Principle of hardness sorting:

Due to the different effects of hardness value, material variety, depth of hardening layer, heat treatment state, and defects in components (such as cracks, pores, inclusions, etc.) of magnetic materials on the magnetic field, there exists a certain corresponding relationship. When the tested workpiece is in contact with a uniformly distributed probe magnetic field, the magnetic field inside the probe changes, and an excitation current is generated in the probe coil, which is transmitted to the instrument through a wire. After being analyzed and processed by the central circuit of the instrument, the quality status of the tested workpiece can be automatically judged and displayed on the display screen through computer software processing. It is precisely through the changes in electromagnetic effects caused by the magnetic flux of the tested workpiece that electrical signals are generated. After amplification and conversion, they are processed by computer software to achieve the detection of defects such as material composition, hardness, surface hardening depth, cracks, and mixing

Technical parameters:

Hardness testing sensitivity: Rockwell: ± 2HRC; Vickers: ± 40Hv. Error range: Effective sorting of different materials

Main technical parameters

Hardness material sorting section:

1. Automatic sorting (removal), automatic material layout, automatic statistics of the total number of inspected workpieces, qualified number, qualified rate, and other functions

2. After inspection, there is no damage to the parts

3. No auxiliary processes such as demagnetization and cleaning are required after inspection

4. Error range: Hardness testing sensitivity: Rockwell: ± 2HRC; Vickers: ± 40Hv

5. Type of probe: Through type probe

6. Characteristics of hardness material sorting instrument

1) Probe excitation current: adjustable from 1 to 256 levels

2) Linear gain: 1-256 times

3) Provide eight frequency measurement signal amplitude displays and sort them according to the set threshold value

4) Analog and digital fast automatic zero adjustment

5) Impedance plot points display phase and amplitude changes

6) Automatic measurement and display of X/Y component values and amplitude values

7) Elliptical sorting domain can be automatically set based on sampling points, and its position and size can be manually adjusted

8) Can be used for manual and online automatic detection, with adjustable signal delay and detection time

9) Provide sorting control signals

Eddy current testing section:

1. Sensitivity of flaw detection: cracks and defects that extend from the surface of the workpiece to the inside of the metal with a depth of ≥ 0.05mm and a length of ≥ 1mm; For cracks inside the metal that have not yet extended to the surface of the workpiece, cracks with a depth of ≥ 0.2mm and a length of ≥ 1mm can be detected when the metal thickness between the upper edge of the crack and the surface of the workpiece is ≤ 0.2mm

2. Characteristics of eddy current testing instruments:

1) Detection frequency range: 100Hz~1MHz, adjustable

2) Band pass filtering, center frequency 250-1000KHz, 8 levels

3) Gain: Each channel has a gain of 0-60dB, with an adjustment of 1dB per level

4) Phase: 0 °~360 °, with a step distance of 1 °

2. High precision detection, ultrasonic flaw detector conducts high-speed data collection, quantitative analysis, calculation, and identification of pulse signals, and its detection accuracy can be higher than that of traditional eddy current flaw detector detection results.

3. Record and archive data detection, ultrasonic flaw detector can present detection records up to the defect image.

4. High credibility and good reliability. The eddy current flaw detector manufacturer's flaw detector can collect and store data information comprehensively and objectively, and carry out parallel processing or post-processing processes on the data information collected by the digital ultrasonic flaw detector. The data signal can be analyzed in the frequency domain, frequency domain, or image. It can also classify the quality of product workpieces based on computer vision, reducing the harm of human error and improving the credibility and reliability of search.