamics response between rigid-flexible coupling system and pure rigid system implies that the flexible part causes a certain degree of nonlinearity and reduces the reaction forces of joints. The elastic modulus of the flexible part is also important to the dynamics of the rigid-flexible multibody system. With smaller elastic modulus, the motion accuracy and reaction forces become lower.

Squeeze film damper (SFD) is widely used in the vibration suppression of aeroengine rotor systems, but will cause complex motions of the rotor system under specific operating conditions. In this paper, a lumped-mass dynamic model of the high-pressure rotor system in an aeroengine is established, and the nonlinear stiffness and damping formula of SFD are introduced into the above model. The vibration responses of the rotor system under different rotating speeds and with different unbalances are investigated numerically, and the influence of SFD on the rotor system vibration and the change of suppression ability are compared and analyzed. The results show that in the case of high speed, together with a small unbalance, the rotor system will perform a complex vibration or a bistable vibration due to SFD. If the unbalance is properly increased under the same case of high speed, the vibration of the rotor becomes single-harmonic and the bistable vibration disappears. The research results can provide a helpful reference for analyzing complex vibration mechanisms of the rotor system with SFD and achieving an effective vibration suppression through unbalance regulation.

This paper presents the dynamic characteristics analysis of a rigid body system with spatial multi-point elastic supports, as well as the sensitivity analysis of support parameters. A rigid object is characterized by six degrees-of-freedom (DOFs) motions and considering the spatial location vector decomposition of elastic supports, a rigid body system dynamic model with spatial multi-point elastic supports is derived via the Lagrangian energy method. The system modal frequencies are calculated, and to be verified by finite element modal analysis results. Next, based on the above-mentioned model, system modal frequencies are obtained under different support locations, where the support stiffness components are different. Interpolate the stiffness components corresponding to each support location, calculate system modal frequencies, and the response surface model (RSM) for system modal frequencies is established. Further, based on the RSM modal analysis results, the allowable support location for the system modal insensitive area can be obtained. At last, a lubricating oil-tank system with four supports is taken as an example, and the effects of support spatial locations and stiffness components on the system inherent characteristics are discussed. This present work can provide a basis for the dynamic design of the spatial location and stiffness for this type of installation structures.

The output flow pulsation characteristics of the hydraulic pump due to the structural characteristics may cause pump source fluid pressure pulsation and even cause the equipment to vibrate, which will affect the life and working reliability of the equipment. Scholars have done a lot of theoretical and simulation analysis on the characteristics of fluid flow and pressure pulsation caused by the specific structure and structure of the plunger pump, but there are few comparisons and analyses of the simplified model of the plunger pump and the pressure pulsation characteristics with experiments. In this paper, AMESim software is utilized to establish a simplified model of one seven-plunger hydraulic pump, and simulate and analyze the pump source fluid pressure pulsation characteristics of different system load pressures at a constant speed. An experimental platform for testing pump fluid pressure pulsation was designed and built, and the actual measurement and simulation results of pump fluid pressure pulsation were compared and analyzed. The results show that the system simulation data is in good agreement with the measured data, which verifies the correctness of the simplified model of the plunger pump. At the same time, it is found that the fluid pressure pulsation of the pump source exhibits broadband and multi-harmonic characteristics. At a constant speed, as the load pressure of the hydraulic system increases, the pump source fluid pressure pulsation amplitude increases, the pressure pulsation rate decreases, and the impact on the fundamental frequency amplitude is the most significant. The research results can provide a theoretical basis for suppressing the pressure pulsation of the pump source fluid and reducing the vibration response of a hydraulic pipeline under the action of the pulsating harmonic excitation.

For vibration damping, coatings are prepared on surface of the structures (substrates), which constitute the coating-substrate composite structures. Elastic parameters of the coating are indispensable for the vibration and damping analysis of the composite structure. Due to the small scale of coating thickness and elastic difference compared with the substrate, the identification results are inevitably influenced by the existence of substrate. Moreover, resulting from the preparation process, elastic properties of hard coating often exhibit anisotropic properties. All the above factors bring about the difficulties of accurate identification. In this study, a method for identifying anisotropic elastic parameters of hard coatings considering substrate effect is proposed, by combining nanoindentation and finite element analysis. Based on the identification results, finite element models are established to analyze the vibration characteristics of the coating-substrate composite structure, which verify the rationality of the anisotropic elastic parameters for vibration analysis. The studies in this paper are significant to more accurately identify the mechanical parameters for establishing the dynamic model. Moreover, they lay the foundation for further optimization design of hard coating damping.

This paper proposes a novel optimization layout method for supporting clamps in a pipeline system. In this method, the global sensitivity analysis based on the Sobol method is presented to determine the influence of clamp position on the first-order frequency difference, the maximum vibration response displacement, and the maximum vibration stress. The modeling density of the finite element calculation is determined, and then a surrogate model of the relationship between the optimized input and the output is established through the neural network. The optimized position and orientation of the clamp are obtained by the genetic algorithm. Finally, a typical pipeline with clamps are conducted as an example to verify the effectiveness of the proposed optimization method. The simulations were compared with the experiment, and the result shows that the proposed optimization method can reduce the vibration of the pipeline system significantly, thus providing a new method for the arrangement of clamps in pipeline system.

To avoid catastrophic failures in rotating machines, it is of great significance to continuously monitor and diagnose the running state of rolling bearings. In this article, a deep feature extraction method for rolling bearing fault diagnosis based on empirical mode decomposition and kernel function is proposed. First, the vibration signals under different states of rolling bearing are decomposed by empirical mode decomposition. Second, to extract more representative high-level features, the obtained intrinsic mode functions are preprocessed with singular value decomposition to acquire singular value parameters, which are regarded as the inputs of the proposed stacked kernel sparse autoencoder network. The proposed method does not depend on prior knowledge of fault diagnosis and even does not need the signal denoising processing, simplifying the traditional process of feature extraction of rolling bearing fault diagnosis. To validate the superiority of the proposed diagnosis network, experiments and comparisons have been made as well. The achieved results demonstrated that the proposed empirical mode decomposition and stacked kernel sparse autoencoder–based diagnosis method has a superior performance in rolling bearing fault diagnosis.

A trend prediction method based on the Pchip-EEMD-GM(1,1) to predict the remaining useful life (RUL) of rolling bearings was proposed in this paper. Firstly, the dimension of the extracted features was reduced by the KPCA dimensionality reduction method, and the WPHM model parameters were estimated via the kernel principal components. Secondly, the hazard rate was calculated at each time, and the Pchip interpolation method was used to obtain the uniformly spaced interpolation data series. Then the main trend of signal was obtained through the EEMD method to fit the GM(1,1) prediction model. Finally, the GM (1,1) method was used to predict the remaining life of the rolling bearing. The full life test of rolling bearing was provided to demonstrate that the method predicting the hazard data directly has the higher accuracy compared with predicting the covariates, and the results verified the feasibility and effectiveness of the proposed method for predicting the remaining life.

Rotating machinery vibration signals are nonstationary and nonlinear under complicated operating conditions. It is meaningful to extract optimal features from raw signal and provide accurate fault diagnosis results. In order to resolve the nonlinear problem, an enhancement deep feature extraction method based on Gaussian radial basis kernel function and autoencoder (AE) is proposed. Firstly, kernel function is employed to enhance the feature learning capability, and a new AE is designed termed kernel AE (KAE). Subsequently, a deep neural network is constructed with one KAE and multiple AEs to extract inherent features layer by layer. Finally, softmax is adopted as the classifier to accurately identify different bearing faults, and error backpropagation algorithm is used to fine-tune the model parameters. Aircraft engine intershaft bearing vibration data are used to verify the method. The results confirm that the proposed method has a better feature extraction capability, requires fewer iterations, and has a higher accuracy than standard methods using a stacked AE.

Large-size and heavy-load slewing bearings, which are mainly used in heavy equipment, comprise a subgroup of rolling bearings. Owing to the complexity of the structures and working conditions, it is quite challenging to effectively diagnose the combined failure and extract fault features of slewing bearings. In this study, a method was proposed to denoise and classify the combined failure of slewing bearings. First, after removing the mean, the vibration signals were denoised by maximum correlated kurtosis deconvolution. The signals were then decomposed into several intrinsic mode functions (IMFs) by complementary ensemble empirical mode decomposition (CEEMD). Appropriate IMFs were selected based on the correlation coefficient and kurtosis. The approximate entropy values of the selected IMFs were regarded as the characteristic vectors and then inputted into the support vector machine (SVM) based on multiclass classification for training. The practical combined failure signals of the 3 conditions were finally recognized and classified using SVMs. The study also compared the proposed method with 5 other methods to demonstrate the superiority and effectiveness of the proposed method.

In this paper, vibration control of an aero pipeline system using active constrained layer damping treatment has been investigated in terms of the vibration and stress distribution. A three-dimensional finite element model of such a pipeline with active constrained layer damping (ACLD) patches is developed. The transfer of the driving force under harmonic voltage is analyzed based on the finite element model. The vibration control of the pipeline with active constrained layer damping treatment under different voltages is computed to analyze the influence of control parameters and structural parameters on the control effect. An experiment platform is developed to validate the above relations. Results show that the performance of the active constrained layer damping treatment is affected by the elastic modulus and thickness of the viscoelastic layer, control voltage and structure size. The performance increases significantly with the rising of the control voltage and cover area of ACLD patches among these parameters.

With the analytic method and numerical method respectively, the asymptotic solutions and finite element model of rotor system with single slowly varying mass is obtained to investigate the time frequency features of such rotor system; furthermore, with given model of slowly varying mass, the rotor system with dual slowly varying mass is studied. For the first order approximate solution is used, there exists difference between the results with analytic method and numerical method. On the base of common characteristics of rotor system with dual slowly varying mass, the general rules and formula describing the frequency distribution of rotor system with multiple slowly varying mass are proposed.

In this paper, we investigate the joint viscous friction effects on the motions of a two-bar linkage under controlling of OPCL. The dynamical model of the two-bar linkage with an OPCL controller is firstly set up with considering the two joints' viscous frictions. Thereafter, the motion bifurcations of the two-bar linkage along the values of joint viscous frictions are obtained using shooting method. Then, single-periodic, multiple-periodic, quasi-periodic and chaotic motions of link rotating angles are simulated with given different viscous friction values, and they are illustrated in time domain waveforms, phase space portraits, amplitude spectra and Poincare mapping graphs, respectively. Additionally, for the chaotic case, Lyapunov exponents and hypothesis possibilities of the two joint motions are also estimated.

This study investigates a method of designing a simplified cylindrical shell model. This model accurately predicts the dynamic characteristics of a prototype cylindrical shell with sealing teeth accurately. The significance of this study is that it provides an acceptable process which guides the design of test models. Firstly, an equivalent cylindrical shell with rectangular rings is designed by combining the energy equation and numerical analysis. Then the transfer matrixes of the stiffened cylindrical shell and the cylindrical shell are employed to calculate the equivalent thickness of the simplified cylindrical shell commonly used in model tests. Further, the equivalent thicknesses are normalized by introducing an average equivalent thickness. The distorted scaling laws and size applicable intervals are investigated to reduce the errors caused by the normalization. Finally, a 42CrMo cylindrical shell with sealing teeth is used as a prototype and a number 45 steel scaled-down cylindrical shell is used as a distorted test model. The accuracy of the prediction is verified by using experimental data, and the results indicate that the distorted model can predict the characteristics of the stiffened cylindrical shell prototype with good accuracy.