Fault diagnosis system for hydraulic steering system of self-propelled hydraulic loader

A fault diagnosis system and steering system technology, which is applied to fluid steering mechanisms, vehicle components, special data processing applications, etc., can solve problems such as endangering the safety of field operators, many fault points or links, and affecting the progress of the project. The effect of communication overhead, small computer resources, and low consumption

Inactive Publication Date: 2014-01-01
BEIHANG UNIV
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Problems solved by technology

There are many circuits in each wheel system, and there are many fault points or links; and large self-propelled hydraulic trucks are exposed to harsh working environments such as open air and dust for a long time, so it is very easy to cause equipment failures, which will affect the progress of the project, or even endanger the site. Workers are safe and cause huge economic losses

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  • Fault diagnosis system for hydraulic steering system of self-propelled hydraulic loader
  • Fault diagnosis system for hydraulic steering system of self-propelled hydraulic loader
  • Fault diagnosis system for hydraulic steering system of self-propelled hydraulic loader

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Embodiment Construction

[0022] The present invention will be further described in detail with reference to the accompanying drawings.

[0023] The present invention is a fault diagnosis system for the hydraulic steering system of a self-propelled hydraulic truck. The fault diagnosis system is based on the ARX model and FCM clustering and is obtained by programming in C++ language. The fault diagnosis system is stored in the hydraulic steering system. Each controller (such as figure 2 Shown). The ARX model is an auto-regressive with extra inputs model, or ARX model for short. The FCM clustering is fuzzy C-means clustering, fuzzy C-means, or FCM clustering for short. In the present invention, for quoting the definition of ARX and FCM models, please refer to He Xiangyu and He Qinghua published "Excavator hydraulic system fault diagnosis based on regression model and fuzzy C-means clustering", Journal of Jilin University (Engineering Edition), 2008, 38(1): 13-187. The amount of information required for ...

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Abstract

The invention discloses a fault diagnosis system for a hydraulic steering system of a self-propelled hydraulic loader. The fault diagnosis system monitors the hydraulic steering system according to ultralimit sensing information and monowheel error sensing information which are collected in real time, and whether hydraulic steering system local loop diagnosis based on an ARX model and FCM clustering is determined by monitoring the hydraulic steering system in real time. A driver is informed of results of the hydraulic steering system local loop diagnosis through a vehicle-mounted displayer. The fault diagnosis system is beneficial to improving reliability and safety of the self-propelled hydraulic loader and guaranteeing safety of field personnel.

Description

Technical field [0001] The invention relates to a fault diagnosis of a hydraulic steering system, and more particularly, to a hydraulic steering system suitable for self-propelled hydraulic trucks based on a regression model (ARX model) and fuzzy C-means clustering ( FCM clustering) fault diagnosis system, the fault diagnosis system is stored in each controller of the hydraulic steering system. Background technique [0002] Large self-propelled hydraulic trucks, or hydraulic powered flatbed trucks, are a special type of tire-type large-scale construction machinery, usually referring to a rated load of 50 tons or more, with multi-wheel hydraulic drive, steering, self-leveling and lifting devices. And each wheel can be a dedicated transport vehicle with independent steering. [0003] October 2010, "Large Self-Propelled Hydraulic Truck" edited by Zhao Jingyi, Chemical Industry Press. The structure of the steering control system is introduced in the second chapter and page 57 of this...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): B62D5/06G06F19/24B60R16/02
Inventor 杨丽曼张明李运华李会东张献黄云涛宋云浩
Owner BEIHANG UNIV
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