Automated Circuit Validation via Priority Node Analysis
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Solution Overview
Problem
Existing methods for validating and debugging electronic circuits require high familiarity with the circuit and its operation, making it challenging for designers without extensive experience to identify and isolate faults, as they rely heavily on trial and error.
Innovation Solution
An automated system using machine learning and artificial intelligence to guide the validation process by analyzing circuit schematic data, comparing expected and measured waveforms, and iteratively identifying faulty components through a diagnostic tree, allowing for validation even by operators without deep knowledge of the circuit.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If automated validation systems are implemented, then validation accessibility is improved, but system complexity increases
Solution Approach 1:
The patent introduces an automated validation system as an intermediary between the circuit under test and the validator. This intermediary system includes a processor that receives test data, compares it against expected values, and generates validation results. The intermediary handles the complexity of circuit analysis internally, presenting simplified interfaces to both the circuit being tested and the user performing validation.
Solution Approach 2:
The system creates virtual copies of circuit behavior through simulation models. Expected waveform data is generated as a reference copy of how the circuit should behave under normal conditions. The actual measured waveform is then compared against this copied expected behavior, allowing validation without requiring direct analysis of complex circuit operations.
2Device complexity
If manual trial and error methods are used, then system complexity is reduced, but validation time increases
Solution Approach 1:
The system performs preliminary actions by pre-calculating and storing expected waveform data for the circuit before actual validation occurs. This expected behavior data is generated in advance through simulation or database queries, so that when actual measurement occurs, the validation can proceed immediately by simple comparison rather than requiring time-consuming analysis during the validation process.
Solution Approach 2:
The patent replaces the manual mechanical process of trial and error with an automated computational system. Instead of physically probing and analyzing circuits through educated guesses, the system uses automated data acquisition, digital signal processing, and computer-based comparison to rapidly validate circuit operation, substituting human cognitive processes with algorithmic automation.
3Productivity
If automated validation is implemented, then validation speed is improved, but measurement precision requirements increase
Solution Approach 1:
The automated validation system incorporates feedback mechanisms where measured waveform data is continuously compared against expected values, and validation results feed back to guide further measurement or adjustment. This feedback loop allows the system to rapidly identify deviations and focus measurement efforts on critical parameters, maintaining precision while operating at high speed through iterative refinement rather than requiring all measurements to be perfectly precise from the start.
Data Source
AI summary
A method comprising categorizing nodes of a fabricated circuit as being priority nodes and nodes as being inferior nodes; evaluating a first priority node by automatically designating for verification the first priority node, and ascertaining whether a measured signal from the first priority node meets a pass-fail criterion for the first priority node; evaluating, when the measured signal from the first priority node meets the pass-fail criterion, a second priority node by automatically designating for verification the second priority node, and ascertaining whether a measured signal from the second priority node meets a pass-fail criterion for the second priority node; and evaluating, when the measured signal from the first priority node does not meet the pass-fail criterion, a first inferior node, by automatically designating for verification the first inferior node, and ascertaining whether a measured signal from the first inferior node meets a pass-fail criterion for the first inferior node.