A Maintenance and Troubleshooting Method Based on Integrated Information and System Principles

Su, Yan; Liang, Xue; Wang, Hui; Wang, Jin Jun; Pecht, Michael

doi:10.1109/access.2019.2915327

Cited by 7 publications

(4 citation statements)

References 33 publications

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“…For example, an ontology-based schema may contain "component-isPartOf-subsystem" while "receiver-isPartOf-radar" could be instances of this schema, i.e., a knowledge graph. Recently, researchers have more focused on ontology-based fault knowledge modeling to achieve fault knowledge extraction and sharing [39][40][41][42]. Therefore, ontology is well suited for describing a fault knowledge model, and knowledge graphs as instances of an ontology provide an ideal platform for acquiring and presenting fault knowledge.…”

Section: Knowledge Graphmentioning

confidence: 99%

Exploring Research on the Construction and Application of Knowledge Graphs for Aircraft Fault Diagnosis

Tang

Cui

et al. 2023

Sensors

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Fault diagnosis is crucial for repairing aircraft and ensuring their proper functioning. However, with the higher complexity of aircraft, some traditional diagnosis methods that rely on experience are becoming less effective. Therefore, this paper explores the construction and application of an aircraft fault knowledge graph to improve the efficiency of fault diagnosis for maintenance engineers. Firstly, this paper analyzes the knowledge elements required for aircraft fault diagnosis, and defines a schema layer of a fault knowledge graph. Secondly, with deep learning as the main method and heuristic rules as the auxiliary method, fault knowledge is extracted from structured and unstructured fault data, and a fault knowledge graph for a certain type of craft is constructed. Finally, a fault question-answering system based on a fault knowledge graph was developed, which can accurately answer questions from maintenance engineers. The practical implementation of our proposed methodology highlights how knowledge graphs provide an effective means of managing aircraft fault knowledge, ultimately assisting engineers in identifying fault roots accurately and quickly.

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Section: Knowledge Graphmentioning

confidence: 99%

Exploring Research on the Construction and Application of Knowledge Graphs for Aircraft Fault Diagnosis

Tang

Cui

et al. 2023

Sensors

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“…Evidently, the acceptable state sets for each multistate machine ares 1 The fixed and perfect maintenance resources of each machine are shown in Table 2. Meanwhile, the maintenance action membership matrix R i of each machine is obtained.…”

Section: B Illustrated Examplementioning

confidence: 99%

“…The key to guaranteeing the normal operation of multistate manufacturing systems and accomplishing the anticipated tasks is to develop an effective and reasonable maintenance strategy [1]. An intelligent manufacturing system is a typical multistate industrial system with strict maintenance demands and that requires good quality and high productivity [2].…”

Section: Introductionmentioning

confidence: 99%

Mission Reliability-Oriented Selective Maintenance Optimization for Intelligent Multistate Manufacturing Systems With Uncertain Maintenance Quality

Chen

Zhao

et al. 2019

IEEE Access

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Selective maintenance is widely used as a reliability-centered maintenance strategy due to the limited maintenance resources. However, existing selective maintenance studies only consider basic reliability, which cannot systematically describe the operating mechanism of a multistate system, thereby resulting in the inability to obtain an optimal maintenance strategy. Moreover, intelligent manufacturing systems are highly representative of typical multistate industrial systems. In this study, a mission reliability-oriented selective maintenance optimization model for intelligent manufacturing systems that considers the uncertain maintenance effect was proposed. First, a new connotation and modeling method for mission reliability based on multistate system theory was presented to comprehensively characterize the operating mechanism of intelligent manufacturing systems. Second, a quantitative model between maintenance resources and quality based on real-time data was established to reflect the uncertain characteristics caused by repairmen and tools. Third, a selective maintenance decision model of a multistate manufacturing system was developed under the constraints of maintenance cost and time. This constraint combination optimization problem was solved using the particle swarm optimization algorithm. Finally, a case study of selective maintenance optimization for a cylinder head manufacturing system was presented to verify the proposed method.

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“…Based on the background described above, the author tries to do some troubleshooting [3]- [5] to solve the problems in the simulator. The purpose of this paper is to determine the root of the problem and repair damage to the excavator arm simulator.…”

Section: Introductionmentioning

confidence: 99%

Optimization of the Hydraulic System in the Excavator Arm Simulator

Abdillah

2021

politeknologi

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Most of the heavy equipment units use a hydraulic system, even including systems that are essential for working with a heavy equipment unit. The hydraulic system is a system that utilizes a liquid medium in the form of fluid or oil to generate pressure, which is used to implement, the power train system, the disconnection system, the steering system. The working principle of hydraulics is to utilize the pressure exerted on the tool (which is used for this actuator / cylinder / tube) so that the pressure pushes the piston which is connected to the rod. The hydraulic system in this study is an arm excavator. This simulator is like a hydraulic system in general which consists of a power unit, in this simulator the power unit used is a type of electric motor that is connected to a hydraulic pump. The control unit is in the form of a control valve. The drive unit is an actuator / cylinder / tube. This simulator has been disabled for a long time due to a malfunction. Then the authors performed a simple analysis and improvements to the excavator arm simulator. So the research that is done is to do the 8 step troubleshooting method on the simulator. This step aims to facilitate the repair process in the simulator.

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A Maintenance and Troubleshooting Method Based on Integrated Information and System Principles

Cited by 7 publications

References 33 publications

Exploring Research on the Construction and Application of Knowledge Graphs for Aircraft Fault Diagnosis

Exploring Research on the Construction and Application of Knowledge Graphs for Aircraft Fault Diagnosis

Mission Reliability-Oriented Selective Maintenance Optimization for Intelligent Multistate Manufacturing Systems With Uncertain Maintenance Quality

Optimization of the Hydraulic System in the Excavator Arm Simulator

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