CAN Connectivity Diagnostics for Industrial Machine Communication Faults
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Solution Overview
Problem
The complexity of modern industrial machines with numerous Electronic Control Modules (ECMs) and communication systems like CAN, LIN, and Ethernet makes diagnosing communication and connectivity issues challenging, especially for technicians who lack proper training and tools, leading to increased downtime and customer dissatisfaction.
Innovation Solution
A CAN and Connectivity Health (CCH) test system and method that includes a diagnostic module capable of analyzing data from industrial machines, identifying potential sources of issues, and providing recommendations to technicians for troubleshooting, using a combination of hardware and software tools for remote and on-site diagnostics, including telematics systems for data transmission and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If technicians use traditional diagnostic methods for CAN and connectivity issues, then they can perform basic troubleshooting, but the diagnostic capability is insufficient and time-consuming
Solution Approach 1:
The system performs preliminary diagnostic actions by automatically executing a standardized troubleshooting sequence before technician intervention. The diagnostic module pre-configures test parameters, communication protocols, and analysis algorithms to rapidly assess CAN bus health, connectivity status, and component functionality, eliminating the need for technicians to manually set up diagnostic procedures and reducing resolution time
Solution Approach 2:
The patent introduces an intermediary diagnostic module that acts as a bridge between the complex communication system and the technician. This module translates raw diagnostic data into actionable insights, provides structured troubleshooting guidance, and automates analysis of communication issues, thereby enhancing technician capability without requiring extensive specialized training
2Measurement precision
If technicians travel to remote locations for diagnostics, then they can perform on-site troubleshooting, but the time and cost increase significantly
Solution Approach 1:
The system creates a virtual copy of the diagnostic capability that can be remotely accessed. The diagnostic module captures and transmits system data, error codes, and communication logs to remote experts or central servers, allowing diagnostics to be performed on copied data without requiring physical presence at the remote location, thereby maintaining diagnostic accuracy while eliminating travel time
Solution Approach 2:
The system implements automated feedback loops where diagnostic results are immediately analyzed and used to guide subsequent troubleshooting steps. The diagnostic module continuously monitors communication bus status, compares readings against known good parameters, and provides real-time feedback to technicians or remote systems, enabling rapid iteration and resolution without prolonged on-site visits
3Reliability
If the diagnostic system is more robust and sophisticated, then the diagnostic capability improves, but the system complexity and cost increase
Solution Approach 1:
The diagnostic system is segmented into modular functional components, each responsible for specific diagnostic tasks such as CAN bus monitoring, connectivity testing, error code analysis, and component diagnostics. This modular architecture allows the system to achieve robust and sophisticated diagnostic capabilities through composition of specialized modules rather than requiring a single complex monolithic system, thereby improving reliability while managing complexity through modular design
Data Source
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AI summary
A system and method for diagnosing connection and communication in an industrial machine includes performing a software check to obtain software data related to software applications, performing a connectivity check to obtain connection status data for one or more controllers, and performing a CAN bus check to obtain CAN bus data. The software data, connection status data, and CAN bus data is analyzed to determine a likely cause of an industrial machine connection or communication issue. A solution to the industrial machine connection or communication issue is output to a technician based on the analyzed data.