Power-shift Steering Transmission Research Articles

Określanie progu awarii na podstawie podobieństwa jako metoda pozwalająca na przewidywanie trwałości resztkowej systemu

An accurate determination of the system failure threshold is an essential requirement in achieving an appropriate system residual life prediction and a reasonable planned maintenance strategy optimization afterward for degradation systems. This paper proposes a failure threshold determination method based on quantitative measurement of the similarity between the operating system and the historical systems. The similarity is formulated by a weighted average function and then calculated by a convex quadratic formulation to minimizing the variance between the operating system and the historical systems. With an accurate determination of the system failure threshold in real-time, a better prediction of the residual life for the operating system is achieved. Finally, a real case study for several power-shift steering transmission systems monitored using oil spectral analysis is adopted to illustrate and numerically compare the improved performance of the proposed method.

Polityka utrzymania ruchu układów smarowanych olejem w oparciu o dane z analizy oleju

Maintenance of oil-lubricated systems plays a significant role in reducing unexpected system failures and improving machine availability. This paper deals with the oil-lubricated systems subject to gradual degradation that revealed by metal wear debris monitored using oil analysis. Oil-lubricated systems usually undertake several preventive maintenances during operation, after each maintenance, the system typical restores to an intermediate state between good-as-new state and bad-as-old state due to system aging such as cumulative wear. Furthermore, oil-lubricated systems often operate continuously in mission execution with availability constraints. However, existing literature still lacks a method to integrate the availability constraints with the system aging into the cause of optimizing the maintenance policy. To fill this gap, this paper develops a maintenance policy optimization method to determine the optimal maintenance threshold joint considering the availability constraints and the system aging. A case study of the power-shift steering transmission systems modelled by a wiener process is presented to illustrate the proposed method in practical application.

Health index extraction for power-shift steering transmission using selected oil field data

The concentration of wear debris in used lubricating oil is generally observed from spectral oil analysis. The element concentration data are one of the commonly used oil field data for degradation evaluation of power-shift steering transmission. However, in practical applications, the underlying degradation degree of the power-shift steering transmission is difficult to evaluate due to the complexity of element concentration data. To solve this problem, we propose a health index extraction methodology using a weighted average method to better characterize the underlying degradation, which leads to an accurate estimation of the residual life before the power-shift steering transmission needs to be maintained. The extracted health index not only maximizes the monotonic trend of underlying degradation but also minimizes the failure threshold variance between different power-shift steering transmissions. The method includes element concentration data modification, data selection, and data fusion steps that result in a reasonable power-shift steering transmission degradation model. Finally, a case study is provided to illustrate the proposed method. The results show that the extracted health index outperforms each selected element concentration data.

Weighted Evidential Fusion Method for Fault Diagnosis of Mechanical Transmission Based on Oil Analysis Data

Condition monitoring (CM) and fault diagnosis are critical for the stable and reliable operation of mechanical transmissions. Mechanical transmission wear, which leads to changes in the physicochemical properties of the lubrication oil and thus severe wear, is a slow degradation process that can be monitored by oil analysis, but the actual degradation degree is difficult to evaluate. To solve this problem, we propose a new weighted evidential data fusion method to better characterize the degradation degree of the mechanical transmission through the fusion of multiple CM datasets from oil analysis. This method includes weight allocation and data fusion steps that lead to a more accurate data-based fault diagnostic result for CM. First, the weight of each evidence is modeled with a weighted average function by measuring the relative scale of the permutation entropy from each CM dataset. Then, the multiple CM datasets are fused by the Dempster combination rule. Compared with other evidential data fusion methods, the proposed method using the new weight allocation function seems more reasonable. The rationality and superiority of the proposed method were evaluated through a case study involving an oilbased CM dataset from a power-shift steering transmission.

A New Life Expectancy Assessment Method for Complex Systems With Multi-Characteristics: Case Study on Power-Shift Steering Transmission Control System

Life is an important monitoring index for prognostic and health management systems. This paper proposes a new life expectancy assessment method for high-value complex systems with multi-characteristics based on goal-oriented (GO) method. First, the new life expectancy assessment method is expounded in detail, and its process is formulated. Then, the control system of power-shift steering transmission for a heavy vehicle, which is a typical mechatronics control system with multi-characteristics, such as multi-state, multi-function, and correlations, is taken as an example to evaluate its life expectancy by this paper’s method. In order to verify the advantages, feasibility, and rationality of the new life expectancy assessment method, the results are compared with the results by Monte Carlo method. All in all, this life expectancy assessment method not only improves the theory of GO method, so that GO method is applied to evaluate the life expectancy of complex systems with multi-characteristics first, but also provides a new approach for life expectancy assessment of complex systems, which can take into consideration various system characteristics and only use unit life data, so that it is low evaluation cost, higher estimating efficiency and accuracy, and a more stable assessment result.

A New Availability Assessment Method for Complex Control Systems With Multi-Characteristics

This paper proposes a new availability assessment method for complex control systems with multi-characteristics based on the goal-oriented (GO) method to evaluate the lower confidence limit of its system availability. First, the GO method for complex control systems with multi-characteristics is illustrated in terms of expounding GO operators and proposing a new exact algorithm with shared signals. Then, the new availability assessment method is expounded in detail, and its process is formulated. Finally, the new method is used to evaluate the lower confidence limit of the system stability of the electrohydraulic control system of a power-shift steering transmission as an example. To verify its advantages and rationality, the availability assessment results and evaluation efficiency are compared with those obtained by the regular Monte Carlo method and the regular exact GO algorithm with shared signals. Furthermore, the coverage rate of the lower confidence limit of the system availability obtained by the new method is compared with the nominal significance level. Overall, this availability assessment method not only improves the theory of the GO method and widens its application but also provides a new approach for the availability assessment of complex control systems that reduces costs and improves the estimation efficiency and accuracy.

Remaining useful life prediction for power-shift steering transmission based on fusion of multiple oil spectra

Remaining useful life prediction is a critical issue to fault diagnosis and health management of power-shift steering transmission. Power-shift steering transmission wear, which leads to the increase of wear particles and severe wear afterwards, is a slow degradation process, which can be monitored by oil spectral analysis, but the actual degree of the power-shift steering transmission degradation is often difficult to evaluate. The main purpose of this article is to provide a more accurate remaining useful life prediction methodology for power-shift steering transmission compared to relying solely on an individual spectral oil data. Our methodology includes multiple degradation data fusion, degradation index construction, degradation modelling and remaining useful life estimation procedures. First, the robust kernel principal component analysis is used to reduce the data dimension, and the state space model is utilized to construct the wear degradation index. Then, the Wiener process–based degradation model is established based on the constructed degradation index, and the explicit formulas for several important quantities for remaining useful life estimation such as the probability density function and cumulative distribution function are derived. Finally, a case study is presented to demonstrate the applicability of the proposed methodology. The results show that the proposed remaining useful life prediction methodology can objectively describe the power-shift steering transmission degradation law, and the predicted remaining useful life has been extended as 65 Mh (38.2%) compared with specified maintenance interval. This will reduce the maintenance times of power-shift steering transmission life cycle and finally save the maintenance costs.

Oil-based maintenance interval optimization for power-shift steering transmission

The concentration of micron-size particles in used oil is generally obtained by atomic emission spectrometry. These accurate results can be considered as the most important index for real-time reliability evaluation including failure prediction and residual life assessment of power-shift steering transmission in tracked vehicles. Stochastic process and especially Wiener process can be applied in processing the oil spectral data. In this article, 50 used oil samples in total were collected and analyzed in sequence which covered 250 motor hours. The eigenvalue and mean value of elemental concentration in those samples were also revealed by linear regression analysis. Then, the increasing trends and the first hitting times for indicating elements were solved by simulating stochastic differential equations, which were based on the positive drift Wiener process. Comparing to the existing conditional maintenance time, the first hitting time increased about 27 motor hours more (13.7%). The results show that the ...

Reliability Optimization Allocation Method for Multifunction Systems With Multistate Units Based on Goal-Oriented Methodology

This paper proposes a new reliability optimization allocation for multifunction systems with multistate units based on goal-oriented (GO) methodology. First, this optimization allocation method is expounded in terms of establishing GO model, establishing reliability optimization allocation model, and solving algorithm. Then its process is formulated. Finally, the new method is applied in reliability optimization allocation of power-shift steering transmission (PSST), whose goal is to minimize the system cost. The results analysis shows that the system costs for different operation times turn to a relatively stable value, and the allocated reliability indices of unit are satisfied with engineering requirements. All in all, this new optimization allocation method can not only obtain the reasonable allocation results quickly and effectively, but it also can overcome the disadvantages of existing reliability optimization allocation methods for complex multifunction systems efficiently. In addition, the analysis process shows that the reliability optimization allocation method based on GO method can provide a new approach for the reliability optimization allocation of multifunction systems with multistate units.

Reliability Analysis of Repairable System With Multiple-Input and Multi-Function Component Based on Goal-Oriented Methodology

This paper proposes a new goal-oriented (GO) method for reliability analysis of repairable systems with multiple-input and multi-function component (MIMFC). First, a new GO operator combination, which is composed of a new function GO operator and a new auxiliary GO operator, is created to represent MIMFC. The new function GO operator named as Type 22 operator is created to represent MIMFC itself, and the auxiliary GO operator named as Type 15B operator is created to represent multi-condition control signals of MIMFC. Then, GO operation formulas of the new GO operator combination are deduced based on logical relationships among inputs, outputs, and the component itself. The reliability analysis process of the new GO method is formulated. Furthermore, this new GO method is applied for the first time in steady availability analysis and qualitative analysis of the fan drive system of a power-shift steering transmission. Finally, the results obtained by the new GO method are compared with the results of fault tree analysis (FTA) and Monte Carlo simulation (MCS), and the comparison results show that this new GO method is reasonable and advantageous in reliability analysis of repairable systems with MIMFC. Moreover, the analysis process shows that it is more advantageous in the aspect of building system models and conducting reliability analysis. Overall, this paper not only improves the basic theory of the GO method and expands the application of the GO method, but it also provides a new approach for reliability analysis of repairable systems with MIMFC.

A new reliability analysis method for vehicle systems based on goal-oriented methodology

This paper presents a new approach for the reliability analysis of vehicle systems by considering typical characteristics based on goal-oriented methodology. First, solutions are proposed for vehicle systems with multiple fault modes, a standby structure at any position, a multiple-input closed-loop feedback link, multiple functions, and multiple conditions for the goal-oriented method. Then, a two-level goal-oriented model and the new rules of goal-oriented operation for such vehicle systems are proposed. Furthermore, the quantitative method and the qualitative method are improved. In addition, the analysis process for these vehicle systems based on the new goal-oriented method is formulated. Finally, this new goal-oriented methodology is applied in the dynamic availability analysis and qualitative analysis of the power-shift steering transmission for a heavy military vehicle. In order to verify the feasibility, the advantages, and the correctness of the new goal-oriented methodology, the results are compared with those from fault tree analysis and Monte Carlo simulations. In general, this study not only improves the theory of the goal-oriented method and widens the application of the goal-oriented method but also provides a new reliability analysis method for such vehicle systems. In addition, the analysis process of the new goal-oriented method shows that the goal-oriented method has advantages in system reliability modeling and system reliability analysis for vehicle systems.

Degradation modeling and experiment of electro-hydraulic shift valve in contamination circumstances

In this article, a degradation assessment model has been proposed for electro-hydraulic shift valve in power-shift steering transmission. Our work is motivated by the failure mechanism of abrasive wear with a mathematic model. Abrasive wear will consecutively enlarge the clearance between the friction pairs. It is an overwhelming wear mechanism in the degradation of shift valve within serious contaminated fluid. Herein, a mathematic model is proposed by considering particle morphology and abrasion theory. Such model has been verified for its applicability and accuracy through comparison between the theoretical and experimental results.

Failure Prediction and Wear State Evaluation of Power Shift Steering Transmission

Within the vehicle transmission, the friction surfaces of mechanical parts were consecutively worn-out and ultimately up to the degradation failures. For assessing the wear progress effectively, wear particles should be generally monitored by measuring the element concentration through Atomic emission (AE) spectroscopy. Herein, the spectral data sampled from life-cycle test has been processed by both the Principal Component Analysis (PCA) and further Kernel Principal Component Analysis (KPCA). Results show that KPCA acts more effectively in variable-dimensions reduction due to fewer principle components and higher cumulative contributing rate. To detect the threshold point at where the wear-stage upgraded, the Fuzzy C-means clustering algorithm was applied to process the eigenvalues of principle components. Furthermore, it is demonstrated that the principle components relate to the worn-out state of friction pairs or transmission parts. In general, the introduction of KPCA has contributed to assess the wear-stage at where the machine situates and the accurate worn-out state of various transmission parts.

Denoising of Mechanical Vibration Signals Using Quantum-Inspired Adaptive Wavelet Shrinkage

The potential application of a quantum-inspired adaptive wavelet shrinkage (QAWS) technique to mechanical vibration signals with a focus on noise reduction is studied in this paper. This quantum-inspired shrinkage algorithm combines three elements: an adaptive non-Gaussian statistical model of dual-tree complex wavelet transform (DTCWT) coefficients proposed to improve practicability of prior information, the quantum superposition introduced to describe the interscale dependencies of DTCWT coefficients, and the quantum-inspired probability of noise defined to shrink wavelet coefficients in a Bayesian framework. By combining all these elements, this signal processing scheme incorporating the DTCWT with quantum theory can both reduce noise and preserve signal details. A practical vibration signal measured from a power-shift steering transmission is utilized to evaluate the denoising ability of QAWS. Application results demonstrate the effectiveness of the proposed method. Moreover, it achieves better performance than hard and soft thresholding.