TW202204880A - Method for evaluating roughening macroscopic defect of surface of formed steel material - Google Patents

Abstract

A method for evaluating a roughening macroscopic defect of a surface of a formed steel material is described. In this method, various steel test specimens are obtained. Each of the steel test specimens has a first surface and a second surface, which are opposite to each other, and each of the steel test specimens has a rolling direction. A stretch forming operation is performed on each of the steel test specimens. After the stretch forming operation is completed, a polishing treatment is performed on the first surface of each of the steel test specimens along the rolling direction. The first surface of each of the steel test specimens is visually observed to obtain a macroscopic defection condition of the first surface of each of the steel test specimens. A roughening macroscopic defect evaluation is performed on each of the steel test specimens according to the corresponding macroscopic defection condition.

Description

Evaluation method for roughening macroscopic defects of steel surface after forming

The present disclosure relates to an evaluation technique for steel defects, and in particular, to an evaluation method for roughened macroscopic defects on a steel surface after forming.

In order to meet the diverse needs of automotive product design, the shape design of automotive outer panels has become more and more complex in recent years. The complex shape of the automobile outer panel is prone to surface defects during the stamping process. This surface defect is a phenomenon of surface roughening of the outer panel caused by the large amount of plastic deformation imparted to the panel surface during the stamping process of the outer panel of the automobile.

The surface defects caused by the roughening of the outer plate surface can be divided into elastic distortion, point defects, atomic surface steps, and large crystallographic system steps according to the degree of plastic deformation. slip steps, surface twin or abnormal stress-induced transformation, non-crystallographic glide traces, surface cracks, orange peel phenomenon), individual surface deformations, and ridging and roping phenomena. Macroscopic defects caused by surface roughening are mainly surface streaks or orange peel. Such macroscopic defects can generally only be detected by optical equipment at the end of the final product.

At present, there is a detection technology that adopts punch bulging test, which can detect different surface forming defects with different bulging depths, such as 2mm~30mm. This technology can detect surface forming defects such as slip lines, orange peel, and slag inclusions of cold-rolled steel sheets, as well as problems such as peeling off and powder forming of zinc layers on the surface of galvanized steel sheets.

However, when this technology is used to detect the forming defects of low carbon or medium and high carbon steel, since the stress-strain curve of the material has a yielding elongation platform, after the forming strain exceeds the yielding strength of the material itself, tensile strain marks commonly known as chicken claw marks will begin to appear. . For most products, such as automotive structural parts, the forming strain is greater than the yield strength. This defect is easily confused with slip line and orange peel, making it difficult to identify the defect.

Another technique utilizes optical equipment systems to detect surface defects on steel products. This technology scans the surface of the object with a laser beam. At different scanning rates, the detector receives the signal of the reflected light to obtain different surface slope changes. The optical signal is then converted into a digital signal by a processor. This technology can be used to detect the uniformity and aggregated structure of the flat or curved surface of lacquer products, such as cellulite.

This detection technology requires the purchase and assembly of parts, such as laser light sources, lenses, and electronic control equipment such as counters. In addition, these devices all need to be calibrated during measurement, resulting in a longer detection time. Moreover, this technology is only suitable for detecting coated products such as baking paint, and cannot immediately detect orange peel defects when the finished steel coil is output, and cannot immediately formulate countermeasures for improvement.

Therefore, one object of the present disclosure is to provide a method for evaluating the roughening macroscopic defects on the surface of steel after forming, which can be used to evaluate the steel coil after the steel coil is produced and before the steel sheet is formed and painted. Samples were taken for evaluation of surface roughening macroscopic defects. In this way, the evaluation results of the surface roughening and macroscopic defects of the steel can be immediately fed back to the steel mill, so that the production line can be adjusted and improved in real time, and the flow of defective products to downstream processing plants and assembly plants can be avoided, thereby strengthening the steel. Factory quality control capabilities.

Another object of the present disclosure is to provide an evaluation method for roughening macroscopic defects on the surface of steel after forming, which is simple, fast, and good in applicability.

In accordance with the above purpose of the present disclosure, a method for evaluating the roughening macroscopic defects on the surface of a steel after forming is proposed. In this method, several steel coupons are taken. Each steel test piece has a first surface and a second surface opposite to each other, and each steel test piece has a rolling direction. A stretch forming operation was performed on each steel coupon. After the stretch forming operation, the first surface of each steel test piece was ground in the rolling direction. Visually observe the first surface of each steel test piece to obtain macroscopic defects on the first surface of each steel test piece. According to each macroscopic defect condition, the corresponding steel test piece is evaluated for coarsening macroscopic defects.

According to an embodiment of the present disclosure, the above-mentioned stretch forming operation includes calculating the difference between the center line average roughness (Ra) and the arithmetic mean ripple (arithmetic average) of each steel test piece before and after forming in parallel to the rolling direction. percent ripple, referred to as Wsa) degree difference.

According to an embodiment of the present disclosure, the above-mentioned stretch forming operation includes calculating the thinning rate of each steel test piece.

According to an embodiment of the present disclosure, the above-mentioned stretch forming operation includes measuring the peak count per centimeter (RPc) of the upper surface of each steel test piece after forming in parallel to the rolling direction.

According to an embodiment of the present disclosure, the above-mentioned method further comprises using the centerline average roughness difference, the arithmetic average waviness difference, the thinning rate, and the number of peaks per centimeter of the steel test pieces to establish the difference between different steel grades. Quantitative assessment table for visualizing surface macroscopic defects.

According to an embodiment of the present disclosure, the above-mentioned quantitative evaluation table for visualizing surface macroscopic defects includes that one of the steel test pieces is hot-dip galvanized (GI) extra-deep drawing quality (EDDQ) steel In the case of sheet, after the stretching operation, the average roughness of the center line of the hot-dip galvanized ultra-deep-drawing grade steel sheet is about 0.8μm or less, the arithmetic average waviness is about 0.35μm or less, and the number of peaks per cm is more than 100, And the thinning rate is within about 10%, this steel test piece is evaluated as a slight degree of surface streaks. When the other of these steel test pieces is hot-dip galvanized drawing quality (DQ) steel sheet or hot-dip galvanized deep drawing quality (DDQ) steel sheet, after stretching operation, The average roughness of the center line of the hot-dip galvanized stamping-grade steel sheet or the hot-dip galvanized deep-drawing grade steel sheet is about 1.0 μm or less, the arithmetic average waviness is about 0.35 μm or less, and the number of peaks per cm is more than 80 , and the thinning rate is about 8% to about 12%, and this steel test piece is evaluated as a slight degree of surface streaks.

According to an embodiment of the present disclosure, the above-mentioned grinding treatment includes using oil stone.

According to an embodiment of the present disclosure, each of the above-mentioned steel test pieces is sampled from a steel coil produced by a pan-cold rolling process, and the steel coil is a hot-rolled steel coil, a cold-rolled steel coil, or a continuous hot-dip galvanized steel coil.

According to an embodiment of the present disclosure, the above-mentioned stretch forming operation is a biaxial stretching forming operation.

According to an embodiment of the present disclosure, each of the above-mentioned steel test pieces has a symmetrical shape.

On the surface of parts obtained by stamping, forging, casting, hot rolling, cold rolling, etc., there will be microscopic shape errors formed by crests and troughs with small spacing. Generally speaking, the actual profile of the processed steel surface includes the surface roughness profile, the waviness profile, and the geometrical error formed by the geometrical profile, which are superimposed on the same surface.

According to the definition of the American Society of Mechanical Engineers (ASME), the surface profile characteristics of steel can be composed of geometry, roughness, and waviness. The geometric shape is the lowest frequency of change in the surface morphology, and the wavelength is above 10mm, which is mainly caused by the bending of the steel sheet itself. The roughness is the part with the highest frequency variation in the surface topography, and the wavelength is less than 1mm. The wavelength range of waviness is between geometry and roughness, and the wavelength range is 1mm~10mm.

Since macroscopic defects such as surface streaks or orange peel caused by surface roughening in the prior art can only be detected by optical equipment at the end of the final product, the present disclosure is based on the above-mentioned definition of the surface profile characteristics of steel, here An evaluation method for roughening macroscopic defects on the surface of steel after forming is proposed. In the present disclosure, a punch is used to form a steel sheet, causing stretching and deformation in the plane area of the steel sheet, and a thinning effect in the thickness direction, thereby simulating the large size of the automobile sheet metal, such as the hood panel, the rear luggage compartment cover, and the door outer panel, etc. Flat stretch forming. Different from the conventional punch bulging, the test piece is hemispherical, which causes the linear defects such as slip line, orange peel, and tensile strain mark after forming the test piece to be easily confused with each other, and it is difficult to be close to the practical application level. The present disclosure proposes a method for evaluating the roughened macroscopic defects on the surface of steel after forming. The macroscopic defects on the surface of the test piece after forming correspond to the surface streaks produced by the forming and baking of the steel sheet. Therefore, the evaluation method of the present disclosure is simple and fast, and can be sampled to evaluate the surface roughening macroscopic defects of the steel after the raw material of the steel coil is produced, and can be immediately fed back to the steel mill for process adjustment and improvement. Avoid the flow of substandard products to downstream end products.

The surface defects caused by the stretching and forming of the steel sheet described in the present disclosure belong to the category of macroscopic defects caused by the grain grade, that is, are clearly visible to the naked eye, mainly including surface streaks and orange peel phenomena.

Please refer to FIG. 1 and FIG. 2 , which are a flowchart of a method for evaluating macroscopic defects of roughened steel surface after forming according to an embodiment of the present disclosure, and a schematic top view of a steel test piece, respectively. In this embodiment, step 100 may be performed first to obtain a plurality of steel test pieces 200 . The steel test piece 200 can be sampled from a steel coil produced by the pan-cold rolling process. For example, raw materials are formed into steel billets through steelmaking and continuous casting processes, and after hot rolling, cold rolling, and continuous hot-dip galvanizing and other pan cold rolling processes, hot rolled Dip galvanized steel coil and other pan cold rolled steel coil. The steel test piece 200 is sampled from hot-rolled steel coils, cold-rolled steel coils, or hot-dip galvanized steel coils and other pan-cold-rolled steel coils. These steel coupons 200 may contain steel of the same steel grade and steel of different steel grades. These steel test pieces 200 have a rolling direction. When these steel test pieces 200 are obtained, the serial number of each steel test piece 200 and the rolling direction of each steel test piece 200 can be selectively marked.

In some embodiments, each steel test piece 200 has a symmetrical shape, so that the steel test piece 200 can achieve uniform stretching deformation during the stretching forming process, which is beneficial to identify the surface roughening caused by the stress deformation of the steel test piece 200 itself resulting in surface macroscopic defects. For example, the shape of the steel test piece 200 can be a rectangle, a symmetrical polygon, or a circle.

In some illustrative examples, as shown in FIG. 2 , the steel coupon 200 is a regular octagon. The specification of the steel test piece 200 can be determined according to the size and capability of the punching equipment. The length 200L and the width 200W of the steel test piece 200 may be 185mm, the length of each side may be 60mm, and the thickness of the steel test piece 200 is less than about 3mm.

Next, step 110 may be performed to subject each steel coupon 200 to a stretch forming operation. When the steel test piece 200 is stretched and formed, the steel test piece 200 may be selectively cleaned and dried with, for example, alcohol, so as to avoid impurities such as dust remaining on the steel test piece 200 . In addition, before punching the steel test piece 200, the thickness and surface roughness of the steel test piece 200 are measured. Please refer to FIG. 2 and FIG. 3 at the same time, wherein FIG. 3 is a schematic diagram illustrating the configuration of a steel test piece and a punching apparatus for a stretching operation according to an embodiment of the present disclosure. The steel coupon 200 has a first surface 202 and a second surface 204 opposite to each other. When measuring the thickness and surface roughness of the steel test piece 200, the thickness of the central area 200C of the steel test piece 200 is measured, and the thickness of the first surface 202 of the steel test piece 200 located in the central area 200C is parallel to the rolling direction. The mean roughness of the center line and the arithmetic mean waviness in the parallel rolling direction. When measuring the surface roughness of the steel test piece 200, the number of peaks per cm parallel to the rolling direction of the first surface 202 of the steel test piece 200 located in the central area 200C can also be selectively measured, that is, the number of peaks per cm of length. The number of crests and troughs of the first surface 202 . In some exemplary examples, when measuring the roughness of the first surface 202 of the steel test piece 200, the measurement rate can be controlled at about 0.5 mm/s, and the cut-off length λc is about 0.8 mm. The length is about 25mm.

The macroscopic defects caused by the surface roughening of the steels described in the present disclosure are surface streaks or orange peels. Since the wavelength range of the surface streak or orange peel phenomenon is 0.1 mm to 5 mm, the embodiment of the present disclosure uses the average roughness of the center line and the arithmetic average waviness as evaluation indicators. In addition, since the steel plate is in the process of baking paint, the higher number of peaks per cm helps to accumulate more paint on the surface of the steel coil, which makes the paint flow more easily during the painting process, so that a smoother surface appearance can be obtained. , to improve the sharpness of image, so the number of peaks per cm can also be used as one of the indicators of the surface macroscopic defect of the steel sheet evaluated in this disclosure.

Please continue to refer to FIG. 3 , the punching equipment 300 mainly includes an extension ring 310 , a pressing plate 320 , and a punch 330 . For example, the punch 330 can be cylindrical, wherein the diameter of the punch 330 can be 100mm, the diameter of the plane where the punch 330 contacts the second surface 204 of the steel test piece 200 can be 75mm, and the radius of the fillet of the punch 330 Can be 10mm. During the stretch forming operation, the extension ring 310 can be set inside the machine, then the steel test piece 200 is placed on the extension ring 310, and then the pressing plate 320 is placed on the steel test piece 200. A clamping force is applied to the plate 320 to hold the steel coupon 200 on the extension ring 310 . In some demonstrative examples, the clamping force exerted on the blanking plate 320 may be about 200KN to about 300KN.

After the steel test piece 200 is clamped and fixed, the stretching operation of the steel test piece 200 can be started. The punch 330 punches the steel test piece 200 from bottom to top along the direction PD, so as to stretch and form the steel test piece 200 . Thus, it is the second surface 204 of the steel coupon 200 that is in contact with the punch 330 . In some illustrative examples, punch 330 forms steel coupon 200 from bottom to top at a speed of 0.8 mm/s. In addition, different stroke depths can be set during the stretch forming operation to achieve the desired thinning rate of the steel sheet. For example, the required stroke depth can be pushed back according to the thinning rate of different automobile outer panels after forming, so as to conform to the actual product forming amount.

In some examples, this stretch forming operation is a biaxial stretch forming operation. During the stamping process, the clamping force in all directions of the steel test piece 200 needs to be the same, so that the steel test piece 200 can bear uniform plane strain during the forming process. In this way, surface macroscopic defects caused by other non-steel test pieces 200 caused by irregular stress can be avoided.

As shown in FIG. 3 , after the steel test piece 200 is punched and formed by the punch 330 , the plane area 206 of the steel test piece 200 is the region where plastic deformation occurs. After the steel test piece 200 is formed, the surface roughness of the first surface 202 of the steel test piece 200 in the plane region 206 is measured. Similarly, when measuring the surface roughness, the average roughness of the center line parallel to the rolling direction and the arithmetic mean waviness parallel to the rolling direction of the first surface 202 of the flat area 206 of the steel test piece 200 are measured. In addition, the number of peaks per cm parallel to the rolling direction of the first surface 202 of the steel test piece 200 in the flat area 206 can also be selectively measured. In some exemplary examples, when measuring the roughness of the first surface 202 of the steel test piece 200 after forming, the measuring rate can be controlled at about 0.5 mm/s, the cut-off value λc is about 0.8 mm, and the measuring length is about 25 mm .

After the measurement, the difference between the average roughness of the center line and the difference in arithmetic average waviness of the first surface 202 of each steel test piece 200 before and after forming in parallel to the rolling direction can be calculated. The difference between the average roughness of the center line is obtained by subtracting the average roughness of the center line after forming by the average roughness of the center line before forming. The arithmetic mean waviness difference is calculated by subtracting the arithmetic mean waviness after forming from the arithmetic mean waviness before forming.

In some examples, after the steel coupon 200 is formed, the thickness of the planar region 206 of the steel coupon 200 is measured. And, using the thickness of the central area 200C of the steel test piece 200 before forming and the thickness of the flat area 206 of the steel test piece 200 after forming, the thickness reduction rate of the steel test piece 200 during the stretch forming operation is calculated.

As shown in FIG. 1 , after the stretch forming operation, step 120 may be performed to grind the first surface 202 of each steel test piece 200 along the rolling direction. Since the surface stripes or orange peel phenomenon caused by surface roughening on the first surface 202 of the steel test piece 200 are not easy to be observed with the naked eye, and the surface stripes are perpendicular to the rolling direction of the steel test piece 200, the formed steel test piece 200 is not easy to be observed. The first surface of the sheet 200 in the planar region 202 is ground in the rolling direction. In this way, the height difference of the surface stripes generated on the first surface 202 after the steel test piece 200 is formed can be highlighted, which is beneficial for evaluating the surface stripes and the orange peel phenomenon. If the grinding direction is perpendicular to the rolling direction of the steel test piece 200 , the surface stripe defects of the steel test piece 200 cannot be revealed. In some illustrative examples, the grinding process may be performed by using a whetstone to grind back and forth along the rolling direction of the parallel steel coupons 200 . Since the whetstone is a non-flexible block, it can be avoided to remove the surface stripes on the steel test piece 200 during the grinding process. The surface defects of the first surface 202 of the steel test piece 200 after being ground by the whetstone have no mesoscopic or microscopic defects such as slip lines and tensile strain marks, and therefore are not easily confused with other defects.

After grinding, step 130 may be performed to visually observe the first surface 202 of each steel test piece 200 to obtain macroscopic defects on the first surface 202 of each steel test piece 200 .

In some examples, step 140 may be performed next to evaluate the roughened macroscopic defects on the corresponding steel test pieces according to the macroscopic defects obtained by visual observation. In this way, it can be confirmed whether the steel coils sampled by the steel test pieces 200 have surface streaks or orange peel after stretching and forming, and can be immediately fed back to the production line for process adjustment and improvement, thereby avoiding the flow of unqualified products to the downstream end products.

In other examples, the arithmetic mean waviness difference between the centerline average roughness difference before and after forming of the first surface 202 of the steel test pieces 200 parallel to the rolling direction can be used to compare the surface macroscopic defects after different forming. To identify surface streaks and orange peel phenomena on the first surface 202 of the steel test piece 200 . In still other examples, the number of peaks per cm and/or the thinning rate of the first surface 202 of the steel test pieces 200 can be further used to evaluate the roughened macroscopic defects on the surface of the steel test pieces 202 after forming.

In some examples, the difference in centerline mean roughness, the arithmetic mean waviness difference, the number of peaks per cm, and the thinning rate of the first surface 202 of the steel coupons 202 can be used to establish the difference Quantitative evaluation table for visual surface macroscopic defects of steel grades.

The evaluation method of the present disclosure can be applied to the evaluation of surface macroscopic defects of continuous annealed, box annealed, hot-dip galvanized, electro-galvanized and other stamping grades, electro-galvanized deep-drawing grades, and electro-galvanized ultra-deep-drawing grades.

The inventor speculates that there may be the following three main reasons for the surface streak or orange peel phenomenon on the steel surface during forming. One of the reasons is the uneven grain size of steel, that is, mixed grains. In such a case, when the steel is deformed, the deformation gap between the inside of the fine grain and the vicinity of the grain boundary is small, while the deformation gap between the inside of the coarse grain and the vicinity of the grain boundary is large. Due to the difficulty of coordination between large and small grains during the deformation process, the grains are deformed unevenly, resulting in uneven surface stripes or orange peel defects.

Another reason is that the grain size of the steel is too large, resulting in reduced impact toughness, so surface streaks or orange peel defects are prone to occur during stamping. Another possible reason is that the tempering rolling of the steel is insufficient. The main purpose of quenching and tempering rolling is to eliminate the yielding platform and make the steel produce uniform and continuous deformation in all directions. When the quenching and tempering reduction ratio is too small, the pre-deformation of the steel material is insufficient, so that surface streaks or orange peel defects are likely to occur during stamping.

The following is the evaluation of macroscopic surface defects of five hot-dip galvanized pure zinc ultra-deep-drawing grade steel sheets with different grain sizes. The grain size of the steel sheets adopts the E112 standard set by the American Society for Testing and Materials (ASTM). For calculation, the stroke is set to 13mm. The pre-forming parameters, the post-forming parameters, and the degree of surface striation of the post-forming steel sheets are listed in Table 1 below. Table 1 project grain size Parameters before forming Parameters after forming degree of streak Ra (μm) Wsa (μm) RPc Thinning rate (%) Ra (μm) Wsa (μm) RPc example 1 7.5 0.771 0.17 165.2 10.11 0.913 0.597 106.4 severe Example 2 8 0.672 0.139 107.6 9.52 0.801 0.482 88 medium Example 3 8.5 0.548 0.11 126 10.09 0.67 0.371 109.6 medium Example 4 9 0.598 0.082 144 9.80 0.664 0.321 119.6 slight Example 5 9.5 0.573 0.091 142.4 10.50 0.629 0.275 114.4 slight

Please refer to FIG. 4 , which is a graph showing the relationship between the grain size of five hot-dip galvanized pure zinc ultra-deep-drawing grade steel sheets and the difference between the average roughness of the center line and the difference in arithmetic average waviness after stretching. picture. According to Fig. 4, as the grain size of the steel sheet increases, that is, the grain size decreases, the difference between the average roughness of the center line and the arithmetic average waviness before and after forming of the steel sheet is smaller. Moreover, the surface streaks produced by the forming of these steel sheets were visually observed, and the grain size of the steel sheets increased, and the degree of surface streaks was slighter.

It can be seen from Figure 4 that when the grain size of the steel sheet is 7.5~8.5, the average roughness difference of the center line is 0.122μm~0.142μm, and the arithmetic average waviness difference is 0.261μm~0.427μm. The resulting surface streaks are severe. When the grain size of the steel sheet is 9, the average roughness difference of the center line is 0.066 μm, and the arithmetic average waviness difference is 0.239 μm. Visual observation of the steel surface stripes is slight, and the stripes are widely spaced. When the grain size of the steel sheet is 9.5, the average roughness difference of the center line is 0.056 μm, and the arithmetic average waviness difference is 0.184 μm. Visual observation of the steel surface stripes is also slight, and the spacing of the stripes is also wider. . Therefore, the roughness difference can represent the degree of deformation of the internal grains of the material. The smaller the roughness difference is, the smaller the grain deformation is, and the less undulating the surface morphology of the steel is.

With the evaluation method provided in the present disclosure, it can be proved that the surface streaks of the hot-dip galvanized ultra-deep-drawing grade steel are mainly caused by excessive grain size. In addition, the hot-dip zinc ultra-deep-drawing grade steel with a grain size of 9.0 was stamped into the trunk rear cover at the depot and painted, and no surface streaks or orange peel defects were found.

The following is the evaluation of macroscopic defects on the surface of ten kinds of hot-dip galvanized pure zinc ultra-deep-drawing grade steel sheets with different stretching and forming strokes. Eight hot-dip galvanized pure zinc ultra-deep-drawing grade steel sheets with a grain size of 7.5, a grain size of 8, and a grain size of 8.5 were stretched with different stroke amounts, and the surface of these steel sheets after forming was observed. The degree of macroscopic defects. The pre-forming and post-forming parameters of these steel sheets are listed in Table 2 below. Table 2 project Stroke(mm) grain size Before forming Thinning rate (%) after forming Ra (μm) Wsa (μm) RPc Ra (μm) Wsa (μm) RPc Example 6 2 7.5 0.687 0.083 152 0.93 0.688 0.163 153.6 Example 7 4 7.5 0.672 0.1 148 1.42 0.721 0.117 156 Example 8 6 7.5 0.667 0.12 136.8 3.1 0.702 0.162 141.2 Example 9 8 7.5 0.689 0.09 146.8 4.66 0.736 0.177 144 Example 10 10 7.5 0.664 0.124 154.8 7.73 0.71 0.245 136.8 Example 11 15 7.5 0.715 0.151 153.2 11.71 0.84 0.376 118.4 Example 12 18 7.5 0.679 0.097 144.4 14.93 1.072 0.355 102 Example 13 20 7.5 0.733 0.147 154.8 21.12 1.181 0.636 91.2 Example 14 25 8 0.663 0.091 149.2 35.65 1.725 0.984 85.2 Example 15 30 8.5 0.636 0.092 150 48.11 2.65 1.933 70.8

The surface macroscopic defects of these formed steel sheets were visually observed. The steel sheets of Example 6 had no surface macroscopic defects, the steel sheets of Examples 7 and 8 had slight surface streaks, and the steel sheets of Examples 9 to 11 had medium surface striations. , The steel sheets of Example 12 and Example 13 are severe surface streaks, and the steel sheets of Examples 14 and 15 are irregular orange peels.

From the evaluation results, it can be seen that when the stroke depth is less than 5mm, that is, when the thickness reduction rate is less than 2%, the steel sheet has no surface macroscopic defects, and the average roughness and arithmetic mean waviness of the center line of the steel sheet after forming are respectively 1.0. μm and below 0.15μm, the number of peaks per cm is more than 100. When the stroke is 6mm, that is, the thickness reduction rate is 3.1%, slight surface streaks begin to appear. The average roughness of the center line, the arithmetic average waviness, and the number of peaks per cm are 0.702μm after forming. , 0.162 μm, and 141.2.

When the stroke depth is continuously increased from 8mm to 20mm, that is, when the thickness reduction rate is 4.66%~21.12%, with the increase of the stroke amount, the surface stripes of the steel sheet become more serious. The average roughness of the center line of the steel sheet after forming is 0.736μm~1.072μm, the arithmetic average waviness is 0.177μm~0.355μm, and the number of peaks per cm is more than 100. In addition, the surface streak degree of the ultra-deep-drawing grade steel sheet after forming with a stroke of 15 mm is the same as that of Example 3, which is a medium degree. When the forming stroke of the steel sheet is less than 15mm, that is, when the thickness reduction rate is less than 11.71%, the surface stripe defects of the steel can be covered in the subsequent steel painting process.

When the forming stroke depth of the steel sheet was increased to 25mm (thickness reduction rate of 35.65%) and 30mm (thickness reduction rate of 48.11%), the surface stripes of the steel sheet turned into irregular orange peel defects. At this time, the average roughness of the center line of the steel sheets with the two forming stroke depths was 1.725 μm and 2.65 μm, respectively, and the arithmetic average waviness was 0.984 μm and 1.933 μm, respectively.

According to the evaluation results of the above examples, it can be concluded that the average roughness of the center line and the arithmetic average waviness of the hot-dip galvanized ultra-deep-drawing steel sheet after stretching are respectively 0.8 μm or less and 0.35 μm or less, and the peak value per cm When the number of pieces is more than 100, and the thinning rate of the stretch forming thickness of the steel sheet is controlled within 10%, the surface stripe defects can be covered after coating.

Please refer to FIG. 5 , which shows the relationship curve between the average roughness difference of the center line and the arithmetic average waviness difference of ten hot-dip galvanized ultra-deep-drawing grade steel sheets before and after stretching and forming with different forming thinning rates picture. When the forming thinning rate of the steel sheet is 0.93% (that is, the stroke depth is 2 mm), the difference between the average roughness of the center line and the difference between the arithmetic average waviness are 0.001 μm and 0.08 μm respectively, and there is no surface macroscopic defect on the surface of the steel sheet. produce. When the forming thinning rate of the steel sheet is 1.42%~3.1% (the stroke depth is 4mm~6mm), the average roughness difference of the center line is 0.05μm or less, and the arithmetic average waviness difference is 0.017μm~0.042μm, and The macroscopic defects on the surface of the steel sheet are slightly streaked.

When the forming thinning rate of the steel sheet is 4.46%~11.71% (the stroke depth is 8mm~15mm), the average roughness difference of the center line is 0.046μm~0.125μm, and the arithmetic average waviness difference is 0.087μm~0.225μm. The surface macroscopic defects of the film are medium streaks. This level of surface streaks is similar to Example 3, which is moderate. When the forming stroke is less than 15mm (thickness reduction rate is 11.71%), the surface streak defects of the steel sheet can be covered in the subsequent steel painting process.

When the forming thinning rate of the steel sheet is 14.93%~21.12% (the stroke depth is 18mm~20mm), the average roughness difference of the center line is 0.393μm~0.448μm, and the arithmetic average waviness difference is 0.258μm~0.489μm. The macroscopic defects on the surface of the steel sheet have been severely streaked. When the forming thinning rate of the steel sheet is increased to 35.65%~48.11% (the stroke depth is 25mm~30mm), the average roughness difference of the center line is 1.062μm~2.014μm, and the arithmetic average waviness difference is 0.893μm~0.1. 841μm, the surface macroscopic defects of the steel sheet are irregular orange peel appearance.

In addition, according to the evaluation method for surface macroscopic defects of the present disclosure, it can be known that after the hot-dip galvanized ultra-deep-drawing steel sheet is stretched and formed with different stroke depths, different types of surface macroscopic defects will be generated. When the surface macroscopic defects of the steel sheet are surface stripes, the aggregate structure is mainly {111}<011>. As the forming amount of the steel sheet is larger, the strength of {111}<011> is higher, and the defect degree of the surface stripes is more serious. When the surface macroscopic defect of the steel sheet is irregular orange peel, the aggregate structure is mainly {111}<112>.

The following applies the surface macroscopic defect evaluation method of the present disclosure to evaluate hot-dip galvanized steel sheets of stamping (DQ) grade and deep-drawing (DDQ) grade. After the hot-dip galvanized steel sheet is formed with a stroke depth of 13 mm, the stretched deformation platform area of the steel sheet is ground with a whetstone, and the surface stripe appearance of the steel sheet is obtained by visual observation. The surface roughness parameters of the steel sheet before and after forming are listed in Table 3 below. table 3 project Type of steel grain size Parameters before forming Parameters after forming Ra (μm) Wsa (μm) RPc Thinning rate (%) Ra (μm) Wsa (μm) RPc Example 16 DQ 9 0.7 0.087 153.6 8.13 0.724 0.303 118 Example 17 DQ 10 0.577 0.093 144.4 8.25 0.595 0.178 120.4 Example 18 DDQ 8 0.563 0.093 89.6 8.29 0.718 0.307 88.8 Example 19 DDQ 8.5 0.725 0.113 147.2 11.99 0.872 0.337 128

The surface macroscopic defects of the formed steel sheets were visually observed, and the surface macroscopic defects of the formed steel sheets of Examples 16 to 19 were all slight surface streaks. The surface stripes produced by the forming of hot-dip galvanized steel sheets of stamping grade and deep-drawing grade are slightly wider and slightly wider. The subsequent coating process can cover the surface stripe defects of the steel sheet.

After the hot-dip galvanized steel sheet of stamping grade and deep-drawing grade is stretched and formed, the average roughness of the center line is below 1.0µm, the arithmetic average waviness is below 0.35µm, and the number of peaks per cm is above 80. In addition, after the hot-dip galvanized steel sheet of stamping grade and deep-drawing grade is stretched and formed, the average roughness difference of the center line is 0.018µm~0.155µm, and the arithmetic average waviness difference is 0.085µm~0.224µm.

In some demonstrative examples, the quantitative evaluation table for visualizing macroscopic surface defects of different steel grades established based on the above evaluation results may include a steel test piece that is a hot-dip galvanized ultra-deep-drawing grade steel sheet that has undergone a stretch forming operation. After that, when the average roughness of the center line of the hot-dip galvanized ultra-deep-drawing grade steel sheet is less than 0.8 μm, the arithmetic mean waviness is less than 0.35 μm, the number of peaks per cm is more than 100, and the thinning rate is less than 10%, This steel test piece was evaluated as a slight degree of surface striation. The quantitative evaluation table for visualizing macroscopic defects on the surface may also include a steel test piece that is hot-dip galvanized stamping grade steel or hot-dip galvanized deep-drawing grade steel, after the stretching operation, hot-dip galvanized pure steel The average roughness of the center line of the stamping grade steel sheet or the hot-dip galvanized deep drawing grade steel sheet is less than 1.0μm, the arithmetic mean waviness is less than 0.35μm, the number of peaks per cm is more than 80, and the reduction rate is 8% At ~12%, this steel test piece was evaluated as slightly surface streaked.

It can be seen from the above-mentioned embodiments that one of the advantages of the present disclosure is that the method for evaluating the roughening macroscopic defects of the steel surface after forming in the present disclosure is after the steel coil is produced, and before the steel sheet forming processing and coating baking paint, that is, Coils can be sampled for evaluation of surface roughening macroscopic defects. Therefore, the evaluation results of the surface roughening and macroscopic defects of the steel can be immediately fed back to the steel mill, so that the production line can be adjusted and improved in real time, and the flow of defective products to downstream processing plants and assembly plants can be avoided, thereby strengthening the steel mill. quality control capability.

As can be seen from the above embodiments, another advantage of the present disclosure is that the method for evaluating the roughened macroscopic defects on the surface of the steel after the present disclosure is simple, fast in evaluation speed, and good in applicability.

Although the present disclosure has been disclosed above with examples, it is not intended to limit the present disclosure. Anyone with ordinary knowledge in this technical field can make various changes and modifications without departing from the spirit and scope of the present disclosure. Therefore, the scope of protection of this disclosure should be determined by the scope of the appended patent application.

100: Steps 110: Steps 120: Steps 130: Steps 140: Steps 200: Steel test piece 200C: Central District 200L: length 200W: width 202: First Surface 204: Second Surface 206: Flat area 300: Stamping equipment 310: Extension Ring 320: Binder plate 330: Punch PD: direction

In order to make the above and other objects, features, advantages and embodiments of the present disclosure more clearly understood, the accompanying drawings are described as follows: [ FIG. 1 ] is a flowchart illustrating a method for evaluating the roughened macroscopic defects on the surface of a steel after forming according to an embodiment of the present disclosure; [ FIG. 2 ] is a schematic top view of a steel test piece according to an embodiment of the present disclosure; [ Fig. 3 ] is a schematic diagram showing the configuration of a steel test piece and a punching device for a stretching operation according to an embodiment of the present disclosure; [Fig. 4] is a graph showing the relationship between the grain size of five hot-dip galvanized pure zinc ultra-deep-drawing grade steel sheets and the difference between the average roughness of the center line and the difference in arithmetic average waviness after stretching; as well as [Fig. 5] is a graph showing the relationship between the average roughness difference of the center line and the arithmetic average waviness difference of ten hot-dip galvanized ultra-deep-drawing steel sheets before and after stretching at different forming reduction rates.

Domestic storage information (please note in the order of storage institution, date and number) without Foreign deposit information (please note in the order of deposit country, institution, date and number) without

100: Steps

110: Steps

120: Steps

130: Steps

140: Steps

Claims (10)

A method for evaluating the roughening macroscopic defects of the steel surface after forming, comprising: Obtaining a plurality of steel test pieces, wherein each of the steel test pieces has a first surface and a second surface opposite to each other, and each of the steel test pieces has a rolling direction; performing a stretch forming operation on each of the steel coupons; performing a grinding process along the rolling direction on the first surface of each of the steel test pieces after the stretch forming operation; Visually observe the first surface of each of the steel test pieces to obtain a macroscopic defect condition of the first surface of each of the steel test pieces; and According to each of the macroscopic defects, a coarse macroscopic defect evaluation is performed on the corresponding steel test piece. The method of claim 1, wherein performing the stretch forming operation comprises calculating a centerline mean roughness difference and an arithmetic mean waviness difference before and after forming each of the steel test pieces parallel to the rolling direction. The method of claim 2, wherein performing the stretch forming operation includes calculating a reduction ratio for each of the steel coupons. The method of claim 3, wherein performing the stretch forming operation comprises measuring the number of peaks per cm on the upper surface of each of the steel test pieces after forming parallel to the rolling direction. The method of claim 4, further comprising using the centerline average roughness differences, the arithmetic average waviness differences, the thinning rates, and the peak values per centimeter of the steel test pieces A quantitative evaluation table for visualizing surface macroscopic defects of one of the different steel grades is established. The method of claim 5, wherein the quantitative assessment table for visualizing surface macroscopic defects comprises: When one of the steel test pieces is a hot-dip galvanized ultra-deep-drawing-grade steel sheet, the average roughness of the centerline of the hot-dip galvanized ultra-deep-drawing-grade steel sheet after the stretching operation is 0.8 μm Below, the arithmetic mean waviness is less than 0.35μm, the number of peaks per cm is more than 100, and the reduction rate is less than 10%, the steel test pieces are evaluated as slight surface streaks; and When the other of the steel test pieces is a hot-dip galvanized stamping grade steel sheet or a hot-dip galvanized pure galvanized deep-drawing grade steel sheet, after the stretching operation, the hot-dip galvanized stamping-grade steel The average roughness of the center line of the sheet or the hot-dip galvanized deep-drawing grade steel sheet is less than 1.0μm, the arithmetic mean waviness is less than 0.35μm, the number of peaks per cm is more than 80, and the reduction rate is 8%~ 12%, the other of the steel coupons was evaluated to have a slight degree of surface striation. The method of claim 1, wherein performing the grinding process comprises utilizing a whetstone. The method of claim 1, wherein each of the steel coupons is sampled from a steel coil produced by a pan-cold rolling process, the steel coil being a hot-rolled steel coil, a cold-rolled steel coil, or a continuous hot-rolled steel coil Dip galvanized steel coil. The method of claim 1 wherein the stretch forming operation is a biaxial stretch forming operation. The method of claim 1, wherein each of the steel coupons has a symmetrical topography.

Images