首页> 外国专利> RECOGNITION METHOD AND RECOGNITION APPARATUS FOR WORKING BUCKET COUNT IN SHOVELLING AND LOADING PROCESS OF LOADING MACHINE

RECOGNITION METHOD AND RECOGNITION APPARATUS FOR WORKING BUCKET COUNT IN SHOVELLING AND LOADING PROCESS OF LOADING MACHINE

机译:装卸机装卸过程中工作桶数的识别方法及识别装置

摘要

A recognition method and apparatus for a working bucket count in shovelling and loading processes of a loading machine. By applying a multi-sensor fusion technique to three kinds of pressure sensors in shovelling and loading processes of the loading machine, automatic recognition of a working bucket count in shovelling and loading processes is realized, thereby effectively improving and guaranteeing accuracy of testing data. Meanwhile, excessive working of a driver is effectively prevented, recognition of a working stage of the loading machine is facilitated, and a good foundation is provided for recognizing a working stage accurately and realizing dynamic prediction and control of the working process. The recognition method for a working bucket count or a working period has significance in accurate metering of the sample count during the performance testing process, and also has significance in post-stage sample statistics. The stage division of the working period is realized and the post-stage statistics are made more convenient. Therefore, the testing staff obtain the needed sample count accurately, the testing accuracy is improved and guaranteed, and time and labour being wasted due to excessive sample collection by the driver is prevented.
机译:一种在装载机的铲斗和装载过程中工作铲斗数的识别方法和装置。通过在装载机铲斗和装载过程中对三种压力传感器应用多传感器融合技术,实现了铲斗装载过程中工作铲斗数量的自动识别,从而有效提高并保证了测试数据的准确性。同时,有效地防止了驾驶员的过度工作,有利于识别装载机的工作阶段,并为准确识别工作阶段并实现工作过程的动态预测和控制提供了良好的基础。工作桶数或工作时间的识别方法,对性能测试过程中对样品数的准确计量具有重要意义,对后期样品统计也具有重要意义。实现了工作期的阶段划分,后期统计更加方便。因此,测试人员可以准确地获得所需的样本数量,提高并保证了测试准确性,并且可以防止由于驾驶员过多收集样本而浪费时间和劳力。

著录项

  • 公开/公告号WO2018014716A1

    专利类型

  • 公开/公告日2018-01-25

    原文格式PDF

  • 申请/专利权人 XIAMEN UNIVERSITY;

    申请/专利号WO2017CN91425

  • 发明设计人 HOU LIANG;WANG SHAOJIE;BU XIANGJIAN;

    申请日2017-07-03

  • 分类号G05B19/042;

  • 国家 WO

  • 入库时间 2022-08-21 12:46:20

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