Damage evaluation of driving events for agricultural tractors
| Autor: | Michele Mattetti, Eugenio Sereni, Giovanni Molari |
|---|---|
| Přispěvatelé: | Mattetti, M., Molari, G, Sereni, E. |
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Signal processing
Engineering Horticulture 01 natural sciences Automotive engineering Durability Data logger Correlation analysi Driving event Agricultural machinery Event (computing) business.industry 010401 analytical chemistry Forestry Computer Science Applications1707 Computer Vision and Pattern Recognition 04 agricultural and veterinary sciences Automation 0104 chemical sciences Computer Science Applications Axle Headland (agriculture) Service life 040103 agronomy & agriculture 0401 agriculture forestry and fisheries Health monitoring system Animal Science and Zoology business Agronomy and Crop Science |
| Popis: | Damage data, from load histories collected under the same conditions, are highly scattered.Large oscillations of axle housing loads are mainly caused by drivers' or ground inputs.Most of the damage of vertical forces is developed at the headland turn on field.The signal processing methodology should be considered as a first step toward the development of a health monitoring system. Durability is the capacity of a machine to maintain the functionality during its intended service life, under the recommended conditions and the prescribed levels of maintenance. A durable machine has to be designed with a sufficient fatigue resistance that can be accomplished only if its service loads are well known. Tractors are characterized by few large load oscillations and these are of most interest in the evaluation of the fatigue damage accumulated by the structural elements. These oscillations are caused by driving events, defined as any major change in vehicle speed, attitude or operating condition. In this paper, a signal processing methodology to automatically identify the highly damage events for axle housings is described. An agricultural tractor was equipped with four Wheel Force Transducers (WFTs) and a CAN-Bus based data logger in order to acquire axle housing loads and the drivers operation signals. Signals were acquired for three different applications as ploughing, subsoiling and implement transportation. The loading events were identified through the analysis of the pairwise Time-Varying Correlation Coefficient (TVCC) between the drivers operation signals and the WFT signals. A driving event was classified as a pattern of TVCCs and for each, the Time-Varying Pseudo-Damage (TVPD) was calculated. Using this methodology, it has been found that the most damaging event for the axle housings occur during the headland turn due to full load accelerations and vertical load transfer between front and rear axles. For these reasons in-field operations were more damaging than off-road transportation. The outlined signal processing methodology should be considered as a first step into the development of a health monitoring methodology for tractors. |
| Databáze: | OpenAIRE |
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