Fault Analysis System for Agricultural Machinery Based on Big Data

Dan Li,Yi Zheng,Wei Zhao

doi:10.1109/access.2019.2928973

Dan Li, Yi Zheng + Show 1 more

Open Access

https://doi.org/10.1109/access.2019.2928973

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Abstract

With the continuous development of agricultural mechanization and information, agricultural machinery failure analysis has become an important issue. Providing effective agricultural machinery failure analysis for agricultural workers can save considerable time and cost. This paper addresses this issue by designing and producing a platform for data analysis of agricultural engineering machinery. Through the collection and analysis of agricultural engineering machinery floor data and with the help of the Internet and big data technology, physical modeling, charts, and other intuitive forms have been developed to provide information for personnel on the mechanical parts of agricultural engineering machinery, the cause of failures, and maintenance requirements. This novel agricultural engineering machinery management analysis platform currently has access to 100 million data points, with system access for capacity expansion, and provides fault detection and maintenance examples. It has already been applied in multiple farms across many of China's provinces.

Highlights

INTRODUCTIONWith the continuous development of modern information technology such as the Internet of Things, cloud computing, big data, mobile Internet, etc., the transformation and upgrading of the entire agricultural industry chain has become a new form of industrial revolution [1]
With the continuous development of modern information technology such as the Internet of Things, cloud computing, big data, mobile Internet, etc., the transformation and upgrading of the entire agricultural industry chain has become a new form of industrial revolution [1].The United States is the first country to install systems such as satellite navigation on agricultural engineering machinery
There are four input and output of the management analysis platform: the data acquisition of the sensor data collected by the data acquisition subsystem, the input of the analysis model of the data analyst in the data analysis subsystem, and the agricultural practitioner of the platform interaction subsystem

Summary

INTRODUCTION

With the continuous development of modern information technology such as the Internet of Things, cloud computing, big data, mobile Internet, etc., the transformation and upgrading of the entire agricultural industry chain has become a new form of industrial revolution [1]. The ‘‘Smart Assistant’’ supports the automation of agricultural machinery, and works with agricultural cloud applications provided by third-party companies such as the ‘‘Facefarm Production Resume’’ program. The platform can provide intelligent and refined management services such as positioning monitoring, command and dispatch, area statistics and information management for agricultural machinery operations. Providing scientific management and business decisions for agricultural production processes by measuring basic farmland data, collecting location information, and matching intelligent agricultural machinery. This greatly improves the efficiency of the entire system. As most of China’s existing research has focused on the synthesis of information, the statistics and records of agricultural machinery use, it is not possible to conduct data analysis and provide reasonable advice based on existing data [10]. The structure of this paper is as follows: the section describes data acquisition and real-time processing; the third section provides key algorithms; the fourth section describes system parameter settings and system architecture design, as well as data storage and analysis; the fifth section conducts an experimental evaluation and displays the results; and the final section provides a summary

OVERALL FRAMEWORK

DATA FUSION

ANALYSIS ALGORITHM

CONCLUSION