This study addresses the challenge of reducing the transmission of low-frequency road excitation vibrations to the cab of mining dump trucks to enhance ride comfort. Given the harsh working conditions of these vehicles, a novel methodology combining experimental data collection and advanced signal processing techniques was developed. The research established a comprehensive vibration testing program aligned with earth-moving machinery standards, collecting vibration acceleration data under both idling and full-load operation at 35 km/h. To improve data accuracy, Singular Value Decomposition (SVD) was employed to denoise the experimental vibration data, effectively mitigating environmental interference. Subsequent Fourier transform analysis revealed the vibration energy transfer patterns of the vehicle suspension system in the frequency domain. The results indicated a significant vibration isolation rate of 89 % for the frame suspension system, contrasting with only 7 % for the cab suspension system. Notably, the cab seat suspension system was found to amplify low-frequency road excitations. Compared to previous methods, this study innovatively integrates SVD and Fourier transform techniques to provide a more accurate and detailed understanding of vibration transmission. The key result of achieving an 89 % vibration isolation rate for the frame suspension system demonstrates the effectiveness of the proposed methodology. This study offers practical optimization directions for improving suspension system performance and ride comfort in mining dump trucks, outperforming traditional approaches by providing a more comprehensive analysis and actionable insights for vibration isolation. The findings also serve as valuable references for addressing similar engineering challenges in heavy machinery.

Accurate identification of weak fault signals is critical for gear fault detection, yet particularly challenging. This study proposes a gear fault diagnosis method that utilizes Mutual Information (MI) and an Improved False Nearest Neighbor (IFNN) algorithm to optimize the delay time (τ) and embedding dimension (m) for Multiscale Permutation Entropy (MPE) calculation. The MPE values of various fault samples are computed using this optimized approach. The minimum Mahalanobis distance (min-MDMaha) for each sample achieves a fault identification accuracy of 76.87%. Information entropy is then employed to extract useful information from different fault samples, serving as weights for the MDMaha. Experiments on gear pitting and wear faults validate the method. The weighted MDMaha significantly improves accuracy to 99.72%. The results demonstrate the superior effectiveness of the proposed weighted MDMaha-enhanced MPE framework in characterizing vibration signatures induced by gear faults.

Due to the intense noise interference in hydraulic systems, it is extremely difficult to detect component faults through vibration signals. Diagnostic performance is also constrained by highly time-varying and non-stationary operating conditions. This study proposes to use instantaneous angular speed (IAS) signals that are both operational and state parameters as sources of information. Firstly, the instantaneous angular speed fluctuation (IASF) of a piston pump is analyzed theoretically, and it is concluded that its fluctuating components contain the health status information of the components. The IASF can then be obtained by subtracting the speed trend term from IAS signals obtained via a magneto-electric speed sensor. A synchro-extraction of the normal S transform (SNST) is proposed to process it via line-pass filtering. Finally, the filtered and reconstructed IASF signal is utilized to draw a two-dimensional polar coordinate map online. A non-stationary-condition test is carried out on the test platform to monitor the morphological characteristics of the valve plate under normal, slight, and severe wear conditions. The polar plot shows significant increases in speed fluctuations and oscillation times within a range from 180° to 270°. The relevant research results reflect that the IAS signal can provide a new method for monitoring the operating status of and conducting fault diagnoses for hydraulic equipment.

An accurate digital model is of great significance to system operation inversion and behavior prediction. The multi-energy domain coupling mechanism of the Electro-mechanical and Hydraulic (EMH) system is complex and has strong nonlinear characteristics. At present, the research mainly focuses on the mechanical-hydraulic coupling characteristics, while the research on the large operating range and the influence of electric motor and load characteristics on the nonlinear dynamics of the EMH system are less. Based on the first principle description, the nonlinear characteristics of the system components are described in this paper. Furthermore, the nonlinear dynamic model of the EMH system described in multi-state space is established based on the Quasi-LPV system. Combined with the experimental data, the structural and non-structural uncertain parameters of system are identified. Finally, the influence of the mechanical characteristics of electric motor, load on the nonlinear dynamics of the EMH system are discussed. Experiments show that the Quasi-LPV models proposed in this paper can accurately reproduce and predict system behavior. It provides technical support for rapid design, selection, and scheme optimization of hydraulic systems in general scenarios.

Due to the non-linear factors of the single loop gear system and the inter-tooth system, is sometimes difficult to establish an accurate nonlinear dynamic model, which leads to the large deviation between the dynamic characteristics and the actual situation. According to the structural characteristics and dynamic mechanism of nonlinear factors, the bond graph power junction with switching characteristics is adopted. This method is used to establish the model of the single loop gear system and the inter-tooth system respectively. On this basis, the amplitude-phase-frequency characteristics of PX single loop gear systems are obtained by numerical simulation analysis. Eventually, the dynamic stability of single loop gear system is judged based on this characteristic index. The study shows that the dynamic stability of PX type single loop gear system is unsteady in the nonlinear state. In addition, it is concluded that when the whole single loop gear system is unstable, its system module also has the same unstability.

Considering that the vibration of the piston pump shell includes not only motion state information, but also energy state information, this study discloses the relationship between the piston pump vibration signal and the operating state by the piston pump shell vibration phase trajectory. Firstly, the high pressure fluid excitation and the vibration speed, displacement, and vibration energy of the pump shell are related. This relationship can be set forth by analysis of the piston pump fluid vibration transmission path. Secondly, according to the vibration frequency traceability, multi-synchrosqueezing transform (MSST) method is used to reconstruct signal. After the integral transformation of the reconstructed signal, the information of vibration speed and displacement can be obtained further. Finally, the trajectory diagram of the shell vibration is constructed based on the vibration speed and displacement. The experiment under different operating conditions are carried out to expound the variation rules of the kinetic energy and potential energy of the piston pump contained in the phase trajectory diagram of the shell vibration. The results show that combined with vibration frequency traceability, MSST can accurately extract the vibration frequency and phase information of shell vibration acceleration signal caused by hydraulic excitation. The operating condition of piston pump has significant influence on kinetic energy and potential energy of piston pump shell. With the increase of system pressure, the distance between the phase trajectory and the vertical zero-shift axis, and the potential energy of the shell increase significantly. With the increase of speed, the maximum vibration speed of phase trajectory diagram and the kinetic energy of shell increase significantly. The phase trajectory diagram of axial piston pump can reflect the kinetic energy and potential energy of the shell more intuitively. This study can provide a theoretical basis and method support for the fault diagnosis and health assessment of key components such as hydraulic pumps, motors.

Considering that the vibration of the piston pump shell includes not only motion state information, but also energy state information, this study discloses the relationship between the piston pump vibration signal and the operating state by the piston pump shell vibration phase trajectory. Firstly, the high pressure fluid excitation and the vibration speed, displacement, and vibration energy of the pump shell are related. This relationship can be set forth by analysis of the piston pump fluid vibration transmission path. Secondly, according to the vibration frequency traceability, multi-synchrosqueezing transform(MSST) method is used to reconstruct signal. After the integral transformation of the reconstructed signal, the information of vibration speed and displacement can be obtained further. Finally, the trajectory diagram of the shell vibration is constructed based on the vibration speed and displacement. The experiment under different operating conditions are carried out to expound the variation rules of the kinetic energy and potential energy of the piston pump contained in the phase trajectory diagram of the shell vibration. The results show that combined with vibration frequency traceability, MSST can accurately extract the vibration frequency and phase information of shell vibration acceleration signal caused by hydraulic excitation. The operating condition of piston pump has significant influence on kinetic energy and potential energy of piston pump shell. With the increase of system pressure, the distance between the phase trajectory and the vertical zero-shift axis, and the potential energy of the shell increase significantly. With the increase of speed, the maximum vibration speed of phase trajectory diagram and the kinetic energy of shell increase significantly. The phase trajectory diagram of axial piston pump can reflect the kinetic energy and potential energy of the shell more intuitively. This study can provide a theoretical basis and method support for the fault diagnosis and health assessment of key components such as hydraulic pumps, motors.

For variable speed pump-controlled hydraulic cylinder system,the nonlinear change of hydraulic system parameters is brought in by large-scale change of speed or load.It causes the control system,which is designed by the linear model,to have the problems such as difficult correction of control parameters,unstable precision or even control instability.In this paper,a multi-model adaptive PID(MMA-PID)control method is proposed by analyzing the state space of a typical variable speed pump-controlled hydraulic cylinder system.According to the nonlinear change of the bulk elastic modulus of oil caused by the change of the system pressure,the system behavior is described by using multiple linear sub-models.A reasonable controller is designed for each sub-model.During the control process,the output weight coefficient of each sub-model is estimated separately through the Kalman filter,and the weighted fusion of all the sub-models control output is used as the final control input of the system.The simulation and experimental results demonstrate that when the working conditions are vary widely,the MMA-PID can adapt to the nonlinear change of system parameters better than the traditional PID,and it owns better control effect and dynamic performance.

针对液压马达驱动负载系统中,马达输出轴的转速波动特性直接影响负载工作稳定性和可靠性的问题,建立典型液压马达-负载系统的动力学模型,阐明液压马达等效弹簧扭转刚度的计算方法;根据非线性动力学原理,分析等效液压弹簧扭转刚度和摩擦转矩对系统转速波动特性的影响机制,提出利用高频采样计数方法对转速波动进行测试与分析.理论分析与实验结果均表明:非线性摩擦转矩、输出容积脉动、负载转矩、油液有效体积弹性模量等因素的变化影响系统的转速波动特性.

The pressure pulsation of axial piston pump is not only an important cause of rotation speed fluctuation,vibration noise and output stability of the hydraulic system,but also the main information source for obtaining fault information.Hydraulic system is characterized by strong noise interference,which leads to low signal-to-noise ratio(SNR)of detection signals.Therefore,it is necessary to dig deep into the system operating state information carried by pressure signals.Firstly,based on flow loss mechanism of the plunger pump,the mapping relationship between flow pulsation and pressure pulsation is analyzed.After that,the pressure signal is filtered and reconstructed based on standard Gabor transform.Finally,according to the time-domain waveform morphology of pressure signal,four characteristic indicators are proposed to analyze the characteristics of pressure fluctuations under different working conditions.The experimental results show that the standard Gabor transform can accurately extract high-order harmonics and phase frequencies of the signal.The reconstructed time-domain waveform of pressure pulsation of the axial piston pump contains a wealth of operating status information,and the characteristics of pulsation changes under various working conditions can provide a new theoretical basis and a method support for fault diagnosis and health assessment of hydraulic pumps,motors and key components.

Volumetric efficiency (VE) is an extremely important index to evaluate the performance of pump and motor. Efforts have been concentrated on the causes and character of leakage loss, but few quantitative analyses of pump kinematic clearances (KCs) identification and nonlinear compression loss caused by air content are discussed. This paper clarifies the nonlinear compression loss resulted from the air content of the oil in detail and proposes an improved flow loss model of the swash-plate axial piston pump (SAPP). Then, combining the improved model with experimental results, the KCs of SAPP are identified. It has been verified that a reasonable sampling path is useful for reducing sampling numbers and guaranteeing identification accuracy. Finally, the identification and quantization of the wear fault of SAPP are realized by analyzing the estimated value of KCs. The proposed method is simple and easy to implement and shows high predictive accuracy. It provides a possible and promoting technology support for the autonomous calibration of the system parameters and the active compensation of the system control.

Abundant system operation state information is included in the electrical signal of the hydraulic system motor. How to accurately extract and classify the operation information of electrical signal is the key to realize the condition monitoring of hydraulic system. The early fault characteristics of hydraulic gear pump hidden in the motor current signal are weak and difficult to extract by traditional time-frequency analysis. Based on the correlation coefficient and artificial bee colony algorithm（ABC）, the parameter optimization of variational mode decomposition（VMD） is realized in this paper. At the same time, the principle of maximum signal correlation coefficient and kurtosis value is adopted to determine the effective intrinsic mode function（IMF）. Moreover, the permutation entropy（PE） and root mean square（RMS） of the effective IMF components are input into the deep belief network（DBN-DNN） as high-dimensional feature vectors. The operation state of gear pump is monitored. The results show that the weak characteristics of current signal of gear pump fault are accurately and stably extracted by this method. The running state of gear pump is monitored and the accuracy of gear fault diagnosis is improved.

针对液压系统在极端工况下非线性特性明显,运行稳定性差的问题,采用了AMESim多学科仿真软件,对多能域耦合闭式液压系统进行了物理建模,通过对典型闭式泵控马达液压系统模型的仿真分析,研究了在不同油液含气量及温度工况下,油液粘度与有效体积弹性模量的变化对闭式泵控马达液压系统稳定性的影响规律;同时,进一步设计了机电液一体化实验平台,对不同含气量、温度工况下,负载阶跃上升与转速阶跃下降激励时的系统稳定特性进行了验证.研究结果表明:油液含气量和温度对闭式液压系统输出稳定性的影响较为明显,随着含气量增加,液压马达转速的超调量随着负载阶跃上升与电机转速阶跃下降,分别增加0.12％和0.18％,系统稳定性减弱;随着温度升高,液压马达转速的超调量分别减小0.09％和4.68％,稳定性增强.

Pumps are vital components in hydraulic equipment, and their malfunction is directly related to the normal operation of the whole system. The hydraulic system is accompanied by the conversion of multi-domain energy during operation. In particular, it exhibits non-stationarity and nonlinearity under variable operating conditions, which brings difficulties to fault diagnosis. In this paper, the instantaneous angular speed (IAS) signal obtained by the equal-angle measurement is studied to diagnose pump faults under non-stationary conditions. For this purpose, a synchroextracting normal S transform method is proposed to extract the time-frequency feature components properly. Then, the extracted signal is reconstructed into a high-dimensional phase space based on the improved C-C method. On this basis, the quantitative analysis indicators of pump state are obtained by the G-P algorithm and small-data method, including correlation dimension, Kolmogorov entropy, and largest Lyapunov exponent. Pump faults can be classified in a chaotic space by using these sensitive features. The results show that the proposed method is capable of diagnosing different states of pumps and robust to the variation of load values.

Abundant system operation state information is included in the electrical signal of the hydraulic system motor.How to accurately extract and classify the operation information of electrical signal is the key to realize the condition monitoring of hydraulic system.The early fault characteristics of hydraulic gear pump hidden in the motor current signal are weak and difficult to extract by traditional time-frequency analysis.Based on the correlation coefficient and artificial bee colony algorithm (ABC),the parameter optimization of variational mode decomposition (VMD)is realized in this paper.At the same time,the principle of maximum signal correlation coefficient and kurtosis value is adopted to determine the effective intrinsic mode function (IMF).Moreover,the permutation entropy(PE)and root mean square(RMS)of the effective IMF components are input into the deep belief network (DBN-DNN)as high-dimensional feature vectors.The operation state of gear pump is monitored.The results show that the weak characteristics of current signal of gear pump fault are accurately and stably extracted by this method.The running state of gear pump is monitored and the accuracy of gear fault diagnosis is improved.

The axial piston pump is a core component for power output conversion in the hydraulic system. Monitoring pump status and diagnosing faults in an optimal way are of profound significance for ensuring system reliability. Currently, considerable studies concentrate primarily on the development of vibration-monitoring technologies. However, due to strong fluid shock and noise, vibration analysis has low signal-to-noise ratio and difficulty in fault location. Therefore, an approach of instantaneous angular speed-based fault detection is introduced in this paper since it has the advantages of short transfer path and non-intrusive measurement. Instantaneous angular speed (IAS) is obtained by cross-period linear interpolation (CLI) algorithm for the voltage square wave induced by a magneto-electric tachometer transducer. Compared with the elapsed time method, CLI has the capacity to precisely capture the speed fluctuation. Weighted angle synchronous averaging (WASA) is then utilized to realize the extraction of abnormal wave components in IAS as a vital signal preprocessing method. Instantaneous angular speed fluctuation (IASF) characteristics of the angular domain are analyzed to study the fault diagnosis under varying working conditions. Moreover, it is proven that after processing, the fault features are extracted in the order spectrum where the deterministic shaft order and its harmonics corresponding to wear characteristics are displayed clearly. Experimental results indicate that IAS has demonstrated more effective and sensitive than vibration signals, thus providing a promising tool for the health monitoring of a pump.

Oil is a key medium for transmitting power and coupling information in the hydraulic transmission system. Accurate calculation and measurement of the dynamic compressibility of the oil have profound significance to the system performance analysis. The present study primarily focuses on the effect of steady pressure on the bulk modulus of static oil. However, changing pressure and flowing oil are the general working conditions in most of hydraulic apparatus. There are few researchers paying attention to the influence of pressure on the compressibility of flowing oil. Considering the log-normal distribution of bubble size in oil, an improved static oil model (Model B) is developed to calculate the bulk modulus of the motionless oil under the dynamic pressure. Then, by deriving Model B, this paper proposes an original flowing oil model (Model C) to determine the effective bulk modulus of flowing oil. Finally, based on the inherent pressure pulsation of the axial piston pump, an innovative online method for measurement of the bulk modulus of flowing oil is presented as it has the advantage of avoiding interference with flow stability. It has been proved that the changes in the flow velocity corresponds to the crucial effect on the effective bulk modulus of flowing oil, especially under the low-flow and low-pressure operation conditions. Those results and analysis provide promoting support for identifying and determining the effective bulk modulus of oil, analyzing the system stiffness, improving the control accuracy, as well as optimizing the mathematical models.

The instantaneous speed of a hydraulic system contains a wealth of operational information, and its accurate extraction is the basis for condition monitoring and fault diagnosis. In order to solve the problem of high hardware requirement for instantaneous speed measurement based on data acquisition card, a new method of high precision measurement is proposed. In this method, the time-displacement information of each tooth is obtained from the pulsed square wave signal of the gear disk collected by magnetoelectric sensors. The time-displacement curve is interpolated by the cubic spline interpolation method, and then the instantaneous speed is calculated by the five-point digital differential formula. The experimental results show that the method improves the speed measurement resolution and reduces the quantization error. The high precision instantaneous speed signal can also be acquired by hardware devices with less teeth and low sampling frequency. The related research results provide a theoretical basis and a method for improving the accuracy of instantaneous speed measurement.

Aiming at the problem that the inner wall of the 90 degree bend is not easy to be welded,a method of getting the moving path of the welding robot based on the movement of the supporting device and its rotary motion is put forward.A new 90 degree bend pipe inner wall surfacing robot is designed.The mechanical structure of the robot body-mechanical arm is determined.This paper expounds the mechanical arm joint and its realization form,using the Lagrange method to establish the motion equation of mechanical arm,the arm movement process in detail the kinematics analysis.It put forward the use of matlab polynomial interpolation method,the drive function was obtained by using Pro/e 3d design software to establish three-dimensional model of mechanical arm,imported into ADAMS,90 degree bend pipe inner wall surfacing robot welding torch head trajectory simulation validation.It can be seen that thesurfacing robot designed by the article can meet the requirements of supporting the transposition mechanism from the analysis results.

为了对振动电机的常见故障类型作出预测和判断,通过基本电磁原理结合振动电机的结构特征,分别计算了振动电机在正常、转子断条和气隙偏心时定子电流的特征频率.结果表明:振动电机正常运行时定子电流中会产生f1±fr的特征频率,转子断条时会同时产生f1±fr和(1±2s)f1的特征频率,气隙偏心时在其定子电流中会产生f1±fr的特征频率且其幅值与偏心程度成正比,通过监测振动电机的定子电流可以判断其工作状态、故障类型以及故障程度.