Paper
23 January 2017 Study on test and preparation of load spectrum of hydraulic excavator
Hong Zhang, Guodi Feng, Haijun Zhang, Xiaofeng Wang, Yingzhi Zhang
Author Affiliations +
Proceedings Volume 10322, Seventh International Conference on Electronics and Information Engineering; 103223J (2017) https://doi.org/10.1117/12.2266910
Event: Seventh International Conference on Electronics and Information Engineering, 2016, Nanjing, China
Abstract
Due to harsh working conditions, the components of hydraulic excavator are subject to large amount of alternating load and random load during the operation and they are seriously damaged. The test of load signal and preparation of load spectrum for the hydraulic excavator are studied in this paper. In the first place, pretreatment of filtering and noise reduction for load signal is conducted based on experimental test on site and experimental working condition analysis. After the load signal is processed in sections, distribution fitting is performed for information like mean amplitude after rain flow counting with the approach of probability statistics to get the probability distribution function for mean value and amplitude value. Finally the two dimensional load spectrum for mean amplitude is obtained and program spectrum loading solution of fatigue experiment is given. The study of load signal test and load spectrum preparation method for hydraulic excavator conducted in this paper is of great significance for clarification of load distribution of excavator and further reliability test of excavator.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hong Zhang, Guodi Feng, Haijun Zhang, Xiaofeng Wang, and Yingzhi Zhang "Study on test and preparation of load spectrum of hydraulic excavator", Proc. SPIE 10322, Seventh International Conference on Electronics and Information Engineering, 103223J (23 January 2017); https://doi.org/10.1117/12.2266910
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KEYWORDS
Signal processing

Electronic filtering

Statistical analysis

Reliability

Data acquisition

Denoising

Interference (communication)

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