Ultrasound Self-Test Feedback for Hardware Trend Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing ultrasound systems lack a mechanism for automatic and continuous feedback of self-test data to manufacturers for trend analysis and proactive maintenance, limiting the ability to predict and prevent component failures.
Innovation Solution
An ultrasound system configured to perform periodic self-testing, store results in a log, and automatically upload them to a manufacturer's database for analysis, enabling trend identification and development of updated self-test protocols.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If self-test data is manually retrieved and reviewed by service engineers, then system reliability monitoring is achieved, but automation and continuous trend analysis are limited
Solution Approach 1:
The patent implements automatic feedback mechanisms where self-test data is continuously collected from ultrasound systems, transmitted to a centralized database, and analyzed to generate insights about component health trends. This automated feedback loop eliminates manual data retrieval and enables continuous monitoring, directly resolving the contradiction between reliability monitoring and automation extent.
Solution Approach 2:
The system enables self-service through automated self-testing and data reporting capabilities built into the ultrasound systems. The systems automatically perform self-tests, store results, and transmit data without requiring service engineer intervention, thus improving both reliability monitoring and automation while reducing manual labor.
2Reliability
If self-test data is collected and analyzed for trend analysis, then predictive maintenance capability is improved, but data management complexity increases
Solution Approach 1:
The patent introduces a centralized database and automated analysis system as intermediaries between the ultrasound systems and service engineers. This intermediary infrastructure handles the complexity of data collection, storage, and analysis, enabling predictive maintenance capabilities while shielding users from data management complexity. The intermediary processes data automatically, transforming raw self-test data into actionable insights.
3Reliability
If periodic self-testing is performed and results are automatically uploaded, then component failure prediction is enhanced, but system operational overhead increases
Solution Approach 1:
The patent implements periodic self-testing at predetermined intervals, balancing the need for failure prediction with operational efficiency. By scheduling tests periodically rather than continuously, the system achieves reliable trend data while minimizing operational overhead. The periodic action allows the system to maintain predictive capabilities without excessive time loss.
Solution Approach 2:
The system performs preliminary self-tests during idle periods or between patient examinations, capturing component health data before failures occur. This preliminary action enables failure prediction without significantly impacting operational time, as tests are conducted in advance during available windows rather than during critical operational periods.
Data Source
Figure 1a
Figure 1b
Figure 2
AI summary
An ultrasound system is configured to perform periodic self-testing of the system's hardware components. Results of the self-testing are stored on the ultrasound system in a data log, and periodically uploaded to a self-test database. The self-test database is sorted, then analyzed by engineers of the ultrasound system manufacturer to discern variances or trends in ultrasound system hardware performance or operation. As a result of the analysis, updated or improved self-test programs are developed by the system manufacturer and uploaded to and installed on ultrasound systems of the installed base of systems.