Comprehensive Performance Evaluation of an Unmanned Excavator Based on Signal Stability Extraction

Abstract

The comprehensive performance of unmanned excavators is crucial for the development and optimization of the field of construction machinery. To effectively improve the unmanned excavator to meet the needs of the market, it is imperative to quantify the evaluation method of the comprehensive performance of unmanned excavators. In this study, an evaluation method combining a fuzzy analytic hierarchy process and multivariate image area analysis method is proposed. Firstly, based on the feature extraction of the signal stability of the unmanned excavators, fifteen evaluation indexes were proposed. Then, the case study is used to obtain the scores corresponding to these indexes. The fuzzy analytic hierarchy process is applied to determine the relative weight of the selected evaluation criteria, in which the uncertain and imprecise judgments of decision makers are converted into fuzzy numbers. At the same time, the braking performance of the three types of unmanned excavators was comprehensively evaluated and ranked using the multivariate image area analysis method as an empirical example. Finally, a weight analysis is performed to check the robustness of the ranking results. The results show that the proposed method is effective and feasible. It provides a reference for the performance improvement and efficiency optimization of unmanned excavators.

Keywords

• unmanned excavator
• radar chart
• fuzzy analytic hierarchy process (FAHP)
• comprehensive performance evaluation