Simulation Test Rig Research Articles

ResNet diagnosis of rotor faults in oil transfer pumps

To address rotor imbalance and misalignment in oil transfer pumps, an innovative diagnostic framework using Residual Network (ResNet) is proposed. The model incorporates advanced signal processing algorithms and strategic sensor placement to enhance diagnostic efficacy. A fault simulation test rig captured vibration signals from eight key measurement points on the pump. One-dimensional and multi-dimensional signal processing techniques generated comprehensive datasets for training and validating the model. Sensor placement optimization, focusing on the bearing seat's axial direction, inlet flange's vertical direction, and outlet flange's axial direction, increased rotor fault sensitivity. Time-frequency data processed via Short-Time Fourier Transform (STFT) achieved the highest diagnostic accuracy, surpassing 98 %. This study highlights the importance of optimal signal processing and precise sensor placement in improving the accuracy of diagnosing rotor faults in oil transfer pumps, thus enhancing the operational reliability and efficiency of energy transportation systems.

Research on bearing fault diagnosis based on laser vibrometer

As general components in machinery, rolling bearings are also fault prone components. And unexpected faults will bring immeasurable loss to economy, personnel, etc. Therefore, fault detection and diagnosis are of paramount importance. As the carrier of fault information, component response signal is the most concerned part in fault diagnosis researches. The detection methods for response signal can be divided into contact and non-contact detection. Compared with the contact detection, laser Doppler vibrometer has the advantage of no contact, no damage and dynamic measurement. Thus, this paper progresses theoretical and experimental researches on non-contact detection of bearing wear fault based on laser Doppler vibrometer. Firstly, the vibration measurement principle of laser Doppler vibrometer is analyzed in this paper. On account of the principle, the internal optical path and signal flow of the single point laser vibrometer is established and analyzed. Secondly, in order to carry out the non-contact detection test, an optical measuring system based on a single point laser vibrometer is built to collect signals. Also, a bearing wear fault simulated test rig is built to provide fault response signals. Based on the above built test devices, the detection tests of the intact and faulty bearings are carried out. Lastly, through the analysis of collected signals of bearings with wear of different parts in time domain and frequency domain, the characterizations of the corresponding fault are obtained so as to implement the fault diagnosis, which prove the effectiveness of laser vibration detection method for fault detection.

Analysis of wheel-rail adhesion redundancy considering the third-body medium on the rail surface

PurposeIn response to the problem of insufficient traction/braking adhesion force caused by the existence of the third-body medium on the rail surface, this study aims to analyze the utilization of wheel-rail adhesion coefficient under different medium conditions and propose relevant measures for reasonable and optimized utilization of adhesion to ensure the traction/braking performance and operation safety of trains.Design/methodology/approachBased on the PLS-160 wheel-rail adhesion simulation test rig, the study investigates the variation patterns of maximum utilized adhesion characteristics on the rail surface under different conditions of small creepage and large slip. Through statistical analysis of multiple sets of experimental data, the statistical distribution patterns of maximum utilized adhesion on the rail surface are obtained, and a method for analyzing wheel-rail adhesion redundancy based on normal distribution is proposed. The study analyzes the utilization of traction/braking adhesion, as well as adhesion redundancy, for different medium under small creepage and large slip conditions. Based on these findings, relevant measures for the reasonable and optimized utilization of adhesion are derived.FindingsWhen the third-body medium exists on the rail surface, the train should adopt the low-level service braking to avoid the braking skidding by extending the braking distance. Compared with the current adhesion control strategy of small creepage, adopting appropriate strategies to control the train’s adhesion coefficient near the second peak point of the adhesion coefficient-slip ratio curve in large slip can effectively improve the traction/braking adhesion redundancy and the upper limit of adhesion utilization, thereby ensuring the traction/braking performance and operation safety of the train.Originality/valueMost existing studies focus on the wheel-rail adhesion coefficient values and variation patterns under different medium conditions, without considering whether the rail surface with different medium can provide sufficient traction/braking utilized adhesion coefficient for the train. Therefore, there is a risk of traction overspeeding/braking skidding. This study analyzes whether the rail surface with different medium can provide sufficient traction/braking utilized adhesion coefficient for the train and whether there is redundancy. Based on these findings, relevant measures for the reasonable and optimized utilization of adhesion are derived to further ensure operation safety of the train.

Inter-turn short circuit and demagnetization fault diagnosis of ship PMSM based on multiscale residual dilated CNN and BiLSTM

Inter-turn short circuit (ITSC) and demagnetization of permanent magnet synchronous motors (PMSMs) can lead to serious ship accidents, timely and accurate fault diagnosis of these faults is very important. A multi-signal fusion fault diagnosis method (MD-CNN-BiLSTM) is proposed based on multi-scale residual dilated convolutional neural network (D-CNN) and bidirectional long and short-term memory (BiLSTM) for PMSM fault diagnosis. This method first takes three-phase current and vibration signals as input; uses a three-column parallel CNN structure with different scales to extract both global signal and local feature. A residual connection in the expanded CNN is then used to eliminate the problems of gradient disappearance or explosion; and finally, BiLSTM is used to further extract features and identify the fault. A 2.2 kW permanent magnet synchronous motor was used to build a fault simulation test rig. The motor stator was rewound to simulate the ITSC fault, and different sizes of permanent magnets were replaced to simulate demagnetization fault. ITSC, demagnetization and their coupled faults were simulated under 10 specific motor speeds and loads respectively. The test proved that the diagnostic accuracy of the proposed method was 4.2% higher than that of ordinary CNN and 29.06% higher than that of BiLSTM. It also had the best diagnostic effect under the noise interference of different intensities. It was verified that the proposed method has good noise interference and strong classification ability.

Research on Improving the Tribological Properties of Bearings under Cryogenic Conditions

Bearings, as one of the most central components of rotating equipment, are widely used both in servo steering gear, aerospace and other fields. However, for extremely cryogenic conditions, the life of bearings is low, so it is necessary to carry out the tribological design of bearings to improve its cryogenic performance. In this paper, four kinds of optimized and improved plain bearings are designed. The tribological tests of these four bearings under extreme cryogenic working conditions were carried out using the developed bearing simulation test rig. The results show that under the same load and rotational speed conditions, the preparation of micro-weave structure on the surface of the shaft tile or the preparation of composite coating on the surface of the journal can improve the friction and wear performance of the bearings to a certain extent. When both methods are used at the same time, the friction reduction and anti-friction wear effect of the sliding bearing is better. This study not only provides theoretical guidance and technical support for improving the cryogenic tribological performance of bearings, but also has important practical significance for the future development of rotating equipment in the low-temperature field.

Design, construction and modeling of a small-scale high temperature field rotor test rig

In-field validation of radiation thermometer performance is time consuming and expensive, especially when prototype experiments are performed. This study focuses on the development of a novel small-scale high temperature field simulation test rig for measuring turbine blade surface temperatures under changing environmental conditions. When developing and testing a radiation thermometer, the testing is typically performed directly on a test rig that can simultaneously provide a standardized environment and compare temperature data. This apparatus allows for static and dynamic temperature testing in a hostile environment by combining temperature, particle, and atmospheric effects. In the present study, a test rig will be utilized to analyze and validate the radiation thermometer, which will be subjected to harsh combined environmental variables with a temperature range of up to 2000K. Notably, the rotating head structure of the two materials allows for the application of a vast range of temperature measurements (700–2000 K), which is a distinctive characteristic of the design. The requirements of the test rig are defined based on the specimens to be tested. The necessity for the combined complete test setup, as well as its design and functionality, are discussed in this paper. Finally, validation experiments are conducted to demonstrate the test rig's accuracy in measuring turbine blade surface temperature, which is 0.25%.

Effect of flow rate and CNM concentration in nanofluid on the performance of convective heat transfer coefficient

The aim of this study is to investigate the thermal performance of water-based Carbon Nano Material (CNM) nanofluids, particularly in the convective heat transfer coefficient (h) parameter, and to analyze the effects of nanoparticle concentration and flow rate on an experimental heat transfer system. To achieve this, the researchers prepared the nanofluid through a 2-step method. In the first step, we mixed the nanoparticles with the base fluid using a magnetic stirrer to ensure homogenization, with the CNM-Water ratio set at 30, 75, 120, and 150 ppm. In the second step, we characterized the prepared samples, determining their size, composition, and particle morphology through PSA and SEM-EDX examination, as well as measuring their density (ρ) and specific heat (Cp). The experiments were carried out using a flow rate simulation test rig with a data acquisition system, at different flow rates of 0.2, 0.6, 1, and 1.4 L/min. Temperature (T) was measured at the inlet, outlet, and heater to determine the convective heat transfer coefficient value. The study successfully investigated the direct impact of CNM concentration and flow rate, with the results showing a consistent and expected value of the coefficient compared to previous studies. The highest coefficient value was observed at 150 ppm CNM-Water ratio and a flow rate of 1.4 L/min, with a value of 1825.37 W/(m2.K).

Dynamic modelling of deep groove ball bearings with different local defects considering skidding and thermal elastohydrodynamic lubrication

The vibration characteristics and skidding behaviour of deep groove ball bearings (DGBBs) are significantly influenced by the evolution of local defects and thermal effects. In previous studies, the influences of skidding and thermal effects were not considered in order to simplify the model of defective bearings. But the presence of skidding and thermal should not be ignored to accurately simulate the operation of bearing. To gain a comprehensive understanding of the operational mechanism of defective bearings, it is crucial to examine the skidding and thermal characteristics of various defect types using dynamic modelling approaches. In this study, the DGBB dynamic model for seven types of defects is established, which considers the self-rotation, rotation, and radial motion of ball, the contact force, ball/cage and ball/raceway skidding, and the effects of thermal elastohydrodynamic lubrication (TEHL). Experimental data from a machine fault simulator test rig is utilized to validate the accuracy of the proposed modelling methods. The results indicate that compound defects (CDs) result in higher vibration amplitudes and more severe skidding phenomena compared to single defects (SDs). Furthermore, compound defects exhibit a greater thermal effect on the oil film in the contact area than SDs, significantly impacting the operational performance of the bearing.

On the effect of temperature in friction force measurements for a simplified piston cylinder set-up: Squeeze film combined with minimum oil film thickness measurements and viscosity index effect

The lubricated interface at the piston-ring and liner and its interaction with different lubricants and testing conditions is examined in terms of experimental measurements that show the minimum oil film thickness developed at the lubricated or depending on conditions partly lubricated conjunction and the surface interaction intensity, as measured from the friction sensor. An analysis is carried out with the use of different parameters for the experiments as well as different lubricants in a simplified piston-ring simulation test rig. This analysis is further enhanced with the squeeze film effect investigations close to the stroke reversals and together with cavitation initiation and load-carrying effect results from previous experimental data, light is shed on the interacting surface’s behaviour at the different lubrication regimes. Another parameter, the viscosity index of the lubricant is used as an indication of the effects of squeeze film shift and friction force measurements and how the load and temperature effect are influencing the squeeze film.

Experimental study for evaluating the response of the power take off of a point absorber wave energy generation system using a hydraulic wave simulator

The increase in energy prices and the need to control the rate of climate change are two of the biggest challenges facing the planet. Despite the fact that the wave energy technology is still in its infancy, it is considered one of the most promising renewable energy sources that exhibits a large potential for sustainable growth towards Net Zero. In this paper, a novel design methodology for a new wave energy generation system is presented and the performance of its power take-off (PTO) or drivetrain is analysed. A complete description of the wave energy generation system is presented including the general concept of the power take-off, configuration, mechanical design, electrical system, simulation test-rig, expected power out and the force load on the system. The results from the power take-off system obtained from the simulation process of the test-rig using a hydraulic linear wave simulator, show that the change in the electric load produces different power and force values and consequently a wide range of efficiencies. It has been noticed that increasing the electric load leads to a better efficiency, i.e., high power and force values. However, there is a certain threshold where the system stops behaving in its high performance and its efficiency drops notably. This threshold depends not only on the electric load, but also on the values of the fixed parameters, i.e., wave cycle time, wave height and frequency. The finding will support the complete design of a point absorber system, including the buoy design, to interact with the expected level of wave patterns.

Experimental study on the evolution characteristics of gas pressure field for true triaxial cyclic mining

The evolution characteristics of coal seam strain and gas pressure in circular mining were explored by conducting physical simulation tests on the influence of cyclic stress on coal seam parameters under different initial gas pressures using a large true triaxial physical simulation test rig. The evolution characteristics of gas pressure and coal seam strain with the number of cycles and gas pressure were discussed. The test results showed that during cyclic loading and unloading, the coal seam is cracked under stress and new cracks are generated, and the new fractures cause the overall pressure of the coal seam methane to decrease by adsorbing more free gas. In the loading stage, the coal skeleton is squeezed by stress, which causes the space of coal seam pores and cracks to shrink, the free gas in the pores and fractures of the coal seam is extruded, and the strain and gas pressure of the coal seam increase with the increase of stress. In the unloading stage, the reduction of stress leads to the coal skeleton tending to return to its initial state, the free gas in the pores is transported and enriched into the fractures of the coal seam, and the strain and gas pressure of the coal seam are gradually reduced. With the increase of the number of cycles, the damage of the coal seam increases and deformation occurs, the increasing amplitude of gas pressure gradually increases during loading, and the decreasing amplitude of gas pressure gradually decreases when unloading, and the closer the distance from the pressurized boundary, the greater the amplitude change. Under different initial gas pressure conditions, the greater the initial gas pressure, the greater the increasing amplitude of gas pressure and the smaller the decreasing amplitude.

Fabrication of a test rig for gearbox fault simulation and diagnosis

1. Huňady R, Pavelka P, Lengvarský P. Vibration and modal analysis of a rotating disc using high-speed 3D digital image correlation. Mechanical Systems and Signal Processing 2019;121:201–214. https://doi.org/10.1016/j.ymss.... CrossRef Google Scholar

RHONN-Modeling-Based Predictive Safety Assessment and Torque Vectoring for Holistic Stabilization of Electrified Vehicles

Improving vehicle safety and reducing traffic accidents have always been of cardinal importance in vehicle dynamics control fields. A reasonable and comprehensive safety index that characterizes the vehicle's safe region is the most challenging aspect of research. With the linear dynamics model as the benchmark, this article uses the deviation of yaw rate and vehicle sideslip angle from the corresponding linear response as the lateral stability indices. Meanwhile, the maximum slip ratio of the driven wheels is selected as the longitudinal stability index. The <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">safety indicator</i> , a quantitative index featuring the safety degree of vehicle planar motions, is then inferred by a fuzzy inference system using the lateral and longitudinal stability indices. As such, the recurrent high-order neural network model predicts the vehicle states. Based on the predicted states, a safety indicator is then derived by using fuzzy inference system, which can assess the safety of a driver's control commands. In the case of an improper driving torque demand given by the driver, the torque correction process is immediately conducted to maintain the vehicle in a safe region. Finally, two typical scenarios—slippery curves and double lane changes in low friction roads—are simulated on the MATLAB/Simulink-CarSim cosimulation platform. The hardware-in-the-loop experiments are also conducted on a driving simulator test rig, validating the performance of the developed algorithms. The holistic stability performance of the in-wheel motor driven vehicle is thoroughly analyzed and compared using three existing methods. The simulation and experimental results validate the effectiveness and feasibility of the proposed method.

Lightweight Design of Commercial Vehicle Cab Based on Fatigue Durability

To better improve the lightweight and fatigue durability performance of the tractor cab, a multi-objective lightweight design of the cab was carried out in this study. First, the finite element model of the cab with counterweight loading was established and then confirmed by the physical testing, and use the inertial relief method to obtain stress distribution under unit load. The cab-frame rigid-flexible coupling multi-body dynamics model was built by Adams/car software. Taking the cab airbag mount displacement and acceleration signals acquired on the proving ground as the desired signals and obtaining the fatigue analysis load spectrum through Femfat-Lab virtual iteration. The fatigue simulation analysis is performed in nCode based on the Miner linear fatigue cumulative damage theory. Then, with the mass and fatigue damage values as the optimization objectives, the bending-torsional stiffness and first-order bending-torsional mode as constraints, the thickness variables are screed based on the sensitivity analysis. The experimental design was carried out using the Optimal Latin hypercube method, and the multi-objective optimal design of the cab was carried out using the Kriging approximation model fitting and particle swarm algorithm. The weight of the optimized cab is reduced by 7.8% on the basis of meeting the fatigue durability performance. Finally, a seven-axis road simulation test rig was designed to verify its fatigue durability. The results show the optimized cab can consider both lightweight and durability.

Experimental Investigation: Vibration Measurement of a Rotating Blade with Digital Image Correlation and Blade Tip-Timing.

High cycle fatigue has been known as an important form of aeroengine blade failure. This study aims to achieve a method of investigation for a rotating blade vibration measurement, combining the two non-contact optical techniques of digital image correlation (DIC) and blade tip-timing (BTT). Dynamic parameters of a thin-blade were obtained on a stationary vibration platform with stereo-DIC system. Meanwhile, the finite element analysis (FEA) of this thin-blade was performed within different rotating speeds. Then, the set of thin-blades was mounted in a simulated compressor test rig equipped with BTT and a wireless strain gauge (SG) system. A rotor speed sweep experiment was carried out and the blade synchronous resonance parameters were extracted. Results show that the displacement mode shapes match well between DIC and FEA, and that MAC values of the first six order modes are over than 0.88. The predicting strain from the FE model and SG agreed to within 32.41% in the worst case, and the predicting strain from the DIC model corresponds to 28.53% in the worst case. This is an effective non-contact, high-precision full-field deformation measurement method that is worth exploring for structural design and dynamic strain assessment of vibrating components.

A novel intelligent method for inter-shaft bearing-fault diagnosis based on hierarchical permutation entropy and LLE-RF

Since the transmission path of inter-shaft bearing-fault signal is complex, a fault feature extraction method based on hierarchical permutation entropy (HPE) and locally linear embedding (LLE) algorithm is proposed in this paper. In this method, HPE is utilized to extract fault information of signals, and LLE is utilized to reduce and fuse high-dimensional fault features of multi-sensors to construct fault samples. Then, the random forest (RF) model is established to diagnose the faults of the inter-shaft bearings. The fault simulation test rig with the inter-shaft bearing is built to simulate the normal bearing, inner ring fault, outer ring fault, and rolling ball fault, and the data are collected to verify the HPE-LLE-RF fault diagnosis algorithm of inter-shaft bearings established in this paper. The experimental results show that the proposed algorithm can extract the fault features of inter-shaft bearings effectively with a fault diagnosis accuracy of 93.3% without overfit phenomenon.

Fault diagnosis of rotating machinery based on graph weighted reinforcement networks under small samples and strong noise

Available fault vibration signals of large rotating machines are usually limited and consist of strong noise. Existing deep learning methods do not sufficiently extract the correlation relationship between samples, and the process of extracting features is easily disturbed by noise. Therefore, the accuracy of rotating machinery fault diagnosis needs further improvement. A graph-weighted reinforcement network (GWRNet) is proposed to accurately diagnose the faults of rotating machines under small samples and strong noise. First, an adjacency matrix was constructed by measuring the Euclidean distance of the time- and frequency-domain characteristics of small samples to achieve the pre-classification of nodes. Second, the node feature aggregation strategy was designed by dynamically enhancing the largest weight of the multiheaded attention matrix to suppress strong noise interference. Finally, the effectiveness of the proposed method was verified using datasets from the drivetrain diagnostics simulator (DDS) test rig and wind turbine gearboxes.

Multibody Model for the Design of a Rover for Agricultural Applications: A Preliminary Study

The employment of vehicles such as rovers equipped with automictic and robotic systems in agriculture is an emerging field. The development of suitable simulation models can aid in the design and testing of agricultural rovers before prototyping. Here, we propose a simulation test rig based on a multibody model to investigate the main issues connected with agricultural rover designs. The results of the simulations show significant differences between the two structures, especially regarding the energy savings, which is a key aspect for the applicability of a rover in field operations. The modular structure of the proposed simulation model can be easily adapted to other vehicle structures.

Experimental Study on Crack Extension Rules of Hydraulic Fracturing Based on Simulated Coal Seam Roof and Floor

Hydraulic fracturing can increase the fracture of coal seams, improve the permeability in the coal seam, and reduce the risk of coal and gas outburst. Most of the existing experimental specimens are homogeneous, and the influence of the roof and floor on hydraulic fracture expansion is not considered. Therefore, the hydraulic fracturing test of the simulated combination of the coal seam and the roof and floor under different stress conditions was carried out using the self-developed true triaxial coal mine dynamic disaster large-scale simulation test rig. The results show that (1) under the condition of triaxial unequal pressure, the hydraulic fractures are vertical in the coal seam, and the extension direction of hydraulic fractures in the coal seam will be deflected, with the increase of the ratio of the horizontal maximum principal stress to the horizontal minimum principal stress. The angle between the extension direction of the hydraulic fracture and the horizontal maximum principal stress decreases. (2) Under the condition of triaxial equal confining pressure, the extension of hydraulic fractures in the coal seam are random, and the hydraulic fracture will expand along the dominant fracture surface and form a unilateral expansion fracture when a crack is formed. (3) When the pressure in one direction is unloaded under the condition of the triaxial unequal pressure, the hydraulic fractures in the coal seam will reorientate, and the cracks will expand in the direction of the decreased confining pressure, forming almost mutually perpendicular turning cracks.

Sparsity-assisted adaptive chirp mode decomposition and its application in rub-impact fault detection

The rub-impact is a familiar failure and its timely detection is vital to maintain the security of whole system. The change of dynamic behavior caused by rub-impact fault can be reflected by the fast-oscillating instantaneous frequency (IF) of the vibration signal. The recently developed adaptive chirp mode decomposition (ACMD) has exhibited satisfactory capability in extracting fast-oscillating IF. However, the ACMD is easily affected by the noise, which greatly limits its application scopes. To overcome this issue, a novel method named sparsity-assisted adaptive chirp mode decomposition (S-ACMD) is developed, which incorporates sparsity-assisted IF update scheme that fully exploits the sparse prior of fast-oscillating IF caused by rub-impact fault. Meanwhile, the parameter selection method for getting optimal results is described. The efficacy of the proposed S-ACMD is confirmed by the vibration signals from dynamic simulation and rotor test rig, and the results show that it has strong anti-noise ability and can accurately extract rub-impact fault related fast-oscillating IF even in noisy cases.