Reliability-based fatigue life of vehicle spring under random loading

2019 ◽  
Vol 10 (5) ◽  
pp. 737-748 ◽  
Author(s):  
Reza Manouchehry Nya ◽  
Shahrum Abdullah ◽  
Salvinder Singh Karam Singh
Keyword(s):  
Fatigue Life ◽  
Life Prediction ◽  
Reliability Assessment ◽  
Fatigue Life Prediction ◽  
Coil Spring ◽  
Fatigue Reliability ◽  
Random Loading ◽  
Content Type ◽  
Road Surfaces ◽  
Road Data

Purpose The purpose of this paper is to analyse fatigue-life prediction based on a reliability assessment for coil springs of vehicle suspension systems using different road excitations under random loading. Design/methodology/approach In this study, a reliability assessment was conducted to predict the fatigue life of an automobile coil spring during different road data surfaces. Campus, urban and highway road surfaces were considered to capture fatigue load strain histories using a data acquisition system. Random loadings are applied on top of a coil spring where coil is fixed from down. Fatigue reliability was established as a system of correlated events during the service life to predict the probability of fatigue life using Coffin–Manson, Morrow and Smith–Watson–Topper (SWT) models. Findings Fatigue-life prediction based on a reliability assessment revealed that the Morrow model can predict a safe region of a life data point for the three road surfaces. Highway road data indicated the highest rate of reliability at 0.8 for approximately 1.69 × 105 cycles for the SWT model. Originality/value Reliability assessment of the fatigue life of vehicle coil springs is vital for safe operation. The reliability analysis of a coil spring under random loading excitations can be used for fatigue-life prediction.

Fatigue life-based reliability assessment of a heavy vehicle leaf spring

2019 ◽  
Vol 10 (5) ◽  
pp. 726-736
Author(s):  
Lennie Abdullah ◽  
Salvinder Singh Karam Singh ◽  
Abdul Hadi Azman ◽  
Shahrum Abdullah ◽  
Ahmad Kamal Ariffin Mohd Ihsan ◽  
...  
Keyword(s):  
Fatigue Life ◽  
Life Prediction ◽  
Reliability Assessment ◽  
Gumbel Distribution ◽  
High Amplitude ◽  
Fatigue Life Prediction ◽  
Leaf Spring ◽  
Heavy Vehicle ◽  
Random Loading ◽  
Content Type

Purpose This study aims to determine the reliability assessment based on the predicted fatigue life of leaf spring under random strain loading. Design/methodology/approach Random loading data were extracted from three various road conditions at 200 Hz using a strain gauge for a duration of 100 s. The fatigue life was predicted using strain-life approaches of Coffin–Manson, Morrow and Smith–Watson–Topper (SWT) models. Findings The leaf spring had the highest fatigue life of 1,544 cycle/block under highway data compared uphill (1,299 cycle/block) and downhill (1,008 cycle/block) data. Besides that, the statistical properties of kurtosis showed that uphill data were the highest at 3.81 resulted in the presence of high amplitude in the strain loading data. For fatigue life-based reliability assessment, the SWT model provided a narrower shape compared to the Coffin–Manson and Morrow models using the Gumbel distribution. The SWT model had the lowest mean cycle to failure of 1,250 cycle/block followed by Morrow model (1,317 cycle/block) and the Coffin–Manson model (1,429 cycle/block). The SWT model considers the mean stress effects by interpreting the strain energy density that will influence the reliability assessment. Research limitations/implications The reliability assessment based on fatigue life prediction is conducted using the Gumbel distribution to investigate the behaviour of fatigue random loading, where most previous studies had concentrated on a Weibull distribution on random data. Originality/value Thus, this study proposes that the Gumbel distribution is suitable for analysing the reliability of random loading data in assessing with the fatigue life prediction of a heavy vehicle leaf spring.

Fatigue Reliability Analysis Including Super Long Life Regime

2010 ◽  
Vol 118-120 ◽  
pp. 17-26 ◽  
Author(s):  
Yong Xiang Zhao
Keyword(s):  
Fatigue Life ◽  
Reliability Analysis ◽  
Life Prediction ◽  
Reliability Assessment ◽  
Cyclic Stress ◽  
Fatigue Life Prediction ◽  
Fatigue Reliability ◽  
Stress Strain ◽  
Structural Fatigue ◽  
Long Life

For an engineering structure with an actual fatigue life over that corresponding to a so-called fatigue limit, appropriate reliability assessment and fatigue life prediction are essential for developing the structure and sustaining its high quality in service. Basic clues are explored. A competition fatigue initial mechanism is shown to provide a requirement of material primary quality management. Affordable deduced material and structural probabilistic S-N curves are presented by fitting into material mid-and-long life S-N data and fatigue limits and, then, comparing to structural fatigue limits. Random cyclic stress-strain relations are depicted for constructing random stressing history of structures. Reliability assessment and fatigue life prediction are established to synthetically consider the interference of applied stresses deduced from the random cyclic stress-strain relations and capacity strengths derived from the structural S-N relations with an expected life. Affordable and appropriate method has been then developed to realize the reliability assessment and fatigue life prediction including the super long life regime. Availability of the present method has been indicated through a reliability analysis to the velocity related reliabilities and fatigue lives of a railway axle.

Durability analysis using Markov chain modeling under random loading for automobile crankshaft

2019 ◽  
Vol 10 (4) ◽  
pp. 454-468 ◽  
Author(s):  
Salvinder Singh ◽  
Shahrum Abdullah
Keyword(s):  
Life Cycle Assessment ◽  
Life Cycle ◽  
Fatigue Life ◽  
Automotive Industry ◽  
Life Prediction ◽  
Fatigue Life Prediction ◽  
Fatigue Reliability ◽  
Load History ◽  
Content Type ◽  
Durability Analysis

Purpose The purpose of this paper is to present the durability analysis in predicting the reliability life cycle for an automobile crankshaft under random stress load using the stochastic process. Due to the limitations associated with the actual loading history obtained from the experimental analysis or due to the sensitivity of the strain gauge, the fatigue reliability life cycle assessment has lower accuracy and efficiency for fatigue life prediction. Design/methodology/approach The proposed Markov process embeds the actual maximum and minimum stresses by a continuous updating process for stress load history data. This is to reduce the large credible intervals and missing loading points used for fatigue life prediction. With the reduction and missing loading intervals, the accuracy of fatigue life prediction for the crankshaft was validated using the statistical correlation properties. Findings It was observed that fatigue reliability corresponded well by reporting the accuracy of 95–98 per cent with a mean squared error of 1.5–3 per cent for durability and mean cycle to failure. Hence, the proposed fatigue reliability assessment provides an accurate, efficient, fast and cost-effective durability analysis in contrast to costly and lengthy experimental techniques. Research limitations/implications An important implication of this study is durability-based life cycle assessment by developing the reliability and hazard rate index under random stress loading using the stochastic technique in modeling for improving the sensitivity of the strain gauge. Practical implications The durability analysis is one of the fundamental attributes for the safe operation of any component, especially in the automotive industry. Focusing on safety, structural health monitoring aims at the quantification of the probability of failure under mixed mode loading. In practice, diverse types of protective barriers are placed as safeguards from the hazard posed by the system operation. Social implications Durability analysis has the ability to deal with the longevity and dependability of parts, products and systems in any industry. More poignantly, it is about controlling risk whereby engineering incorporates a wide variety of analytical techniques designed to help engineers understand the failure modes and patterns of these parts, products and systems. This would enable the automotive industry to improve design and increase the life cycle with the durability assessment field focussing on product reliability and sustainability assurance. Originality/value The accuracy of the simulated fatigue life was statistically correlated with a 95 per cent boundary condition towards the actual fatigue through the validation process using finite element analysis. Furthermore, the embedded Markov process has high accuracy in generating synthetic load history for the fatigue life cycle assessment. More importantly, the fatigue reliability life cycle assessment can be performed with high accuracy and efficiency in assessing the integrity of the component regarding structural integrity.

Application of a Multiaxial Fatigue Criterion for the Evaluation of Life of Gears of Complex Geometry

2003 ◽  
Author(s):  
Leonardo Borgianni ◽  
Paola Forte ◽  
Luigi Marchi
Keyword(s):  
Fatigue Life ◽  
Stress State ◽  
Life Prediction ◽  
Complex Geometry ◽  
Biaxial Stress ◽  
Fatigue Life Prediction ◽  
Random Loading ◽  
Complex Load ◽  
Biaxial Stress State ◽  
Principal Axes

Gears can show significant biaxial stress state at tooth root fillet, due to the way they are loaded and their particular geometry. This biaxial stress state can show a significant variability in principal axes during meshing. Moreover loads may have non predictable components that can be evaluated with the aid of recorded data from complex spectra. In these conditions, commonly adopted approaches for fatigue evaluation may be unsuitable for a reliable fatigue life prediction. This work is aimed at discussing a computer implementation of a fatigue life prediction method suitable for multiaxial stress states and constant amplitude or random loading. For random loading a counting procedure to extract cycles from complex load histories is discussed. This method, proposed by Vidal et al., is based on the r.m.s. value of a damage indicator over all the planes through the point where the fatigue life calculation is made. Miner’s rule is used for the evaluation of the overall damage. The whole fatigue life of the component is evaluated in terms of the numbers of repetitions of the loading block. FEM data are used to evaluate stresses under load. The implementation was validated using test data found in the technical literature. Examples of applications to gears are finally discussed.

scholarly journals Durability Analysis for Coil Spring Suspension Based on Strain Signal Characterisation

2018 ◽  
Vol 7 (3.17) ◽  
pp. 104
Author(s):  
Chin Chuin Hao ◽  
Shahrum Abdullah ◽  
Ahmad Kamal Ariffin ◽  
Salvinder Singh Karam Singh
Keyword(s):  
Fourier Transform ◽  
Fatigue Life ◽  
Frequency Domain ◽  
Time Domain ◽  
Life Prediction ◽  
Energy Content ◽  
Fatigue Life Prediction ◽  
Coil Spring ◽  
Time Frequency ◽  
Strain Signal

This paper aims to predict the durability of an automobile coil spring by characterising the captured strain data. The load histories collected at coil spring are often presented in time domain but time domain cannot provide sufficient information for fatigue life prediction. The objective of this study was to characterise the strain signal in time domain, frequency domain and time-frequency domain for fatigue life prediction. The signal obtained in time domain was used to predict the fatigue life of the coil spring through Rainflow cycle counting technique and models of strain-life relationships. In frequency domain, fast Fourier transform revealed that the frequency components in the strain signal ranged between 0-5 Hz. The frequencies can be further categorised into two ranges: 0-0.3 Hz and 1-2 Hz. Power spectral density confirmed that the frequencies with high energy content were 0-5 Hz and the total energy content in the signal is 4.0872x103 µɛ2. Short time Fourier transform can identify the local time and frequency properties of the signal but it has a limitation in time-frequency resolutions. Wavelet transform can provide a better time-frequency resolutions and it confirmed that the transients in the time domain had frequency range of 1-2 Hz. In summary, this study revealed different possible approaches of signal processing in fatigue life assessment of automotive components as guidance for the selection of suitable approach based on the type of information needed for the analysis.  

Fatigue life prediction for automobile stabilizer bar

2019 ◽  
Vol 11 (2) ◽  
pp. 303-323
Author(s):  
Shuangshuang Li ◽  
Xintian Liu ◽  
Xiaolan Wang ◽  
Yansong Wang
Keyword(s):  
Fatigue Life ◽  
Life Prediction ◽  
Test Sample ◽  
Fatigue Life Prediction ◽  
Bench Test ◽  
Load Spectrum ◽  
Content Type ◽  
Life Model ◽  
On The Road ◽  
The Impact

Purpose During the running of automobile, the stabilizer bar is frequently subjected to the impact of complex random loads, which is prone to fatigue failure and accident. In regard to this, the purpose of this paper is to study and discuss fatigue life of automobile stabilizer bar. Design/methodology/approach Durability bench test shows that failure is located at the joint of sleeve and stabilizer bar body. Based on the collection and compilation of micro-strain load spectrum of the stabilizer bar, the strain-life model is studied considering the influence of average stress and maximum stress at failure area. Seven-grade strain-life curves of the stabilizer bar are established. According to the principle of linear damage accumulation, the relationship between fatigue life and damage is discussed, then the fatigue life of stabilizer bar is predicted. Fatigue life evaluation is carried out from three aspects: reliability analysis, static analysis and fatigue life simulation. Findings The results show that the reliability of the test sample is 99.9 percent when the confidence is 90 percent and the durability is 1,073 load spectrum cycles; the ratios of predicted and simulated life to design life are 2.77 and 2.30, respectively. Originality/value Based on the road load characteristics of automobile stabilizer bar, the method of fatigue life prediction and evaluation is discussed, which provides a basis for the design and development of automobile chassis components.

An improved fatigue life prediction model for shock absorber cylinder with surface roughness correction

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Haijie Wang ◽  
Xintian Liu ◽  
Que Wu ◽  
Xiaolan Wang ◽  
Yansong Wang
Keyword(s):  
Surface Roughness ◽  
Fatigue Life ◽  
Prediction Model ◽  
Life Prediction ◽  
Shock Absorber ◽  
Fatigue Life Prediction ◽  
Improved Method ◽  
Content Type ◽  
Lateral Forces ◽  
Life Prediction Model

Purpose The purpose of this paper is to obtain a more accurate fatigue life of structures by introducing the surface roughness into fatigue life prediction model. Design/methodology/approach Based on the fatigue life prediction model with surface roughness correction, the shock absorber cylinder is taken as an example to verify the feasibility of the improved method. Based on the load of the shock absorber cylinder during driving, fatigue experiments are performed under longitudinal and lateral forces, respectively. Then, the fatigue life predicted by the modified model is compared with that predicted by the traditional model. Findings By comparing with the test results, considering the influence of mean stress, the Manson method is more accurate in life prediction. Then, the modified Manson-Coffin and Manson method with surface roughness is more accurate in life prediction under longitudinal force and lateral forces, respectively. This verifies the feasibility of the improved method with the surface roughness. Originality/value The research on the influence of surface roughness on fatigue life can lay the technical foundation for the life prediction of products and have great significance to the quality evaluation of products.

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