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Woven Fabric AI Visual Inspection Equipment

Woven fabric AI visual inspection equipment targets warp and weft structured woven cloth, performing inline inspection of warp and weft breaks, missing weft, weft shrinkage, holes, weaving defects, oil stain, color differences and other defects, with OK/NG output and production line interlocking.

Materials Overview

Warp and weft structures are more stable than knit, but stripe and check matching needs extra handling

Quick answers

Woven fabric AI visual inspection equipment images warp-and-weft woven cloth, and the algorithm identifies defects such as broken warp, broken weft, missing weft, weft shrinkage, holes, weaving defects, oil stain, and color difference, outputs OK/NG results, and interlocks with the production line. It is suitable for roll and cut-piece formats.

Woven fabric is formed by warp and weft yarns interwoven at right angles; its structure is flatter and more stable than a knit, and it does not stretch easily, so positioning is relatively easy. However, its warp and weft directions are strongly oriented, and once a yarn breakage or weaving fault occurs the defect extends along the warp or weft, a directional characteristic that should be exploited during recognition.

Defects specific to woven fabric include broken warp, broken weft, missing weft, weft shrinkage (curled weft yarn), holes, weaving defects (missing warp or weft, float stitches, reed marks), oil stains, and color difference. Plaid and striped fabrics additionally require stripe and check matching inspection to prevent cutting offset.

Woven fabric is mostly used in garments, bags and luggage, automotive interiors, and home textiles, with a very large number of varieties. For inspection, AI distinguishes normal weave texture from weaving defects; for plaid fabrics, a datum is established and offsets are then compared against it. Changing varieties mainly means adjusting illumination and recipe.

Applicable Type

Plain Weave

Basic weave structure, with the focus on warp and weft breaks and holes

Twill / Satin

Structure variation, with a focus on weaving faults and gloss

Check / Stripe

Patterned; the focus is on stripe and check matching

High-density Woven Fabric

Fine, dense yarn; high pixel equivalent requirement

Woven Cut Pieces

Already cut, inspected piece by piece with defect locating

Common defect

Defect TypesTypical ManifestationsInspection Focus Points
Broken warpSingle or multiple warp yarn breaksElongated along the warp direction
Weft Break / Missing WeftMissing Weft YarnElongated along the weft direction
Weft shrinkageWeft yarn curling, loop formationLook for local bulges on the fabric surface
holeWarp/weft breakage forming holesBacklight Is the Most Direct
Weaving DefectsMissing warp, skipped yarn, reed markRequires a normal weave structure model
Oil Stain / DirtOil Spots, StainsContrast Against Base Color
color difference Inconsistent shade within the same batchStable light source and color datum
Stripe and check matching deviationPlaid and stripe misalignmentRequires Datum Comparison

inspection Workflow

Complete chain from loading to judgment

Visual inspection judgement chainThe complete chain from image acquisition to OK/NG judgement and PLC interlocking.image acquisitiontrigger captureTarget Positioningtemplate matchingfeature recognitionAlgorithm JudgementResult JudgementOK / NGindustrial communicationPLC interlockingRelease OKRejection / NG AlarmEvery step's result retains the image and judgement item, for traceability and review
Inspection Judgement Chain — Acquisition → Positioning → Recognition → Judgment → Communication interlocking; the entire chain runs locally on the machine.
  • 01 Woven fabric loading / roll unwinding or cut-piece feeding
  • 02 Flattening and tension control
  • 03 Triggered Imaging
  • 04 Warp/weft direction positioning
  • 05 Region segmentation and defect segmentation
  • 06 Weaving defect classification and grading
  • 07 Stripe and check matching comparison (plaid fabric)
  • 08 Synthesized OK / NG
  • 09 Marking / rejection and image archiving

AI Inspection Principles

AI Visual Inspection Principles

Woven fabric inspection exploits the warp-and-weft directionality: normal construction is a regular orthogonal grid, and defects break this periodicity. The algorithm builds a model of the normal construction and judges deviations such as missing warp, missing weft, weft shrinkage and weaving faults as anomalies; for plaid fabrics an additional baseline comparison is made. Imaging stability remains the precondition.

For illumination, diffuse light provides uniform lighting to see oil stain and color difference clearly, while low-angle light exposes surface relief and reed marks. Stains on dark woven fabric and holes in light woven fabric require separate light settings, with recipes grouped by color.

Stripe and check matching requires establishing a datum pattern on an OK sample first, then comparing the actual offset. The specific tolerance is subject to the customer's acceptance criteria and must be confirmed by measured sample testing.

Applicable Industry

Applicable equipment

Common Question

Where does the inspection difficulty differ between woven and knit fabrics?
Woven fabric is flatter and less stretchy, so positioning is relatively easy; knit fabric is elastic and deforms easily, so tension must be stabilized first. For woven fabric the difficulty lies more in stripe and check matching and in the pixel scale of fine weaves.
Can stripe and check matching on plaid fabric be checked?
Yes. A datum pattern is first established on an OK sample, then the actual offset is compared against it, and anything beyond the tolerance is judged abnormal. The tolerance is subject to the customer's acceptance criteria and requires measured sample testing.
Can weave defects be seen clearly in high-density fine-yarn woven fabric?
Yes, but it demands a high pixel scale - the finer the yarn, the higher the resolution required. The camera and lens must be derived backwards from the smallest weaving defect size, subject to measured testing.
Can Back-Side Defects Be Detected?
Single-side inspection can only see the visible side. If both sides are required, a rear station or a turnover mechanism must be added; this depends on the site layout and is outside single-side capability.
What is the inspection accuracy?
To be added. Accuracy is determined by the field of view and camera resolution: pixel equivalent = FOV ÷ pixel count. First define the minimum defect size, then work back to the imaging solution and validate it by measurement with samples.
What samples are needed to develop a solution?
Provide OK and NG samples in different weaves and colors (including plaid samples), the defect acceptance criteria, loading format and production line cycle time.
Can It Be Integrated Into an Existing Production Line?
Yes. The system exchanges data with the PLC over I/O, TCP, RS485, Modbus, S7, Profinet and others, and outputs OK/NG to trigger rejection; the specific protocol depends on the site.

Submit sample testing

Send us OK and NG samples of woven fabric in different weaves and colors (including plaid samples), and we will carry out weave modeling and measured stripe and check matching to recommend an illumination solution.

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Each file must not exceed 20 MB
    JPG / PNG supported, multiple files allowed
    Each file must not exceed 20 MB
      JPG / PNG supported, multiple files allowed
      Each file must not exceed 20 MB
        A solution engineer will contact you within 1 business day after submission

        Need to assess imaging conditions, defect criteria and cycle time item by item? Go to the Full Requirement Assessment →

        Send Us Your Material and We Will Show You the Measured Results

        Provide several OK and NG samples of the material, and a solution engineer will run actual imaging and judgement tests on the equipment to give a workable inspection configuration recommendation, rather than reading the datasheet alone.

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