Layered detection and quantitative evaluation method for residual stress of hot rolled strip steel

Abstract

The invention relates to a hot-rolled strip steel residual stress layering detection and quantitative evaluation method, and belongs to the technical field of metal rolling process detection methods. According to the technical scheme of the invention, the method comprises the steps: adding a thickness direction detection level on a required measurement point according to the size specification and the steel grade number of strip steel; acquiring stress actual measurement data of different thickness levels of each detection point through a measurement device; and performing weighted calculation on the multi-layer stress data by adopting a data regression mode to obtain characterization values, and taking the characterization value of each measurement point as a quantitative evaluation parameter of the overall stress state of the strip steel. The method has the advantages that the thickness of the strip steel is measured in a layered mode, weighted averaging is carried out on the measured value and the thickness, the characterization value is obtained, the characterization precision of the stress measurement result of the hot-rolled strip steel is improved, and the method can be more accurately used for evaluating the strip shape of the hot-rolled strip steel.

Description

Technical Field

[0001] This invention relates to a method for detecting and quantitatively evaluating residual stress stratification in hot-rolled strip steel, belonging to the technical field of metal rolling process detection methods. Background Technology

[0002] Residual stress is one of the main factors affecting workpiece quality in the machining field. However, with the increasing proportion of high-strength steel in the steel industry, the phenomenon of residual stress inducing shape defects in high-strength hot-rolled strip steel has become a major pain point in the industry. Currently, residual stress detection for hot-rolled strip steel often involves measuring the residual stress values ​​on the surface or neutral plane along the width of the strip, thereby constructing a stress distribution curve in the width direction to assess the relationship between stress and shape. Common detection methods include blind hole testing, magnetic measurement, and X-ray diffraction. However, this detection and evaluation method mainly draws on traditional machining practices. Due to the coupling effect of temperature gradient, plastic deformation, and phase transformation behavior during rolling, complex stress gradients easily form along the thickness direction of the strip steel. Stress differences in the thickness direction can also affect the measurement results, potentially misleading the judgment of the stress-shape relationship. Therefore, traditional detection and evaluation methods are difficult to accurately assess the stress distribution of hot-rolled strip steel. Summary of the Invention

[0003] The purpose of this invention is to provide a method for detecting and quantifying residual stress in hot-rolled strip steel. By measuring the strip steel thickness in layers and taking a weighted average of the measured values ​​with the thickness to obtain a characterization value, the accuracy of the stress measurement results of hot-rolled strip steel is improved. This method can be used more accurately for evaluating the shape of hot-rolled strip steel and effectively solves the above-mentioned problems in the background technology.

[0004] The technical solution of this invention is: a method for detecting and quantitatively evaluating residual stress stratification in hot-rolled strip steel, comprising the following steps: S1. Determine multiple inspection levels in thickness directions based on the size and grade of the strip steel; S2. Obtain measured stress data at different levels in the thickness direction at each detection point using a stress measurement device; S3. A data regression algorithm is used to perform regression processing on the multi-layer stress measurement data to obtain characteristic parameters that characterize the stress state of each measurement point, and the characteristic parameters of each measurement point are used as quantitative evaluation indicators of the overall stress state of the strip.

[0005] In step S1, the number of detection layers is determined proportionally according to the strip thickness, specifically satisfying the following: no less than 3 detection layers are set in the thickness direction, and the spacing between adjacent layers is not less than 20% of the total strip thickness.

[0006] In step S2, the surface of the strip is pretreated before stress measurement to avoid the influence of iron oxide scale on the measurement results.

[0007] The stress measuring device used in step S2 is a non-destructive testing device such as magnetic or ultrasonic testing, and it is capable of measuring deep stress.

[0008] The expression for calculating the representation value in step S3 is: .

[0009] In step S3, the strip thickness percentage is the thickness percentage of the surface closest to the nearest surface, and the neutral surface thickness percentage is the maximum value.

[0010] The beneficial effects of this invention are: by performing layered measurement of strip thickness and weighted averaging of the measured values ​​with the thickness to obtain a characterization value, the accuracy of the characterization of the stress measurement results of hot-rolled strip steel is improved, and it can be used more accurately for the evaluation of the shape of hot-rolled strip steel. Attached Figure Description

[0011] Figure 1 This is an example diagram of the measurement points in an embodiment of the present invention; Figure 2 This is a comparison chart of the measurement results of the present invention; Figure 3 This is a comparison chart of stress values ​​at different thicknesses according to the present invention; In the diagram: Measurement point 1, thickness direction 2, width direction 3. Detailed Implementation

[0012] To make the purpose, technical solutions, and advantages of the invention's embodiments clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described are only a small part of the embodiments of the present invention, not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the protection scope of the present invention.

[0013] A method for detecting and quantitatively evaluating residual stress stratification in hot-rolled strip steel includes the following steps: S1. Determine multiple inspection levels in thickness directions based on the size and grade of the strip steel; S2. Obtain measured stress data at different levels in the thickness direction at each detection point using a stress measurement device; S3. A data regression algorithm is used to perform regression processing on the multi-layer stress measurement data to obtain characteristic parameters that characterize the stress state of each measurement point, and the characteristic parameters of each measurement point are used as quantitative evaluation indicators of the overall stress state of the strip.

[0014] In step S1, the number of detection layers is determined proportionally according to the strip thickness, specifically satisfying the following: no less than 3 detection layers are set in the thickness direction, and the spacing between adjacent layers is not less than 20% of the total strip thickness.

[0015] In step S2, the surface of the strip is pretreated before stress measurement to avoid the influence of iron oxide scale on the measurement results.

[0016] The stress measuring device used in step S2 is a non-destructive testing device such as magnetic or ultrasonic testing, and it is capable of measuring deep stress.

[0017] The expression for calculating the representation value in step S3 is: .

[0018] In step S3, the strip thickness percentage is the thickness percentage of the surface closest to the nearest surface, and the neutral surface thickness percentage is the maximum value.

[0019] In practical applications, the present invention includes the following steps: S1. Determine multiple inspection levels in thickness directions based on the size and grade of the strip steel; S2. Obtain measured stress data at different levels in the thickness direction at each detection point using a stress measuring device; S3. A data regression algorithm is used to perform regression processing on the multi-layer stress measurement data to obtain characteristic parameters that characterize the stress state of each measurement point, and the characteristic parameters of each measurement point are used as quantitative evaluation indicators of the overall stress state of the strip.

[0020] The number of detection layers in step S1 is determined proportionally to the strip thickness, specifically satisfying the following: S1.1 Set no less than 3 detection levels in the thickness direction, with a total number of levels n≥3.

[0021] S1.2 The spacing between adjacent layers shall not be less than 20% of the total thickness of the strip, and the spacing between adjacent layers Δ≥20%h (e.g., Δ≥2mm when h=10mm).

[0022] S1.3 The neutral plane should be a mandatory thickness level.

[0023] Before stress measurement in step S2, the surface of the strip steel should be treated to avoid the influence of iron oxide scale on the measurement results. Sandpaper, grinding wheel or chemical treatment should be used to ensure that there is no iron oxide scale on the surface of the strip steel.

[0024] The stress measurement device used in step S2 should be a non-destructive testing device such as magnetic measurement or ultrasonic measurement, and should be capable of measuring deep stress.

[0025] The calculated representation value in step S3 specifically satisfies: S3.1 Calculate the stress-weighted average value of the measurement points as the stress characterization value of that point, with the measured thickness as the weight. The calculation formula is as follows:

[0026] S3.2 The strip thickness percentage is the percentage of the thickness closest to the surface, and the thickness percentage of the neutral surface is the maximum value. Example

[0027] The purpose of this embodiment is to evaluate and verify the improvement in rolling force prediction accuracy of a certain stand compared to using only adaptive learning as a rolling force correction method. The specific steps included above are as follows: 1. Based on the size and grade of the strip steel, multiple thickness detection levels were determined. The strip steel used in this measurement was hot-rolled 700L strip steel with a product specification of 6*1510mm. The strip steel was measured along the width direction, and a total of 3 thickness measurement levels were set: h1=3mm at the neutral surface, 1mm at the two side surfaces, and h2=h3=1mm.

[0028] 2. Obtain measured stress data at different levels in the thickness direction at each test point using a stress measuring device: The measurement method adopts the magnetic measurement method of non-destructive testing. The testing equipment can set the measurement thickness and measure the stress value at different thicknesses at different measurement points. Before measurement, it is ensured that there is no iron oxide scale on the surface of the strip being measured.

[0029] 3. A data regression algorithm is used to process the multi-layer stress measurement data to obtain characteristic parameters representing the stress state at each measurement point: the weighted average of the measured stress values ​​at each measurement point is calculated based on the thickness ratio. Significant differences exist in the measurement results at different thicknesses. Compared to measuring only the neutral surface stress value, the stress distribution trend obtained using this invention changes less due to the consideration of the influence of different thicknesses, but the peak value is significantly altered. Furthermore, compared to other methods for measuring the surface stress of strip steel, this invention effectively avoids the situation where the stress on the surface differs greatly from that in the strip steel core.

Claims

1. A method for detecting and quantitatively evaluating residual stress stratification in hot-rolled strip steel, characterized in that... Includes the following steps: S1. Determine multiple inspection levels in thickness directions based on the size and grade of the strip steel; S2. Obtain measured stress data at different levels in the thickness direction at each detection point using a stress measurement device; S3. A data regression algorithm is used to perform regression processing on the multi-layer stress measurement data to obtain characteristic parameters that characterize the stress state of each measurement point, and the characteristic parameters of each measurement point are used as quantitative evaluation indicators of the overall stress state of the strip.

2. The method for detecting and quantitatively evaluating residual stress stratification in hot-rolled strip steel according to claim 1, characterized in that: In step S1, the number of detection layers is determined proportionally according to the strip thickness, specifically satisfying the following: no less than 3 detection layers are set in the thickness direction, and the spacing between adjacent layers is not less than 20% of the total strip thickness.

3. The method for detecting and quantitatively evaluating residual stress stratification in hot-rolled strip steel according to claim 1, characterized in that: In step S2, the surface of the strip is pretreated before stress measurement to avoid the influence of iron oxide scale on the measurement results.

4. The method for detecting and quantitatively evaluating residual stress stratification in hot-rolled strip steel according to claim 1, characterized in that: The stress measuring device used in step S2 is a non-destructive testing device such as magnetic or ultrasonic testing, and it is capable of measuring deep stress.

5. The method for detecting and quantitatively evaluating residual stress stratification in hot-rolled strip steel according to claim 1, characterized in that: The expression for calculating the representation value in step S3 is: 。 6. The method for detecting and quantitatively evaluating residual stress stratification in hot-rolled strip steel according to claim 1, characterized in that: In step S3, the strip thickness percentage is the thickness percentage of the surface closest to the nearest surface, and the neutral surface thickness percentage is the maximum value.

Images