The need to generate realistic strain signals at an automotive coil spring for durability simulation leading to fatigue life assessment

Putra, T. E.; Abdullah, Shahrum; Schramm, Dieter; Nuawi, Mohd. Zaki; Brückmann, Tobias

doi:10.1016/j.ymssp.2017.03.014

Cited by 43 publications

(24 citation statements)

References 40 publications

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“…Hence, the effect of the extraction at one EGV needs to be taken into consideration. This helps in certifying that the fragments that were retained fulfilled the FDE criterion of maintaining 90 % fatigue damage [6,7]. Thus, the retained fragments were reattached to yield a single strain signal for validating if the extraction process was performed satisfactorily.…”

Section: Modified Strain Signalsmentioning

confidence: 98%

“…In this study, the research acquired the strain signals after placing a strain gage in a critical location in the coil spring of the car and then driving the vehicle on the public road surfaces. The finite element analysis [6,7] was used for detecting the high-stress area in the component and the strain gage was installed in that area. The SAE5160 carbon steel was selected as the material for the simulation, which is generally applied in many automotive industries for the fabrication of the coil springs [8].…”

Section: Strain Signal Measurementmentioning

confidence: 99%

“…Another DWT-based FDE had also been created by Abdullah et al [5]. Recently, Putra et al [6,7] developed a FDE algorithm based on the continuous wavelet transform (CWT) giving a significant result in terms of saving fatigue testing. The question then arose as to how accurate the algorithms are in shortening a strain signal.…”

Section: Introductionmentioning

confidence: 99%

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Fatigue Feature Clustering of Modified Automotive Strain Signals for Saving Testing Time

Husaini¹,

Putra²,

Ali³

2018

Int. J. Automot. Mech. Eng.

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This paper discusses on the clustering of damaging fragments from a fatigue data editing leading to fatigue damage using the fuzzy C-means. In this work, strain signals were measured from an automotive coil spring which involved vehicle movements on three types of road surfaces at different speeds. Next, the extractions of higher amplitude cycle utilising the wavelet transform were conducted. From the results, it was obtained that the transformation was able to shorten the strain signal time up to 81.5 % removing 81.5 % of lower amplitude cycles, which these cycles theoretically contribute to minimum fatigue damage. Therefore, retaining of fatigue damage by more than 90.4 % was obtained. Furthermore, the resulted fragments from the extraction processes had been clustered utilising the fuzzy C-means, providing a significant coefficient of determination, reaching 0.9036. The testing time was successfully decreased up to 81.4 % using the edited strain signals. In conclusion, the technique could be successfully used to shorten a strain signal without changing the main history.

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Section: Modified Strain Signalsmentioning

confidence: 98%

Section: Strain Signal Measurementmentioning

confidence: 99%

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Fatigue Feature Clustering of Modified Automotive Strain Signals for Saving Testing Time

Husaini¹,

Putra²,

Ali³

2018

Int. J. Automot. Mech. Eng.

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“…Finally, a simulated strain signal generated by the acceleration is offered in the gain. [29][30]. The strain signals were changed into stress with the aid of the Ramberg-Osgood equation [51] outlined below:…”

Section: Sprung Massmentioning

confidence: 99%

“…60-second strain data with 5 % noise were measured by He et al [28] in order to acquire the strain responses, especially at critical spots with regards to the empirical mode decomposition. Putra et al [29][30] also collected strain signals for validating FDE based on experimental. Zhang et al [31] used strain signals to identify the golf swing.…”

Section: Introductionmentioning

confidence: 99%

A Novel Way to Overcome Problems Arising in Strain Signal Measurements Leading to a Fatigue Failure Characterisation

Putra

Abdullah

Schramm

2020

IJAME

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The aim of this study is to identify the issues that arise when measuring a strain signal in order to characterise fatigue failure. In traditional methods, acquisition of a strain signal is constrained due to the presence of errors, time-consuming process and associated high cost. In this study, a new method for generating strain signals based on computer simulation was proposed. A strain gauge was positioned near the citical area pertaining to an automotive coil spring driven on road surfaces in order to measure strain signals. The strain signals were utilised for the inputs in the simulation. For validation purposes, the actual and simulated strain signals were examined by performing fatigue tests. The actual and simulated urban strain signals, respectively, required 412 and 415 reversals of blocks. For the rural road, the fatigue life was 137 and 139 reversals of blocks, respectively, for the actual and simulated strain signals. These indicated that simulated strain signals were accurately generated, providing a minimum fatigue life deviation, which was lower than 1.5 %. By developing the strain signals of a component through simulation, its integrity and fatigue failure can adequately be determined, thereby, saving the cost associated with operation and maintenance. Thus, the simulation is expected to assist the automotive industries involved with strain signal acquisition.

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Computing low-frequency vibration energy with Hölder singularities as durability predictive criterion of random road excitation

et al. 2021

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The need to generate realistic strain signals at an automotive coil spring for durability simulation leading to fatigue life assessment

Cited by 43 publications

References 40 publications

Fatigue Feature Clustering of Modified Automotive Strain Signals for Saving Testing Time

Fatigue Feature Clustering of Modified Automotive Strain Signals for Saving Testing Time

A Novel Way to Overcome Problems Arising in Strain Signal Measurements Leading to a Fatigue Failure Characterisation

Computing low-frequency vibration energy with Hölder singularities as durability predictive criterion of random road excitation

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