Sniffer Probe Leak Detection With Scanned Test Point Verification
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Solution Overview
Problem
Current leak detection methods are often random, unreliable, and inconsistent, leading to missed detections and reduced accuracy in identifying leaks, particularly in products containing refrigerants.
Innovation Solution
A computer-implemented system with a sniffer probe, sensor unit, scanner, and processor unit for real-time monitoring and data comparison, ensuring consistent leak detection by comparing target and monitored parameters to determine the status of leak testing points.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional random leak detection methods are used, then the testing process is simple, but the detection reliability and accuracy deteriorate
Solution Approach 1:
The system segments the leak detection process into distinct functional modules: scanner for object identification, processor for data management, sensor unit for real-time monitoring, and sniffer probe for leak detection. Each module performs a specific function, improving overall reliability through specialized components while keeping individual components manageable in complexity.
Solution Approach 2:
The sensor unit continuously monitors testing parameters in real-time and feeds this information back to the processor, which compares actual values against target values. This feedback mechanism ensures consistent detection conditions and improves reliability by automatically adjusting or flagging deviations from expected parameters.
2Reliability
If traditional random leak detection methods are used, then the testing process is simple, but the detection consistency deteriorates
Solution Approach 1:
The scanner performs preliminary object identification and the processor pre-establishes target testing parameters before the actual leak detection begins. This preliminary setup ensures that consistent detection criteria are applied to all test objects, improving consistency across different testing scenarios.
Solution Approach 2:
Real-time monitoring of testing parameters with continuous feedback to the processor ensures that detection conditions remain consistent throughout the testing process, automatically maintaining uniformity in detection efforts across multiple test objects.
3Measurement precision
If real-time parameter monitoring and comparison is implemented, then leak detection accuracy improves, but system complexity increases
Solution Approach 1:
The system replaces manual monitoring and comparison of testing parameters with automated electronic sensors and processors. The sensor unit electronically monitors parameters in real-time, and the processor automatically compares actual values against target values, significantly improving measurement precision while the electronic automation manages the complexity.
Data Source
AI summary
Systems, computer-implemented methods and related aspects for leak detection testing are disclosed. The system for a leak detection test comprises a leak detector unit comprising a sniffer probe and is configured for leak testing a test object by sniffing a testing point of the test object. The system further comprises a sensor unit configured to monitor a set of parameters of the leak detection test in real time. The system further comprises a scanner for scanning the test object. The system further comprises a processor unit configured to receive object identification data of the test object by scanning the test object thereby identifying the test object, receive a first set of leak test data for the identified test object, the first set of leak test data comprising information about a target set of process parameters for the leak detection test of the testing point, receive a second set of leak test data by the sensor unit of the leak detector system, the second set of leak test data representing a set of monitoring parameters obtained by the sensor unit in real time during the leak detection test of the testing point, and output a signal indicative of a status of the leak detection test based on a difference level between the first set of leak test data and the second set of leak test data.