Abstract
Safety is an important indicator to the design of agricultural machinery products. In order to grasp the risk source of agricultural machinery accidents accurately, explore the causes and laws of agricultural machinery accidents, and prevent the occurrence of various accidents in the process of agricultural machinery products effectively. This study constructs a fuzzy fault tree model by combining the fault tree analysis method with the triangular fuzzy number, and analyzes the factors which cause agricultural machinery accidents. The results are as follows: 1) Through fault tree analysis, 23 known and potential causes of agricultural machinery accidents were deduced, and 57 minimum cut sets and 3 minimum path sets were solved; 2) The probabilities of 23 basic events were fuzzed by triangular fuzzy number theory, and the fuzzy probability value of each basic event was obtained; 3) Sorting fuzzy importance of 23 basic events has clarified the degree of influence of each basic event on the top event. Factors such as, Machine without safety protection device (X1), Personnel not wearing safety protective equipment (X2), Long Working Hours (X16), Unreasonable control device (X15), Speeding and overloading (X7), are ranked top among the 23 factors. The analysis result shows that these factors have a great impact on the occurrence of agricultural machinery accidents which should be given priority in the formulation of preventative measurements to agricultural machinery accidents.
Original language | English |
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Pages (from-to) | 871-881 |
Number of pages | 11 |
Journal | Journal of Computational Methods in Sciences and Engineering |
Volume | 22 |
Issue number | 3 |
DOIs | |
Publication status | Published - 2022 |
Keywords
- Agricultural machinery accident
- fault tree analysis method
- fuzzy fault tree
- fuzzy importance
- triangular fuzzy number
ASJC Scopus subject areas
- General Engineering
- Computer Science Applications
- Computational Mathematics