AI Circuit Inspection Using Datasheet Extraction and Rule Checks
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Solution Overview
Problem
Existing electrical circuit design inspection methods are inefficient, costly, and prone to errors due to their reliance on manual processes and limited software tools, failing to detect a wide range of design errors and best-practice violations in complex circuits, leading to increased re-design iterations and potential faults in final products.
Innovation Solution
An AI-based system for electrical design inspection that autonomously extracts data from electrical component documentation, converts it to a formal language, and performs comprehensive verification using AI models and deterministic algorithms to identify a wide range of errors and violations, including those related to component connections, logical errors, and best-practice guidelines.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual inspection methods are used to review electrical circuit designs, then inspectors can understand component requirements from datasheets, but the process becomes time-consuming and costly
Solution Approach 1:
The patent replaces manual mechanical inspection processes with an automated computer-based system that uses optical character recognition (OCR) to extract text from datasheets and rule-based engines to verify circuit designs. This substitution eliminates human labor while maintaining comprehensive inspection capabilities, directly resolving the contradiction between reliable error detection and time consumption.
Solution Approach 2:
The system creates digital copies of datasheet information through OCR technology, storing extracted component requirements in structured databases. These digital copies enable automated querying and verification without requiring manual reading of physical or PDF datasheets, significantly reducing inspection time while preserving complete component specification data for reliable error detection.
2Reliability
If comprehensive manual review of all component datasheets is performed, then more errors can be detected, but the complexity and cost of the inspection process increases
Solution Approach 1:
The patent segments the complex inspection process into distinct modular components: OCR text extraction module, data parsing module, rule-based verification engine, and reporting module. Each module handles a specific aspect of the inspection, making the overall complex process manageable and maintainable while achieving comprehensive error detection through the coordinated operation of all segments.
Solution Approach 2:
The system introduces an intermediary structured database that stores extracted component requirements and design parameters in standardized formats. This intermediary layer translates unstructured datasheet information into machine-readable forms that the verification engine can process, simplifying the complexity of directly comparing raw datasheet text against circuit designs while maintaining comprehensive detection capability.
3Productivity
If existing verification software tools are used, then some design rule checks can be performed, but they cannot identify errors related to datasheet information such as missing pull resistors or communication protocol mismatches
Solution Approach 1:
The system performs preliminary extraction and structuring of component-specific requirements from datasheets before the actual verification process. By pre-processing datasheet information to identify specific constraints such as required pull resistors, communication protocol specifications, and operating conditions, the system enables the verification engine to accurately detect these errors during automated inspection, overcoming the limitations of traditional tools that lack access to detailed component specifications.
Data Source
AI summary
An artificial intelligence (AI) based system and method for electrical design inspection, configured to autonomously extract, convert, and analyze data from electrical documentation related to electrical circuits by utilizing AI algorithms along with deterministic algorithms in order to produce output results.