Normalized Torque Analysis for Screw Tightening Defect Detection

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Solution Overview

Problem

Existing screw tightening state detection devices struggle to determine screw tightening defects, particularly when using tapping screws with soft materials like resin, due to variations in torque values across different workpieces.

Innovation Solution

A screw tightening defect determination device that samples rotary torque data at a predetermined cycle, generates a normalized torque data sequence, and determines screw tightening defects based on this sequence, even when using tapping screws in soft materials.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of manufacture

If torque value-based determination is used to detect screw tightening defects, then the detection method is simple, but it cannot accurately determine defects when torque values vary across different workpieces

Engineering Contradiction:

Improvedetection method simplicityVSAvoiddefect determination accuracy

Core Design Contradiction:

Ease of manufactureVSMeasurement precision

Solution Approach 1:

The patent transforms the absolute torque value parameter into a normalized torque value parameter by dividing each torque value by the maximum torque value in the sequence. This parameter transformation enables accurate defect determination across different workpieces with varying torque characteristics, resolving the contradiction between simple detection and accurate determination.

Inventive Principle:

Principle #35Parameter changes

2Measurement precision

If normalized torque data sequence is generated and used for defect determination, then defect detection accuracy improves across different workpieces, but the data processing complexity increases

Engineering Contradiction:

Improvedefect determination accuracyVSAvoiddata processing complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent applies parameter transformation by normalizing torque values through division by the maximum value, creating a standardized sequence that improves detection accuracy while maintaining relatively simple processing logic.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The system uses the maximum torque value from the torque sequence as a reference feedback value to normalize all other torque values. This feedback mechanism enables accurate defect determination without requiring complex external reference data or complicated processing algorithms.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS12220777B2Screw tightening defect determination device and learning device

Publication Date: 2025.02.11 OMRON CORP

AI summary

Even when a tapping screw is used in a soft material, it is determined whether or not a screw tightening defect has occurred. A PLC (10) comprises a determination unit (13) which for a rotational torque data sequence having a predetermined number of data points, generates a normalized torque data sequence that is the amount of change with respect to rotational torque at a first data point of the data sequence, and determines whether screw tightening is defective, on the basis of the normalized torque data sequence.