Simulation Test Rig Research Articles

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.

Research on-orbit temperature variation stability of the positioning accuracy of maintenance interface

The space telescope is running, which is influenced by the rapid temperature difference. The paper analyzes the stability of the space environment of the on-orbit maintenance interface. The influence of temperature changes on the positioning of the interface mechanism is studied. Based on the 3-2-1 kinematic positioning principle, a mathematical model is established, and the mathematical expression of the on-orbit positioning accuracy of the back-end module between the temperature change and the interface layout point is deduced, and the variation quantity and the displacement variation of the angle of the center point are derived. The results show that when the line of AB points coincides with the positioning axis of B point, the rotation angle of the back-end module in the plane composed of A, B, C three points is the smallest. Through the relationship between the four independent variables λ, μ, η, t and the change of the central point ∆E, it is concluded that when A, B, C three-point layout is obtained, to make the back-end module have the highest stability, the order of variable design should be η, t, λ and μ. The suspension wire system was used to build a ground microgravity simulation test rig. The gravity unloading and thermal stress tests were carried out by the balancing mass method. The thermal stress test results prove that the interface can realize kinematics positioning and complete the on-orbit thermal stress release.

Intelligent fault diagnosis of planetary gearbox based on adaptive normalized CNN under complex variable working conditions and data imbalance

In real industrial application, the operating conditions of the planetary gearbox are always variable speed and variable load according to production. Meanwhile, the scarcity of fault data and different working conditions lead to serious data imbalance and distribution differences, which make a great challenge for planetary gearbox fault detection and diagnosis. To address these issues, a novel adaptive normalized convolutional neural network (ANCNN) is developed to accurately and automatically diagnose the different fault locations and severities of planetary gearbox considering the scenarios of complex variable working conditions and data imbalance. First, Teager calculated order (TCO) spectrum is applied to avoid the influences of large speed fluctuations and variable loads, which is an efficient pretreatment approach for the proposed ANCNN. Then, the batch normalization algorithm is adopted to eliminate the feature distribution differences caused by variable operating modes and data imbalance. Finally, in order to automatically adapt to different planetary gearbox diagnosis circumstances, the particle swarm optimization (PSO) strategy is used for optimizing and flexibly deciding the key hyperparameters of the designed model, thereby improving the overall performance of the model. The effectiveness of the presented method is confirmed through experiments on two different planetary gearbox datasets, which are from a generic planetary gearbox for industrial applications and a drivetrain dynamic simulator test rig. In addition, comparison with other mainstream intelligent diagnosis techniques validates the superiority of the presented method. The experimental results demonstrate that the presented method can achieve diagnostic accuracies of better than 99.8%, and also shows excellent stability for the unbalanced data classification.

Perceived comfortable posture and optimum riding position of Indian male motorcyclists for short-duration riding of standard motorcycles

Dimensional incompatibility between rider and motorcycle is one of the most causative factors responsible for the prevalence of musculoskeletal discomfort among motorcyclists. The present study aims to identify the comfortable riding posture (CRP) and optimum riding position (ORP) for improving motorcycle design for better riding experience. The data (through image processing technique) was acquired from 120 Indian male motorcyclists (aged 19–40 years) using a static simulator test-rig. The CRP was achieved by adjusting three controls (handgrip, seat, and footrest of the test-rig), and perceived comfort and discomfort ratings. Weighed mean comfort joint angles of ten body-joints defining CRP were estimated and compared with the earlier studies. The best possible ORP among the nine test conditions (defined by the positions of the three controls) was estimated using Taguchi DOE. The study outcomes will help automobile designers to conceptualize the comfortable standard motorcycles.

Investigation of Aviation Lubricant Aging under Engine Representative Conditions

Measurement of the antioxidant additives during lubricant thermal degradation is a useful method for providing a quantitative basis to understand the performance of the lubricant. In this study, a synthetic ester-based aviation oil was thermally exposed for a period of 500 h under gas turbine aero engine representative conditions using a lubricant/system interaction simulator (L/SIS) test rig. Physical and chemical changes including kinematic viscosity, total acid number (TAN), and oil chemical composition were monitored during the experiment. The change in oil chemical composition, with a particular focus on antioxidant additives, was examined using gas chromatography–mass spectroscopy (GC-MS) techniques. The results indicate that the identified antioxidants in the lubricant, dioctyl diphenylamine (DODPA) and phenyl-α-naphthylamine (α-NPA), were consumed during the degradation process of the oil, with DODPA having a slightly higher depletion rate. Posttest analysis of the stressed samples showed an increase in viscosity and TAN of the lubricant oil in the course of the thermal exposure. Furthermore, the reaction of DODPA and α-NPA in an oil thermally degrading environment was compared using density functional theory (DFT). The calculations indicate a lower energy barrier for the reaction of oil with DODPA.

Diagnosis of mechanical defects using a hybrid method based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and optimized wavelet multi-resolution analysis (OWMRA): experimental study

The early detection of defects in rotating machines before their severity reaches an intolerable threshold has become the priority of the maintenance crew, hence the need to apply or even adapt new reliable methods that can meet this requirement. In this paper, a hybrid approach based on the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), the optimized wavelet multi-resolution analysis (OWMRA), and the Hilbert transform is proposed. The proposed approach is initially applied on experimental signals measured on faulty bearings of the Machinery Fault Simulator (MFS) test rig. Two types of defects are considered: on the outer race and on the inner race. An industrial application carried out on a production machine validates on a large scale, exceeding that of the laboratory, the proposed method. It was then possible to detect potential faults on a turbo-alternator group GZ 1164.2 operating in real industrial conditions in the largest fertilizer products company in Algeria. The obtained results show the power of the proposed approach to get reconstructed signals less noisy, containing more information and highlighting the precise nature of the defect and its severity in different configurations, regardless of its type. Finally, the main contribution of this study is to show that the application of the proposed approach is very practical on signals measured on real industrial rotating machines to detect the potential mechanical faults.

Numerical calculation and experimental study on friction and lubrication of Stirling engine piston ring

To solve the practical problem of Stirling engine piston ring, numerical model on friction and lubrication were established based on average Reynolds equation theory. Numerical calculation results show: piston rings are in the mixed lubrication state which gas lubrication film and micro-convex body contact existing simultaneously; contact pressure is 2 orders of magnitude less than gas film pressure; contact pressure is approximately linearly related to mean gas pressure. Simulated test rig was built and experimental results show: high-pressure working gas leak to intermediate chamber through piston rings, and the pressure of intermediate chamber drops sharply at lowest pressure of circulation; piston ring wear increases when rotational speed or working pressure increase. The accuracy of numerical model was proved by experimental phenomena and test data.

Assessment of prediction accuracy of droplet-film-interaction – numerical simulation and experimental test rig validation of water film suction slots for low pressure steam turbine guide vanes

Assessment of prediction accuracy of droplet-film-interaction – numerical simulation and experimental test rig validation of water film suction slots for low pressure steam turbine guide vanes

Three-dimensional simulation and experimental validation of solar air heater having sinusoidal rib

ABSTRACT A new geometry of roughness in the sinusoidal form has been investigated computationally using Computational Fluid Dynamics (CFD) software for examining the influence of roughness on heat transfer and fluid friction in solar air heater and results obtained have been compared with experimental results. The simulated results for smooth solar air heater are compared with Dittus-Boelter equation for heat transfer and Blasius equation for fluid friction. The deviation of simulated results are found to be 7.55% and 16.91%, respectively. In order to validate the simulated results experimental test rig was fabricated and experiments were carried out for the same set of parameters used in the simulation. The experimental results indicate that for the roughened absorber plate having a sinusoidal rib, the variation in heat transfer is within 9% from that of simulated results and for fluid friction, deviation is within 4%. The optimal value of thermohydraulic performance (THP) is obtained 2.05 for roughness pitch (P) = 10 mm and Reynolds number (Re) = 4000, where enhancement ratio of Nusselt number (Nur/Nus) and friction factor (ƒr/ƒs) are 2.48 and 1.76, respectively. The experimental value of THP is found to be within 6.77% of the value indicated by CFD analysis. The results are also compared with the triangular and square rib and found that the optimal THP of the proposed rib is 20.06% and 33.31% more.

Simulation method of impact load for vehicle drivetrain on durability test rig

Fatigue and durability tests are important to develop or to optimize the vehicle drivetrain system. Using the vehicle drivetrain road load simulation test rig to reproduce the longitudinal driving load of the vehicle on the real road and the vertical impact load caused when the vehicle is on a bumpy pavement. In order to improve the control accuracy and convergence speed, an iterative learning control (ILC) method is presented. After 10 times of learning, the control error of iterative learning control method is 4.8 %, it is better than the 7.1 % error achieved by proportional-integral-derivative (PID) control. The simulation results demonstrate that the ILC can improve the convergence rate and increase the tracking accuracy than the PID control method.

Fault diagnosis of rolling bearings in non-stationary running conditions using improved CEEMDAN and multivariate denoising based on wavelet and principal component analyses

This paper presents a fault diagnosis method for rolling bearings working in non-stationary running conditions. The proposed approach is based on an improved version of the improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), the multivariate denoising using wavelet analysis and principal component analysis (PCA), the spectral kurtosis, and the order tracking analysis (OTA). The results show that the improved CEEMDAN has completely decomposed the raw signal into different intrinsic mode functions (IMFs) representing the natural oscillatory modes embedded into the signal. The most relevant IMF from which the defect was extracted is selected by the kurtogram plot which allows locating the optimal frequency band having the highest kurtosis value. Multivariate denoising based on wavelet analysis and PCA is used to increase the signal-to-noise ratio (SNR) of the selected IMF. The results show the great contribution of the denoising approach when comparing the selected denoised IMF with the original one. Finally, order tracking analysis is applied on the denoised IMF’s envelope to remove the effect of speed variation, and an envelope order spectrum is obtained. The proposed approach is first applied on theoretical signal simulating rolling bearing defect in variable regime including three different phases. The final order spectrum shows exactly the simulated defect order and several of its harmonics. For the experimental validation, several signals of defective rolling bearings have been measured on the Machine Fault Simulator test rig in variable regime. Despite the combined variable regime including acceleration-constant regime-deceleration, at the same time, the obtained results indicate the efficiency of the proposed method to extract the fault order with high accuracy. The maximum error between the theoretical order and the experimentally obtained one was 1.3% for outer race defect and 1% for inner race defect. Finally, the performances of the proposed method are compared to those of another diagnosis method designed for variable regime conditions. Both outer race and inner race defects are considered in acceleration regime. The results show the superiority of the proposed method to highlight the defect order with highest clarity.

A Local Weighted Multi-instance Multi-label Network for Fault Diagnosis of Rolling Bearings Using Encoder Signal

Rolling bearings are the key components of modern machinery, and thus, the diagnosis of bearing faults plays a crucial role in ensuring the reliable operation of the equipment. Due to the limitation of cost and environmental conditions, the traditional fault diagnosis method based on the vibration signal is not always suitable for practical use. An encoder is widely used in the mechanical transmission system, and its signal contains rich information about health status and working conditions. However, the encoder signals are mostly used to monitor the rotational speed in the industrial and not considered as an alternative to the vibration signal. In this article, a framework based on a local weighted multi-instance multilabel (LWMIML) network is proposed to make full use of the information contained in the encoder to achieve the purpose of bearing fault diagnosis. This framework first constructs the instance generator to acquire feature vectors. On this basis, a local weighted strategy based on the MIML network is used to enhance the potential association between features and labels. Finally, the superiority of this method is verified by the data of the fault simulation test rig. The results indicate that the proposed method offers a promising tool, which will help to reduce the cost of future intelligent fault diagnosis systems.

Model-Based Fault Detection and Identification for Prognostics of Electromechanical Actuators Using Genetic Algorithms

Traditional hydraulic servomechanisms for aircraft control surfaces are being gradually replaced by newer technologies, such as Electro-Mechanical Actuators (EMAs). Since field data about reliability of EMAs are not available due to their recent adoption, their failure modes are not fully understood yet; therefore, an effective prognostic tool could help detect incipient failures of the flight control system, in order to properly schedule maintenance interventions and replacement of the actuators. A twofold benefit would be achieved: Safety would be improved by avoiding the aircraft to fly with damaged components, and replacement of still functional components would be prevented, reducing maintenance costs. However, EMA prognostic presents a challenge due to the complexity and to the multi-disciplinary nature of the monitored systems. We propose a model-based fault detection and isolation (FDI) method, employing a Genetic Algorithm (GA) to identify failure precursors before the performance of the system starts being compromised. Four different failure modes are considered: dry friction, backlash, partial coil short circuit, and controller gain drift. The method presented in this work is able to deal with the challenge leveraging the system design knowledge in a more effective way than data-driven strategies, and requires less experimental data. To test the proposed tool, a simulated test rig was developed. Two numerical models of the EMA were implemented with different level of detail: A high fidelity model provided the data of the faulty actuator to be analyzed, while a simpler one, computationally lighter but accurate enough to simulate the considered fault modes, was executed iteratively by the GA. The results showed good robustness and precision, allowing the early identification of a system malfunctioning with few false positives or missed failures.

Transmission characteristics of planetary gear wear in multistage gear transmission system

Gear tooth surface wear is a common failure mode. It takes a long time and can cause other major faults. The wear fault signal is weak and hard to identify. This paper reveals the transmission characteristics of the planetary gear wear and the relationship between multistage gear meshing through the transmission characteristic analysis. Taking the multistage gear transmission system fault simulation test rig as the research object, a three-dimensional solid rigid-flexible coupling model of the system was established. The contact force signals from each pair of gears in the state of planetary gear wear were obtained by dynamic simulation. The test signals of the fixed-axis gearbox and planetary gearbox were obtained under normal and planetary gear wear states. Comparing the transmission characteristics of the system under normal and planetary gear wear states, the vibration mechanism of the wear fault and the correlative characteristic between gearboxes were revealed.

Strength Evaluation of a Bogie Frame by Different Methods

Some crucial loads that current strength design specifications have not taken into account are also considered when assessing the strength of a bogie frame. Calculation methods of these loads come from load analysis. Finite element simulation and fatigue test rig have been used to assess static strength and fatigue strength of a bogie frame. In addition to the two methods, actual running test is also used to assess bogie frame fatigue strength. In finite element simulation method, endurance limit and modified Goodman fatigue limit diagram are two important tools to judge whether fatigue strength of a bogie frame meets requirement. In actual running test method, Miner linear cumulative damage rule is used to assess bogie frame fatigue strength.

A Microcontroller Based Intelligent Traffic Control System

A new microcontroller based intelligent traffic control system is proposed in this paper. Instead of changing traffic lights automatically for a given interval, this system allows passing the vehicles considering the number of vehicles on the roads. An Atmega 32 microcontroller and infrared sensors (IR sensors) are used to implement the traffic system. An algorithm is also developed for this purpose. The system is simulated and implemented also by constructing a test rig. The results from the simulation and experimental test rig confirm its appropriateness of using in the roads of different cities. No further processing scheme is required for this intelligent traffic control system.

Vehicle braking force distribution with electronic pneumatic braking and hierarchical structure for commercial vehicle

Brake by wire that allows a number of braking functions exists on commercial vehicles under the name electronic pneumatic braking system, which can improve braking comfort and safety of commercial vehicle. The design of braking force distribution control method has drawn much more attention. Considering structure characteristics of electronic pneumatic braking system, a control method with a three-layer hierarchical structure is proposed. The first layer presents an estimation method towards vehicle mass and centre of gravity combining Kalman filter with recursive least square. The second layer is developed by designing a fixed relationship between the brake pedal displacement and vehicle braking deceleration. A deceleration control method that only uses brake pedal displacement as input is applied to make the vehicle follow the desired deceleration. The third layer includes a braking force distribution control method between the front and rear axles. The vehicle deceleration can be achieved with a smooth axle load transfer process based on linear matrix inequality. In addition, the controllers of wheel slip rate and valve hysteresis compensation are designed to improve control accuracy and efficiency. Utilizing a hardware-in-the-loop simulation test rig of electronic pneumatic braking system, the experiment results show that the control method can improve the braking performance of vehicle.

BikeShake: the design of an indoor simulator dedicated to motorcycle ride testing as an interactive project

A servo-hydraulic road simulator test rig (aka four-poster) can play a key role in testing and development of road vehicles. Its use for durability testing, NVH analysis, suspension setup optimization etc. is widespread. Engineers often make use of four-poster testing to validate their dynamic simulation models as well. The use of a so-called four poster is normally restricted to four-wheeled vehicles, typically passenger cars and light commercial vehicles. Motorbikes might also require similar RD however, there are not many specific rigs around. This work proposes a method to retrofit a four-poster into a two-poster dedicated to motorbikes by means of a simple auxiliary structure: the so-called BikeShake. A case study has been reported at the end of the paper to validate the project.

Analysis of electrical drive speed control limitations of a power take-off system for wave energy converters

The active control of wave energy converters with oil-hydraulic power take-off systems presents important demands on the electrical drives attached to their pumps, in particular on the required drive accelerations and rotational speeds. This work analyzes these demands on the drives and designs reliable control approaches for such drives by simulating a wave-to-wire model in a hardware in-the-loop simulation test rig. The model is based on a point absorber wave energy converter, being the wave, hydrodynamic and oil-hydraulic part simulated in a computer that sends and receives signals from the real embedded components, such as the drive generator, controller and back-to-back converter. Three different control strategies are developed and tested in this test rig and the results revealed that despite the drive limitations to acceleration levels, well above 1 × 104 rpm/s, these do not significantly affect the power take-off efficiency, because the required acceleration peaks rarely achieve these values. Moreover this drive is much more economical than an oil-hydraulic and equivalent one that is able to operate at those peaks of acceleration.

Multi-feature entropy distance approach with vibration and acoustic emission signals for process feature recognition of rolling element bearing faults

To accurately reveal rolling bearing operating status, multi-feature entropy distance method was proposed for the process character analysis and diagnosis of rolling bearing faults by the integration of four information entropies in time domain, frequency domain and time–frequency domain and two kinds of signals including vibration signals and acoustic emission signals. The multi-feature entropy distance method was investigated and the basic thought of rolling bearing fault diagnosis with multi-feature entropy distance method was given. Through rotor simulation test rig, the vibration and acoustic emission signals of six rolling bearing faults (ball fault, inner race fault, outer race fault, inner ball faults, inner–outer faults and normal) are gained under different rotational speeds. In the view of the multi-feature entropy distance method, the process diagnosis of rolling bearing faults was implemented. The analytical results show that multi-feature entropy distance fully reflects the process feature of rolling bearing faults with the change of rotating speed; the multi-feature entropy distance with vibration and acoustic emission signals better reports signal features than single type of signal (vibration or acoustic emission signal) in rolling bearing fault diagnosis; the proposed multi-feature entropy distance method holds high diagnostic precision and strong robustness (anti-noise capacity). This study provides a novel and useful methodology for the process feature extraction and fault diagnosis of rolling element bearings and other rotating machinery.