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OMRON ZFX-C Vision Sensor in Practical Use

F: | Au:FAN | DA:2026-04-23 | 865 Br: | 🔊 点击朗读正文 ❚❚ ▶ | Share:

Ferrite core: Comes with two cores, installed at both ends of the camera cable and power cable. The power cable needs to pass through the magnetic core once.

2.4 Overview of I/O interfaces

The controller provides multiple interfaces:

Parallel interface: standard port (12 point input/23 point output) and expansion port (14 point data output)

RS-232C/422: Serial communication, maximum 115200bps

Ethernet: 100BASE-TX/10BASE-T

USB 2.0: MINI-B interface

Monitor output: Analog RGB, VGA (640 × 480)

Basic operation and measurement process

3.1 Three working modes

Mode switch position, mode purpose

MENU menu mode setting measurement conditions, registering models, adjusting images

ADJ adjusts the continuous measurement mode (without outputting results), adjusts the threshold and parameters

RUN mode actual measurement, output results to external devices

3.2 Three steps to complete measurement setup

Taking the detection of whether different products are mixed in as an example:

Step 1: Select the measurement item

MENU mode → select [Setup] → [Item] → [Shape] → [Pattern] (pattern search).

Step 2: Register the model

Select [Register model] → Move and adjust search area → [Apply].

Press the AUTO key or select [AUTO] on the screen to automatically set the optimal parameters (color filters, model images, reference values, etc.).

Step 3: Adjust the threshold and start measuring

Switch to ADJ mode and confirm that the measurement is stable and accurate.

Switch to RUN mode, input the trigger signal, and start measuring.

Important: After setting up, be sure to save the data (MENU → [System] → [Save]). Otherwise, any changes made after power failure will be lost.


Detailed Explanation of Measurement Projects

ZFX-C offers a wide range of measurement items, divided into five categories: shape, size, edge, brightness/color, and application.

4.1 Shape detection

Project Description Output

Pattern Search: Register image patterns as models to search for similar areas, supporting ± 45 ° tilt correlation values, position X/Y, and angle

Graphic Search is a model search mainly based on contour information, suitable for low contrast or partially cropped image related values, position X/Y

Flexible Search treats subtle differences as the same type and registers up to 36 model related values, locations, and model numbers

Sensitive Search detects subtle differences and automatically subdivides models (up to 100 sub models) into related values, positions, and solid color rates

Key parameters:

Search mode: High speed/Standard/High precision (sub-pixel units)

Rotation range: 0~180 °, combined with skipping angle (1~30 °)

Verification: Conduct a detailed search of all candidate points when turned on

Candidate level: 0~100, set the threshold for rough search

4.2 Dimensional Inspection

Project Description Output

Area measures the area, center of gravity, axis angle area, center of gravity X/Y, and axis angle of a specified color

Labeling counts the connected area of the measured color as one label, and outputs the number, area, position, center of gravity, perimeter, bounding rectangle, and roundness of the labels

Multi Colors simultaneously measure the area of up to 4 colors, including their respective areas and differences

Key parameters for area detection:

Fill profile: When turned on, measure the target color and the entire external area, suitable for workpieces with bumps and depressions.

Measure axis angle: Calculate axis angle when turned on (processing time increases).

Calibration: Convert pixel units to actual size when turned on.

4.3 Edge detection

Project Description Output

Position: Detecting edge coordinates within the region, edge position X/Y

Width detects the distance between two edges and the width of the edge

Count the number, spacing, width, average spacing, and average width of edges

Angle Detects edges in two areas and calculates the angle angle of two points

Key parameters for edge detection:

Measurement mode: Average/Peak/Valley

Color: Bright → Dark/Dark → Bright

Edge level: 1~99, set the threshold for determining the concentration change at the edge

Noise level: 0~255, concentration changes below this value are ignored

Noise width: 0~255, fluctuations within this width are considered noise

Partition size: 1~99, divide the area and calculate the edges

4.4 Brightness/Color Detection

Project Description Output

The average concentration and concentration deviation within the brightness measurement area, as well as the average concentration and concentration deviation

Hue (HUE) measures the average and deviation of hue, saturation, and brightness. Hue/saturation/brightness average and deviation

Key parameters for hue detection: OK ranges can be set for hue, saturation, and brightness respectively. Suggest setting a wider range of saturation and brightness to make hue judgment more stable.

4.5 Application detection

Project Description Output

Grouping: Group products, register up to 64 models, and output the index related values, positions, and index numbers of the most similar models

Defect detection includes values, locations, and numbers of defects such as scratches, dirt, and burrs

Key parameters for defect detection:

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