Piezo impedance-based monitoring of loosening of bolts: Experimental and numerical study

The suspension strut mount plays a crucial role in any vehicular suspension system, where it acts as a connector (bolted) to the vehicular body and suspension strut. The mount’s purpose is to cushion the Vehicular impacts and reduce the jarring effect, noise, and vibration caused due to vehicle movement over the undulated roads. The self-loosening of bolts results because of the up and down impact of the spring cause the jounce bouncer to push and pull action at the mount interface, cause vibrations transmitted to the vehicle camber. Self-loosening leads to damage of mount followed by clunking noises, noisy steering, tire misalignment, and can cause discomfort to the passenger. Therefore, condition monitoring and assessment of an upper strut mount is necessary for vehicles. This paper studies the feasibility of the piezo Impedance-based Structural health monitoring (SHM) technique to monitor the self-loosening bolts in the upper strut mount of the suspension system (MacPherson strut suspension) of passenger car. The piezo coupled signatures were obtained experimentally by loosening all the three bolts (connected to strut bearing) through control torques through a digital torque wrench. All the experimental signatures were acquired with a single PZT patch bonded to the surface of the upper strut mount for loosening bolts with pre-tight loss. Progressive damage scenarios are simulated along with preload loss of either single bolt or all three bolts, respectively. Three different statistical damage indices were evaluated for damage quantification raised due to bolt loosening. A 3D numerical modeling of strut mount is done using ANSYS WORKBENCH, and piezo impedance signatures were acquired (hence converted to admittance) for validating the experimental signatures. In an overall, this study provides an insight into the loss of structural integrity due to the self-loosening of suspension bolts, which can be threatful to vehicular integrity.

Design and Analysis of Suspension Strut in Automobile Vehicles

This research paper discusses about the design and analysis of suspension strut used in automotive industries. The main objective of this research is to study the suspension strut by modelling using solid works and then analysis have been performed using ANSYS by considering structural steel, carbon fiber and E-Glass material. Based on the results obtained from the analysis, comparison have been made for above materials to reduce the weight of the suspension strut to improve the life of the model. From the analysis results it can be concluded that it is possible to reduce the weight of suspension strut using composite materials. From the above study it can be concluded that glass fiber has performed well as compared to other materials which in turn increases the life of the suspension strut.

Quantification of Uncertainty in the Mathematical Modelling of a Multivariable Suspension Strut Using Bayesian Interval Hypothesis-Based Approach

Mathematical models of a suspension strut such as an aircraft landing gear are utilized by engineers in order to predict its dynamic response under different boundary conditions. The prediction of the dynamic response, for example the external loads, the stress and the strength as well as the maximum compression in the spring-damper component aids engineers in early decision making to ensure its structural reliability under various operational conditions. However, the prediction of the dynamic response is influenced by model uncertainty. As far as the model uncertainty is concerned, the prediction of the dynamic behavior via different mathematical models depends upon various factors such as the model's complexity in terms of the degrees of freedom, material and geometrical assumptions, their boundary conditions and the governing functional relations between the model input and output parameters. The latter can be linear or nonlinear, axiomatic or empiric, time variant or time-invariant. Hence, the uncertainty that arises in the prediction of the dynamic response of the resulting different mathematical models needs to be quantified with suitable validation metrics, especially when the system is under structural risk and failure assessment. In this contribution, the authors utilize the Bayesian interval hypothesis-based method to quantify the uncertainty in the mathematical models of the suspension strut.