Medical Imaging Troubleshooting via Log Event Analysis
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Solution Overview
Problem
Troubleshooting medical imaging equipment is challenging due to the vast number of log events generated, requiring deep knowledge and experience to identify relevant and causal events, making it difficult to determine the root cause of issues.
Innovation Solution
A framework that analyzes log event and state data to generate processed data, providing graphical representations and interactive timelines to highlight primary log events and system conditions, facilitating efficient troubleshooting by service personnel.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If service personnel manually analyze thousands of log events to identify relevant issues, then troubleshooting accuracy may improve with deep knowledge, but time consumption and operational difficulty increase significantly
Solution Approach 1:
The patent replaces manual mechanical analysis of log events with an automated computer-based system that performs pattern recognition and causal relationship analysis. The system automatically processes thousands of log events, identifies primary log events, and determines causal relationships without requiring manual intervention, thereby resolving the contradiction between accuracy and time consumption.
Solution Approach 2:
The patent introduces an intermediary automated troubleshooting system that acts as a mediator between the raw log data and the service personnel. This intermediary system processes and filters log events, presenting only the most relevant information to operators, thus reducing time consumption while maintaining troubleshooting accuracy.
2Reliability
If service personnel manually dig through thousands of log events to identify relevant issues, then comprehensive analysis may be achieved, but operational complexity and difficulty increase
Solution Approach 1:
The patent replaces manual log analysis operations with an automated computer-based system that performs comprehensive pattern recognition and causal analysis. The system automatically processes all log events to ensure comprehensive analysis while eliminating operational complexity by removing manual intervention requirements.
Solution Approach 2:
The troubleshooting system performs self-service by automatically analyzing log events, identifying patterns, and determining causal relationships without requiring service personnel to manually examine each log entry. The system serves itself in processing and interpreting data, thereby maintaining comprehensive analysis while simplifying operations.
3Measurement precision
If service personnel rely on deep knowledge and experience to filter log events, then accurate identification of primary issues may be achieved, but the requirement for highly skilled operators increases system complexity
Solution Approach 1:
The patent replaces the need for human expert knowledge and experience with an automated computer-based system that embeds pattern recognition and causal analysis algorithms. This substitution maintains high identification accuracy while eliminating the complexity associated with requiring highly skilled operators.
Solution Approach 2:
The patent creates a virtual copy of the expert troubleshooting process through software algorithms that replicate pattern recognition and causal analysis capabilities. Instead of relying on human experts, the system uses computational models that copy and automate expert-level analysis, thereby maintaining accuracy while reducing skill requirements.
4Reliability
If all log events are analyzed in detail during troubleshooting, then complete understanding of system state may be achieved, but time and computational resources are wasted on irrelevant events
Solution Approach 1:
The patent extracts only the most relevant log events from the complete set by identifying primary log events and their causal relationships. The system separates relevant from irrelevant data, analyzing only the extracted subset that contributes to understanding the system state, thereby avoiding waste of computational resources on irrelevant events while maintaining complete understanding.
Solution Approach 2:
The patent segments the complete set of log events into hierarchical groups based on causal relationships and relevance. By dividing the log data into segments of varying importance, the system focuses computational resources on critical segments while minimizing analysis of less relevant portions, thus achieving complete understanding with reduced resource consumption.
Data Source
AI summary
A framework for troubleshooting medical imaging equipment. Log event data and state data of one or more components of the medical imaging equipment are received. One or more calculations are performed based on the log event data and state data to generate processed data. One or more representations of the one or more components of the medical imaging equipment may then be generated based on the processed data, the log event data, the state data, or a combination thereof.