Intelligent cleaning system for cold rolling

Abstract

The application discloses an intelligent cleaning system for cold rolling, and belongs to the field of cold-rolled strip steel cleaning. The intelligent cleaning system for cold rolling comprises an inlet section visual acquisition system, a unit, an outlet section visual acquisition system and a picture grading system. The inlet section visual acquisition system and the outlet section visual acquisition system are respectively located at the front and back sides of the unit, and respectively capture surface information before and after strip steel cleaning. According to the movement direction of the strip steel, the processes of the unit in turn include chemical degreasing, first mechanical brushing, electrolytic degreasing, second mechanical brushing, hot water rinsing and hot air drying. The picture grading system acquires information captured by the inlet section visual acquisition system and the outlet section visual acquisition system, and carries out difference processing, and then adjusts the adjustment amount of each process in the unit in turn.

Description

Technical Field

[0001] This invention belongs to the field of cold-rolled strip steel cleaning, and specifically relates to an intelligent cleaning system for cold rolling. Background Technology

[0002] With the continuous development of technology, hot-rolled strips, after pickling to remove surface iron oxide scale, undergo continuous cold rolling to achieve the target thickness before being coiled or processed into sheets for delivery or subsequent processing. The continuous rolling process inevitably leaves a large amount of emulsion and fine iron powder and iron oxide powder irregularly distributed on the strip surface. Since most steel coils require subsequent processing (such as galvanizing), tempering is necessary before post-processing to improve the strip's microstructure and properties. The main equipment for this process is a vertical furnace. Before entering the furnace, a degreasing process must be completed to remove residual oil (mainly emulsion) and residual iron (iron powder or iron oxide particles) from the strip surface. Furthermore, the surface contaminants of the strip steel must be tested before it enters the furnace. If the amount of residual oil and residual iron exceeds the standard, it indicates that the strip steel degreasing is incomplete. During the tempering process, this can lead to black spots on the strip steel surface (incomplete combustion of residual oil) or nodules on the surface of the rollers in the furnace (accumulation of residual iron). The former will affect the coating quality of subsequent hot-dip galvanizing, thus affecting the surface quality of the strip steel; the latter will cause surface scratches (minor) or abrasions (more serious), further affecting the surface quality of the strip steel. Some residual iron entering the zinc pot can also contaminate the zinc liquid composition, deteriorate the process conditions of the zinc pot, cause zinc dross defects, and unnecessary increase in zinc consumption. Therefore, the strip steel degreasing process plays a crucial role in improving the quality of the delivered strip steel.

[0003] The existing degreasing process employs a combination of methods, namely, the sequential application of chemical degreasing, electrolytic degreasing, and mechanical degreasing, which further improves the degreasing effect. ① Chemical degreasing is mainly the result of the combined effects of saponification, chelation, and emulsification, thereby reducing the impact of grease on the subsequent quality of the strip. ② Electrolytic degreasing mainly utilizes the tearing and pulling action of hydrogen and oxygen generated by electrolysis on the oil film and iron powder to achieve the purpose of oil removal. ③ Mechanical brushing mainly uses the mechanical action of brush rollers to forcibly remove contaminants from the surface of the strip. In addition to the above three methods, new process technologies such as ultrasonic degreasing and laser scanning degreasing have been developed, but their implementation on older production lines is not very significant.

[0004] For the existing degreasing process, there are two key issues that have not been effectively resolved: ① online evaluation of strip cleaning quality; ② dynamic adjustment of strip cleaning load.

[0005] For question ①, the main methods used are still visual inspection, wiping, weighing, solution conductivity, and adhesive bonding, as well as the newly emerging reflectivity method. However, most of these methods are limited by the limitations of existing processes and are mainly offline. Since they are post-event evaluations, even if the evaluation is completed, adverse damage has already occurred, making rapid process adjustments impossible. Online methods, on the other hand, are limited in application scenarios due to the excessively high strip speed.

[0006] Regarding question ②, the mechanical brushing of the rollers leads to their periodic wear and tear, chemical degreasing requires a large amount of chemical agents, which is not environmentally friendly, and electrolytic degreasing consumes a large amount of electricity, which is not conducive to energy conservation. Moreover, the three existing sub-processes are all operating at full capacity, lacking the flexibility and adaptability of the manufacturing process. If the surface cleaning quality of the strip steel has already met the process requirements, there is no need to continue high-consumption output (energy consumption, spare parts and chemicals). Summary of the Invention

[0007] To address the shortcomings of existing technologies, the present invention aims to provide an intelligent cleaning system for cold rolling.

[0008] The objective of this invention can be achieved through the following technical solutions:

[0009] A smart cleaning system for cold rolling includes an inlet section visual acquisition system, a mill unit, an outlet section visual acquisition system, and an image grading system; the inlet section visual acquisition system and the outlet section visual acquisition system are located on the front and rear sides of the mill unit, respectively, and capture surface information of the strip steel before and after cleaning.

[0010] According to the direction of strip movement, the unit's processes include: chemical degreasing, first mechanical washing, electrolytic degreasing, second mechanical washing, hot water rinsing, and hot air drying.

[0011] The image grading system collects information captured by the entrance section visual acquisition system and the exit section visual acquisition system, performs differential processing, and then adjusts the adjustment amount of each process in the unit in turn.

[0012] Furthermore, the image grading system includes an acquisition system, a preprocessing system, an expert system, a processing system, and a grading and distribution system. The acquisition system collects information captured by the visual acquisition system at the entrance and exit sections, respectively, and the information is processed by the preprocessing system, the expert system, and the processing system. The information on the surface of the exit strip is then compared with the surface information of the entrance strip, and the grading and distribution system is used to adjust the adjustment amount in each device in the unit.

[0013] Furthermore, both the entrance section visual acquisition system and the exit section visual acquisition system are equipped with dot matrix light sources and CCD systems.

[0014] Furthermore, the first mechanical brushing uses alkaline water to clean the surface of the strip steel, and the second mechanical brushing uses desalinated water to clean the surface of the strip steel.

[0015] Furthermore, the adjustment amounts include: the mass of chemical agents in chemical degreasing, the number and pressure of rollers input in mechanical brushing, and the magnitude of the electrolytic current in electrolytic degreasing.

[0016] Furthermore, the evaluation dimensions for the distribution of residual oil and residual iron in the strip steel include:

[0017] α: Area size of the pollutant;

[0018] β: Distribution of contaminants along the width of the strip;

[0019] γ: The distribution of contaminants along the length of the strip steel, measured in meters.

[0020] Furthermore, the function for classifying and grading strip steel is:

[0021]

[0022] Where w and h are the width and thickness of the strip, respectively, and Q is the energy consumption.

[0023] Furthermore, considering the water temperature change T in the cleaning section and the requirement to maximize the strip speed V, the improved classification function is as follows:

[0024]

[0025] The beneficial effects of the present invention are as follows: The present invention provides an intelligent cleaning system for cold rolling, which can significantly improve the cleaning quality of strip steel, effectively reduce the material and energy consumption of the cleaning section, provide a flexible manufacturing process, and thus achieve the multiple goals of cost reduction, quality improvement and consumption reduction. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 This is a schematic diagram of the overall framework structure of the cleaning system of the present invention. Detailed Implementation

[0028] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0029] like Figure 1 As shown, an intelligent cleaning system for cold rolling includes an inlet section vision acquisition system 1 and an outlet section vision acquisition system 3, which are located at the inlet and outlet of the cleaning system, respectively, and can capture the surface cleaning status of the strip before and after cleaning. In addition, both the inlet section vision acquisition system 1 and the outlet section vision acquisition system 3 are equipped with dot matrix light sources and CCD systems.

[0030] The cleaning system also includes unit 4 and image grading system 2. According to the movement direction of the strip steel, the process of unit 4 includes: chemical degreasing, first mechanical brushing, electrolytic degreasing, second mechanical brushing, hot water rinsing, and hot air drying. Among them, the first mechanical brushing uses alkaline water to clean the surface of the strip steel, and the second mechanical brushing uses desalinated water to clean the surface of the strip steel. Each piece of equipment in unit 4 has an input adjustment function. Chemical degreasing is controlled by the mass M of chemical agent added; mechanical brushing is controlled by the number N and pressure P of rollers added; electrolytic degreasing is controlled by the magnitude I of the electrolytic current applied. The above adjustment values ​​are directly related to the cleaning load.

[0031] The inlet section visual acquisition system 1 is set before chemical degreasing and captures the surface condition of the strip steel before cleaning; the outlet section visual acquisition system 3 is set after hot air drying and captures the surface condition of the strip steel after cleaning.

[0032] The image grading system 2 includes an acquisition system, a preprocessing system, an expert system, a processing system, and a grading and distribution system. The acquisition system collects information captured by the inlet visual acquisition system 1 and the outlet visual acquisition system 3, and the preprocessing system, expert system, and processing system process the information (comparing the outlet strip surface information with the inlet strip surface information) to determine the cleaning quality. The grading and distribution system then adjusts the adjustment amounts in various devices in the unit 4.

[0033] The inlet visual acquisition system 1 and outlet visual acquisition system 3 in the cleaning system employ visible light vision systems or light reflection technology, collecting information based on real-time photographs with a granular acquisition size of 1 meter. The distribution of residual oil and iron in the strip is evaluated in conjunction with the process, and the evaluation dimensions include:

[0034] α: Area size of the pollutant (boundary identification);

[0035] β: Distribution of contaminants along the width of the strip;

[0036] γ: The distribution of contaminants along the length of the strip steel, with particles in meters as the particle size.

[0037] Grading Method 1: The final evaluation method f(α,β,γ) is the grading function. The initial plan for strip steel cleaning is three levels: light contamination, general contamination, and severe contamination (process evaluation). Based on specific field applications, it can be further subdivided into five levels (preferred) to improve adaptability and distinguishability. The three-level system represents 50% cleaning intensity, 70% cleaning intensity, and 100% cleaning intensity, depending on the different cleaning quality levels. Within the three-level system of chemical degreasing (a), electrolytic degreasing (b), and mechanical degreasing (c), further subdivisions can be made based on the removal effects of different subsystems on residual oil and residual iron. For example, residual oil removal mainly relies on chemical and electrolytic degreasing; the removal of residual oil and residual iron compounds relies on mechanical brushing. This allows for a second grading step, using visual identification to determine whether the residue is primarily oil or iron, thereby balancing the different combinations of the three sub-processes: if residual oil is dominant, then mainly adjust ma+nb, supplemented by lc; if residual iron is dominant, then mainly increase the value of lc, supplemented by ma+nb. Where m, n, and l are cleaning intensity coefficients, which can be dynamically adjusted using neural networks to suit different cleaning scenarios.

[0038] Grading Method Two: The strip specifications (width w, thickness h) and energy consumption Q can also be used as constraints. The improved grading function is as follows:

[0039]

[0040] This allows for the classification and grading of cold-rolled products of specific specifications.

[0041] Classification Method 3: Considering the water temperature change T in the cleaning section and the requirement to maximize the strip speed V, the improved classification function is as follows:

[0042]

[0043] This allows for the classification and grading of cold-rolled products of specific specifications.

[0044] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0045] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention.

Claims

1. An intelligent cleaning system for cold rolling, characterized in that, It includes an inlet section visual acquisition system (1), a unit (4), an outlet section visual acquisition system (3), and an image grading system (2); the inlet section visual acquisition system (1) and the outlet section visual acquisition system (3) are located on the front and rear sides of the unit (4), respectively, and capture the surface information of the strip steel before and after cleaning. According to the direction of the strip's movement, the process of unit (4) includes: chemical degreasing, first mechanical brushing, electrolytic degreasing, second mechanical brushing, hot water rinsing and hot air drying. The image grading system (2) collects the information captured by the entrance section visual acquisition system (1) and the exit section visual acquisition system (3), performs differential processing, and then adjusts the adjustment amount of each process in the unit (4) in turn. The image grading system (2) includes an acquisition system, a preprocessing system, an expert system, a processing system, and a grading distribution system. The acquisition system acquires the information captured by the entrance section visual acquisition system (1) and the exit section visual acquisition system (3), and processes it by the preprocessing system, the expert system, and the processing system. The exit strip surface information and the entrance strip surface information are then used to adjust the adjustment amount in each device in the unit (4) through the grading distribution system. Both the entrance section visual acquisition system (1) and the exit section visual acquisition system (3) are equipped with dot matrix light sources and CCD systems; The evaluation dimensions for the distribution of residual oil and residual iron in the strip steel include: α: Area size of the pollutant; β: Distribution of contaminants along the width of the strip; γ: The distribution of contaminants along the length of the strip steel, with particles in meters as the particle size. The function for classifying and grading strip steel is: Where w and h are the width and thickness of the strip, respectively, and Q is the energy consumption.

2. The intelligent cleaning system for cold rolling according to claim 1, characterized in that, The first mechanical scrubbing uses alkaline water to clean the surface of the strip steel, and the second mechanical scrubbing uses desalinated water to clean the surface of the strip steel.

3. The intelligent cleaning system for cold rolling according to claim 1, characterized in that, The adjustment parameters include: the mass of chemical agents in chemical degreasing, the number and pressure of rollers input in mechanical brushing, and the magnitude of the electrolytic current in electrolytic degreasing.

4. The intelligent cleaning system for cold rolling according to claim 1, characterized in that, Considering the water temperature change T in the cleaning section and the requirement to maximize the strip speed V, the improved classification function is as follows:

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