Network Analyzer Drift Verification With Modified Measurement Parameters
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Solution Overview
Problem
Conventional drift verification techniques for network analyzers are time-consuming and inefficient, requiring repeated measurements and data compensation, which affects measurement accuracy.
Innovation Solution
A method and system for drift verification involving modified measurement parameters, where a controller connected to a signal generation and analysis assembly measures and compares first and second results to verify system drift, reducing measurement time by altering parameters such as frequency range, frequency points, and correction settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional drift verification techniques are used with repeated measurements at regular intervals and data compensation, then measurement accuracy can be maintained, but the verification process becomes time-consuming and reduces productivity
Solution Approach 1:
The system performs drift verification measurements at modified frequency points before actual production testing. By pre-characterizing system drift at these specific frequency points and storing the drift data, the system eliminates the need for repeated measurements during production, thereby maintaining accuracy while significantly reducing verification time and improving productivity.
Solution Approach 2:
The verification process is segmented into two distinct phases: (1) drift characterization phase where measurements are taken at modified frequency points to build drift models, and (2) production testing phase where pre-characterized drift data is applied. This segmentation allows comprehensive drift verification to be performed once beforehand, rather than repeatedly during production, resolving the contradiction between accuracy and efficiency.
2Reliability
If repeated measurements at regular intervals are performed for drift verification, then system drift can be detected, but the measurement time and effort increase significantly
Solution Approach 1:
The system performs drift verification measurements at modified frequency points before actual production testing. By pre-characterizing system drift at these specific frequency points and storing the drift data, the system eliminates the need for repeated measurements during production, thereby maintaining accuracy while significantly reducing verification time and improving productivity.
Solution Approach 2:
The system creates a drift model by measuring at modified frequency points that replicates the drift behavior across the full frequency range. This drift model serves as a copy or representation of the actual drift characteristics, allowing the system to verify drift without performing complete repeated measurements, thus reducing time while maintaining reliability.
3Measurement precision
If conventional measurement parameters are used for drift verification, then comprehensive drift analysis can be performed, but the process requires more time and resources
Solution Approach 1:
The system changes the measurement parameters by using modified frequency points that are different from the original production test frequency points. These modified frequency points are specifically selected to effectively characterize drift behavior. By changing parameters in this way, the system achieves comprehensive drift verification with fewer measurements, reducing process complexity while maintaining or improving accuracy.
Data Source
AI summary
A method, a system, and a media related to system drift verification are provided. In the method, first measuring with one or more modified measurement parameters is performed, to generate a first measured result of the modified measurement parameter. Second measuring with one or more modified measurement parameters is performed in response to measuring with the modified measurement parameter, to generate a second measured result of the modified measurement parameter. The second measured result with the first measured result is compared. The modified measurement parameter is different from the original measurement parameter. A compared result of the first measured result and the second measured result is used for verifying a system drift.