Cloud Knowledge Map Fault Diagnosis With Multimedia Recommendations
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Solution Overview
Problem
Existing digital factory systems struggle with timely and efficient fault diagnosis and solution recommendation, as most diagnostic programs rely on established modes and limited data, failing to account for specific task characteristics and sensor data.
Innovation Solution
An intelligent fault diagnosis and solution recommendation system utilizing a third-party robot with data stream and multimedia content analysis modules, coupled with neural networks, to analyze fault data and provide accurate recommendations based on cloud databases and knowledge maps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional diagnostic programs use established modes and limited data, then device complexity is reduced, but measurement precision and reliability of fault diagnosis deteriorate
Solution Approach 1:
The patent introduces a third-party robot as an intermediary diagnostic system that collects data from multiple sources (sensor data, operation data, maintenance data) and processes them through neural networks. This external mediator provides comprehensive analysis without requiring the original equipment to become more complex, thereby improving diagnosis accuracy while maintaining simple device architecture.
Solution Approach 2:
The third-party robot is designed with multi-functional capabilities, serving as both a data collection platform and an analysis system. It integrates multiple data stream analysis modules and multimedia content analysis modules, enabling a single system to perform comprehensive fault diagnosis across different equipment types, thus improving measurement precision without proportionally increasing overall system complexity.
2Reliability
If workers manually analyze fault reasons, then diagnostic thoroughness improves, but loss of time and productivity deteriorate
Solution Approach 1:
The system implements automated self-service diagnosis through neural networks and AI algorithms that automatically analyze collected data, generate fault diagnoses, and provide solution recommendations. This eliminates the need for manual worker analysis while maintaining high reliability, thereby significantly reducing the time required for fault resolution.
Solution Approach 2:
The system performs preliminary data collection and analysis automatically as soon as fault symptoms appear. By pre-configuring multiple analysis modules and neural network models, the system is ready to immediately process data and provide diagnoses without waiting for manual intervention, thus reducing loss of time while ensuring reliable diagnosis through comprehensive preliminary analysis.
3Measurement precision
If diagnostic systems use only device self-collected data, then ease of operation improves, but measurement precision and adaptability deteriorate
Solution Approach 1:
The third-party robot acts as an intermediary data collection platform that automatically gathers information from multiple sources including sensor data, operation data, maintenance data, and multimedia content. This mediator handles the complexity of multi-source data acquisition, providing comprehensive and accurate fault detection data without burdening the original equipment with complex data collection operations.
4Adaptability or versatility
If fault diagnosis is performed by the equipment owner, then adaptability to specific equipment improves, but device complexity and loss of time worsen
Solution Approach 1:
The third-party robot serves as an adaptable intermediary that can be deployed across different equipment types. Through its multi-functional design and neural network capabilities, it adapts to various diagnostic scenarios without requiring each piece of equipment to have its own complex diagnostic system, thus maintaining high adaptability while avoiding increased device complexity.
Data Source
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AI summary
Examples of the present disclosure provide a method, device, system and computer readable storage medium for fault diagnosis and solution recommendation. The method includes: obtaining original data including fault problem of a target device; analyzing the original data including fault problem to obtain problem description information; analyzing the problem description information to obtain a diagnosis report; according to the diagnosis report, obtaining a video and/or document solution for the fault based on a cloud knowledge map, and recommending the solution to a user; the knowledge map comprises: nodes representing the fault, video solution and/or document solution, and multiple edges representing the relationship between nodes. The technical solutions of the present disclosure can achieve the intelligent fault diagnosis and solution recommendation.