Monitoring of hand-arm vibration

Abstract

This paper aims to describe the development of a statistical analysis method called the integrated kurtosis-based algorithm for a Z-notch filter (I-kaz) Vibro for monitoring hand-arm vibration (HAV) in Malaysian Army (MA) three-tonne truck steering wheels. HAV from the steering wheel was measured using a single axis piezoelectric accelerometer that was connected to a Brüel & Kjær Type 3649 vibration analyser. The raw acceleration data was integrated to obtain velocity data and reintegrated to obtain displacement data. The data was analysed using I-kaz Vibro to determine the vibration values in relation to varying speeds of the truck and to determine the degree of data scattering for three-axial raw data signals for acceleration, velocity, and displacement in the x-, y-, and z-axes, respectively. Based on the results obtained, HAV experienced by the drivers can be presented using daily vibration exposure A(8), the I-kaz Vibro coefficient (Zv ∞), and the I-kaz Vibro display. For the developed model validation, predicted and measured values of A(8) were compared and a relatively good agreement was obtained between them. The low average relative error (4:78%) for the developed equation model demonstrated that I-kaz Vibro is very effective in monitoring HAV in steering wheels.