A need exists within the industry to prevent the overturn of construction, agricultural, automotive and industrial machinery at a cost which makes it affordable to all types of vehicles.
The work was consist on conveniently combining conventional and micromachined strain gauge sensors, inclinometers with vehicle physical and operating conditions in order to define a stability index to inform the operators when working in potentially hazardous conditions, as well as on improving their operational efficiency.
Multi-sensor inputs were processed aided by neural network based software for autocalibration and being able to learn from changes in operating conditions. Industrial validation for different types of vehicles taken place, using products from within the consortium of members in order to confirm the appropriate use of the developed technology. These vehicles were conducted to investigate model validity. Further applications were analysed.
A resonant beam sensor was developed, as an alternative to strain gauges. The physical working principle is based on a shift in resonance frequency of a vibrating beam sensitive to strain. Similar to a (guitar) string, the resonance frequency of a beam stromgly depends on the applied axial stress.