PSI - Issue 38

Frédéric Kihm et al. / Procedia Structural Integrity 38 (2022) 12–29 Kihm, Miu, Bonato / Structural Integrity Procedia 00 (2021) 000 – 000

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4. Case Study 2 – Suspension subsystem 4.1. Introduction

A suspension subsystem for the rear wheels of a passenger car was instrumented and measured data was collected over various test tracks. The aim is to build a predictive model that estimates the local strain-derived damage from a combination of available signals. 4.2. Instrumentation Strain measurements were made in various points of the rear suspension subsystem. The strain measurement of interest was made on the shock absorber turret. Accelerations were collected at two different locations on the chassis, close to the suspension subsystem. The vertical displacement of the wheel hub and the force in the steering rod were measured. The inclination of the rear axle was given as a calculated channel. In addition, some vehicle parameters, obtained from the CAN bus of the vehicle were also given. Those were the steering wheel angle and the yaw rate. 4.3. Data Processing The data processing is different for each signal, it is therefore made on a per-signal basis. The acceleration signals are integrated twice with drift being removed each time (the highpass filters) in order to obtain a reliable estimate of displacement. Each signal is rainflow-counted and relative damage is calculated periodically on 30-second windows. The damage data from all these channels is then merged back together and saved to a single output for further processing in another downstream component. The same fatigue slope of -3 was used in this example. 4.4. Correlation We calculate the correlation of the output (strain damage) to all of the inputs. The results are given in Table 7:

Table 7. Correlation coefficients between the output and the inputs.

Correlation coefficient with StrainDamage

Rear_axle_inclination 0.71 Accel_Lat_Chassis 0.49 Accel_Long_Chassis 0.47 SteeringWheel_Angle 0.11 DispZ_AftRight 0.10 Yaw_Rate -0.08 SteeringRod_Force 0.05

Damage from…

We can see that the strain damage correlates relatively well with three signals (damage from Rear_axle_inclination, from Accel_Lat_Chassis and from Accel_Long_Chassis). We use this preliminary finding to start the investigation of linear regression models between strain damage and these highly correlated signals.

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