A method and detection device for identifying zinc dross patterns in hot-dip galvanizing units

Abstract

This invention discloses a method for identifying zinc slag patterns in hot-dip galvanizing units, belonging to the field of zinc slag identification technology. The method includes the following steps: acquiring aluminum and iron content data of slag within the zinc bath area based on a data platform; defining several variables, substituting the aluminum and iron content data into these variables, calculating their real-time values, and determining the state of the zinc slag based on these values ​​to identify the zinc slag pattern, thereby providing guidance for production. This invention also discloses a zinc slag detection device for hot-dip galvanizing units. This method and device achieve low error in zinc slag pattern identification, providing a basis for on-site workers to monitor the current zinc bath production status in real time. It is of great significance for guiding adjustments to zinc addition and zinc slag cleaning, and can provide important guidance for improving the quality of strip steel production.

Description

Technical Field

[0001] This invention relates to the field of zinc slag identification technology, and more specifically, to a method and detection device for identifying zinc slag patterns in hot-dip galvanizing units. Background Technology

[0002] Zinc dross refers to Fe-Zn, Fe-Al, or Fe-Zn-Al intermetallic compounds formed by iron and zinc, or aluminum dissolved in molten zinc, under high-temperature conditions. The formation of zinc dross in molten zinc is unavoidable. The causes and types of zinc dross vary depending on the molten zinc system. Based on their state in the molten zinc, zinc dross can be classified into three categories: surface dross, bottom dross, and suspended dross. Surface dross: Surface dross is mainly composed of Fe₂Al₅, with a density of approximately 4.2 g / cm³. 3 The density of the zinc slag is less than that of the molten zinc, so it easily floats on the surface of the molten zinc. Zinc can also dissolve in this binary compound. Therefore, the actual composition of the surface slag is a ternary metal compound of Fe₂Al₅Znx. The surface slag generally appears as rounded, angular, granular polygons, approximately 40-100 μm in size. The bottom slag, in molten zinc with a lower aluminum content, is usually a Zn-Fe compound formed by the interaction of zinc and iron dissolved in the molten zinc, mainly FeZn₇ and FeZn₁₃, with a small amount of dissolved aluminum. According to on-site engineers, the bottom slag composition is 6-9 wt% Fe, 87-91 wt% Zn, and 2-4 wt% Al. The bottom slag is approximately 80-400 μm in size and slightly denser than the molten zinc. Therefore, if the molten zinc is not stirred, the bottom slag will slowly sink to the bottom of the zinc pot, accumulating and adhering to the bottom, making it difficult to remove. In the actual continuous hot-dip galvanizing process, when the hot-dip galvanizing bath transitions from an alloyed state to pure zinc, the bottom slag at the bottom of the zinc bath reacts chemically with the added Al to form surface slag. Therefore, it is necessary to understand the transformation law of the slag and control the coating structure of hot-dip galvanized steel and alloy hot-dip galvanized steel. Suspended slag: The size of suspended slag is approximately 10-40 μm, and its density is between that of surface slag and bottom slag. It consists of zinc slag suspended in the zinc bath. The probability of the strip steel carrying different types of zinc slag out of the zinc pot varies slightly.

[0003] Hot-dip galvanized steel sheets are increasingly favored by the market due to their excellent corrosion resistance, machinability, and lower cost, and are gradually replacing electro-galvanized and cold-rolled sheets in the application of automotive exterior panels and appliance panels. Therefore, higher requirements are placed on the surface quality of hot-dip galvanized steel sheets. Due to the influence of the hot-dip galvanizing production process, zinc dross has become one of the main defects affecting the surface quality of hot-dip galvanized products. Besides harming the quality of hot-dip galvanized steel sheets, zinc dross also accumulates at the bottom of the zinc pot, insulating heat, making it difficult for the zinc liquid to heat up, and increasing fuel consumption. Therefore, timely understanding of the current state of zinc dross and timely removal of zinc dross is of great significance for the high-quality production of strip steel.

[0004] In existing technologies, electrochemical detection methods are commonly used to determine the aluminum and iron content in zinc bath components. While this method can determine the aluminum and iron content in zinc bath components, it has a large error in identifying zinc slag, poor accuracy, and cannot define the current state of zinc slag. It cannot determine the current zinc slag pattern, cannot use zinc slag to judge the current production status, and cannot make targeted adjustments to the type of zinc added or zinc slag cleaning. Summary of the Invention

[0005] The purpose of this invention is to provide a method and device for identifying zinc slag patterns in hot-dip galvanizing units. The zinc slag detection device in hot-dip galvanizing units can detect the aluminum and iron content of slag in the zinc bath. At the same time, the zinc slag pattern identification method in hot-dip galvanizing units can not only realize the real-time detection of zinc bath composition, but also directly analyze the content of effective aluminum, free iron and various components of zinc slag in the sample, which greatly improves the shortcomings of previous electrochemical detection methods.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] According to one aspect of the present invention, a method for identifying zinc dross patterns in a hot-dip galvanizing unit is provided, comprising the following steps:

[0008] S1. Based on the data platform, obtain data on slag aluminum content and slag iron content in the zinc pot area;

[0009] S2. Define several variables, substitute the data in S1 into the variables, and calculate the real-time value of the variables;

[0010] S3. Determine the state of zinc slag based on the real-time values ​​of variables, identify the zinc slag pattern, and thus provide guidance for production.

[0011] According to the above-mentioned aspects of the present invention, a zinc dross pattern recognition method for hot-dip galvanizing units, wherein the data platform in S1 includes two parts, namely a steel coil data center and a zinc bath status online analysis system.

[0012] According to the above-mentioned aspects of the present invention, a method for identifying zinc dross patterns in a hot-dip galvanizing unit, wherein S1 includes the following steps:

[0013] S11. The online zinc bath status analysis system acquires data on the aluminum and iron content of slag in the zinc bath area and the working status of the zinc pot, and sends the above data to the server of the steel coil data center.

[0014] S12. The steel coil data center collects and stores steel coil production data during strip steel production on the server, and receives data sent by the zinc bath condition online analysis system;

[0015] S13. The online zinc bath status analysis system communicates with the steel coil data center to obtain real-time steel coil production data. At the same time, it integrates and further calculates and analyzes the steel coil production data and the data in the zinc bath area, and displays it visually through the front-end page.

[0016] According to the above-mentioned aspects of the present invention, a zinc dross pattern recognition method for hot-dip galvanizing units, wherein S2 specifically includes the following steps:

[0017] S21. Define two variables: zinc slag mold and zinc slag angle;

[0018] S22. Based on the aluminum and iron content of the slag in the current zinc bath area, substitute them into the zinc slag mold and zinc slag angle respectively to calculate and obtain the calculated values ​​of the zinc slag mold and zinc slag angle.

[0019] According to the above-mentioned aspects of the present invention, a method for identifying zinc dross patterns in a hot-dip galvanizing unit, wherein the calculation formula for the zinc dross pattern in S21 is as follows:

[0020]

[0021] The formula for calculating the argument θ of zinc slag is as follows:

[0022]

[0023] According to the above-mentioned aspects of the present invention, a method for identifying zinc dross patterns in a hot-dip galvanizing unit, wherein S3 specifically includes the following steps:

[0024] S31. Based on historical production records, define the limit values ​​for the zinc slag mold and the zinc slag angle;

[0025] S32. Based on the limit values ​​of the zinc dross mold and the zinc dross angle, the zinc dross pattern is defined as four patterns;

[0026] S33. Based on the real values ​​of the variables, perform pattern recognition on the content and composition of zinc slag to determine the state of zinc slag, thereby providing guidance for production.

[0027] According to the above-mentioned aspects of the present invention, a method for identifying zinc dross patterns in a hot-dip galvanizing unit, wherein the four patterns of zinc dross in S32 are as follows:

[0028] Pattern 1: dross < 0.02, 45℃ < θ < 90℃, indicating less suspended slag in the zinc pot and a tendency towards surface slag;

[0029] Pattern 2: dross < 0.02, θ < 45℃, indicating less suspended dross in the zinc pot and a tendency towards bottom dross;

[0030] Pattern 3: 0.02 < dross < 0.04, 45°C < θ < 90°C, indicating that there is more suspended dross in the zinc pot, tending to surface dross;

[0031] Pattern 3: 0.02 < dross < 0.04, θ < 45°C, indicating that there is more suspended dross in the zinc pot, tending to bottom dross.

[0032] According to another aspect of the present invention, there is provided a zinc dross detection device for a hot-dip galvanizing line, comprising:

[0033] A Galvalibs detection probe, which is communicatively connected to the upper computer device in the PLC control cabinet through a cable, shoots a laser beam into the zinc bath, obtains the content and existence state of each chemical element in the zinc bath, then amplifies and filters the signal, and transmits it to the upper computer device through the cable; and / or

[0034] A feeding mechanism, which is mechanically connected to the Galvalibs detection probe, controls the up and down movement and left and right movement of the Galvalibs detection probe; and / or

[0035] A PLC control cabinet, which is electrically connected to the feeding mechanism, controls the operation of the feeding mechanism, and sends device information to the on-line analysis system of the zinc bath state in the form of TCP / IP; and / or

[0036] A camera, which is electrically connected to the PLC control cabinet and the Galvalibs detection probe respectively, and monitors the operation of the on-site hardware system of the detection and the hot-dip galvanizing production in the zinc pot area in real time.

[0037] A zinc dross detection device for a hot-dip galvanizing line according to the above aspect of the present invention, wherein the PLC control cabinet includes a Galvalibs upper computer device, which is used to send an excitation signal to the Galvalibs detection probe, obtain the detection signal transmitted from the Galvalibs detection probe, and process the detection signal, and transmit the signal to the on-line analysis system of the zinc bath state in the form of TCP / IP; and / or a PLC control device, which is used to control the operation of the feeding mechanism and send device information to the on-line analysis system of the zinc bath state in the form of TCP / IP.

[0038] Adopting the above technical solutions, the present invention has the following advantages:

[0039] This invention provides a zinc slag pattern recognition method and detection device for hot-dip galvanizing units. The zinc slag detection device detects the aluminum and iron content in the zinc bath during hot-dip galvanizing. The zinc slag pattern recognition method determines the current zinc slag pattern, enabling qualitative identification of the current zinc bath state. This has a very positive effect on guiding strip steel production, improving strip steel galvanizing quality, and reducing costs. The zinc slag pattern recognition has high accuracy and low error, providing a basis for on-site workers to monitor the current zinc bath production status in real time. It is of great significance for guiding the adjustment of zinc addition and zinc slag cleaning, and can provide important guidance for improving strip steel production quality. Attached Figure Description

[0040] Other features, objects, and advantages of the invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings.

[0041] Figure 1 This is a configuration diagram for zinc dross detection in the hot-dip galvanizing unit of this invention;

[0042] Figure 2 This is a structural connection block diagram of the zinc dross detection device for hot-dip galvanizing units of the present invention;

[0043] Figure 3 This is a flowchart of the zinc dross pattern recognition method for hot-dip galvanizing units according to the present invention;

[0044] Figure 4 This is a flowchart of the zinc slag mode discrimination process of the present invention. Detailed Implementation

[0045] The technical solution of the present invention will be specifically described below with reference to the accompanying drawings. The detailed features and advantages of the present invention are described in detail in the specific embodiments. The content is sufficient to enable any person skilled in the art to understand the technical content of the present invention and implement it accordingly. Based on the specification, claims and drawings disclosed in this specification, those skilled in the art can easily understand the related objects and advantages of the present invention.

[0046] Figure 1 This invention illustrates the configuration for zinc dross detection in a hot-dip galvanizing unit. Figure 2 The structural connection block diagram of the zinc dross detection device for hot-dip galvanizing units of the present invention is shown.

[0047] A zinc dross detection device for hot-dip galvanizing units is specifically as follows: Figure 1 and Figure 2 As shown, it includes the following four parts:

[0048] The Galvalibs detection probe is connected to the host computer in the PLC control cabinet via a cable. Its main function is to obtain the content and state of each chemical element in the zinc bath by shining a laser beam into the zinc bath, then amplify and filter the signal, and finally transmit it to the host computer in the PLC control cabinet via a cable.

[0049] The Galvalibs device is primarily used for continuous, real-time laser-induced breakdown spectroscopy (LIBS) measurements of molten metal. LIBS, based on elemental spectroscopy, is a technique that uses a laser to perform instantaneous measurements on the surface of a sample. A high-energy pulsed laser irradiates the surface, exciting a plasma. During cooling, the plasma emits characteristic light, which is collected by optical fibers and analyzed by a spectrometer to determine the content of each element. This technique utilizes the plasma generated by the pulsed laser to ablate and excite the substances in the sample. The spectrometer then acquires the spectrum emitted by the plasma-excited atoms to identify the elemental composition of the sample, enabling material identification, classification, qualitative and quantitative analysis. LIBS not only allows for real-time detection of zinc bath composition but also directly analyzes the content of effective aluminum, free iron, and various zinc slag components, typically suspended slag and bottom slag. The Galvalibs device distinguishes between dissolved and combined states of Al and Fe by the intensity of their spectral lines. The spectral wavelengths used for dissolved and combined states of various elements distributed in the slag are the same; the difference lies in the fact that the spectral intensities of combined Al and Fe are more than 20 times greater than those of dissolved Al and Fe. Because the composition within the zinc pot is relatively stable, the dissolved and combined states of Al and Fe are easily distinguished, thus allowing for the detection of the content of aluminum and iron in the slag within the zinc pot; and / or

[0050] The feeding mechanism, mechanically connected to the Galvalibs probe, primarily controls the probe's ascent, descent, and lateral movement. When the Galvalibs probe is in operation, it must be completely submerged 50mm below the zinc bath surface to obtain accurate and reliable data. When the probe is not in operation, it must be raised and removed from the zinc bath area to prevent liquefaction and solidification of the zinc bath or zinc vapor, which could ultimately clog it. And / or

[0051] The PLC control cabinet is electrically connected to the feeding mechanism. It includes a Galvalibs host computer and a PLC control unit. The Galvalibs host computer primarily transmits excitation signals to the Galvalibs detection probes, acquires the detection signals transmitted from the probes, processes the signals, and then transmits them to the zinc bath condition online analysis system via TCP / IP. The PLC control unit primarily controls the operation of the feeding mechanism and then sends equipment information to the zinc bath condition online analysis system via TCP / IP; and / or

[0052] The cameras are electrically connected to the PLC control cabinet and the Galvalibs detection probes, respectively, and are mainly used to monitor the operation of the on-site hardware system and the hot-dip galvanizing production in the zinc pot area in real time.

[0053] Figure 3 A flowchart of the zinc slag pattern recognition method for hot-dip galvanizing units of the present invention is shown.

[0054] A method for identifying zinc dross patterns in hot-dip galvanizing units, such as Figure 3 As shown, the specific steps include:

[0055] S1. Based on the data platform, obtain data on slag aluminum content and slag iron content in the zinc pot area;

[0056] The data platform in S1 consists of two parts: a steel coil data center and a zinc bath condition online analysis system.

[0057] The main function of the steel coil data center is to collect and store basic information about steel coils and production site data during strip steel production on the steel plant's servers.

[0058] The zinc bath status online analysis system has two main functions. First, it communicates with the host computer of the Galvalibs equipment to acquire various data of the zinc bath area (such as the current slag aluminum content and slag iron content in the zinc pot) and the working status data of the equipment in the form of TCP / IP, and sends them to the central server of the steel coil data. Second, it communicates with the steel coil data center to obtain real-time steel coil production data. Finally, it integrates and further calculates and analyzes various data, and displays them visually through the front-end page.

[0059] S1 specifically includes the following steps:

[0060] S11. The online zinc bath status analysis system acquires data on the aluminum and iron content of slag in the zinc bath area and the working status of the zinc pot, and sends the above data to the server of the steel coil data center.

[0061] S12. The steel coil data center collects and stores steel coil production data during strip steel production on the server, and receives data sent by the zinc bath condition online analysis system;

[0062] S13. The online zinc bath status analysis system communicates with the steel coil data center to obtain real-time steel coil production data. At the same time, it integrates and further calculates and analyzes the steel coil production data and the data in the zinc bath area, and displays it visually through the front-end page.

[0063] S2. Define several variables, substitute the data from S1 into the variables, and calculate the real-time values ​​of the variables;

[0064] S2 specifically includes the following steps:

[0065] S21. In a specific embodiment, based on the slag aluminum content data and slag iron content data in the zinc pot area obtained by the data platform, two variables are defined, namely zinc slag modulus dross and zinc slag amplitude θ, both of which are real-time values;

[0066] The formula for calculating the zinc slag mold dross is as follows:

[0067]

[0068] The formula for calculating the argument θ of zinc slag is as follows:

[0069]

[0070] S22. Based on the aluminum and iron content of the slag in the current zinc bath area, substitute them into the zinc slag mold and zinc slag angle respectively to calculate and obtain the calculated values ​​of the zinc slag mold and zinc slag angle.

[0071] Figure 4 A flowchart for zinc slag mode discrimination according to the present invention is shown.

[0072] S3. Determine the state of zinc slag based on the real-time values ​​of variables, identify the zinc slag pattern, and thus provide guidance for production.

[0073] S3 specifically includes the following steps, as follows: Figure 4 As shown:

[0074] S31. Based on historical production records, define the limit values ​​of zinc slag mold and zinc slag angle; based on historical production records, define the maximum value of zinc slag mold as 0.04 and the maximum value of zinc slag angle as 90°.

[0075] S32. Based on the limiting values ​​of the zinc dross mold and the zinc dross arc angle, the zinc dross mold is defined into four modes, which are as follows:

[0076] Pattern 1: Dross < 0.02, 45°C < θ < 90°C, indicating less floating dross in the zinc pot, tending towards surface dross;

[0077] Pattern 2: Dross < 0.02, θ < 45°C, indicating less floating dross in the zinc pot, tending towards bottom dross;

[0078] Pattern 3: 0.02 < dross < 0.04, 45°C < θ < 90°C, indicating more floating dross in the zinc pot, tending towards surface dross;

[0079] Pattern 3: 0.02 < dross < 0.04, θ < 45°C, indicating more floating dross in the zinc pot, tending towards bottom dross.

[0080] When the zinc dross mold is small and the zinc dross angular range is large, it indicates that the zinc dross content is less at this time, and the aluminum content in the zinc dross is higher, with more surface dross, which is beneficial to removing zinc dross, thus beneficial to production. Based on this, a method for pattern discrimination of zinc dross is determined, and the determination flow chart is specifically as Figure 4 shown.

[0081] S33. Perform pattern recognition on the content and component composition of zinc dross according to the actual values of the variables, discriminate the state of zinc dross, so as to provide guidance for production. As shown in Figure 4 shown, the determined method for pattern discrimination of zinc dross provides a basis for on-site workers to grasp the current production state of the zinc bath in real time, thus having great significance for guiding production.

[0082] In a specific embodiment, the above technical solution is applied to a certain production line of strip steel. When applied to the production of a coil of strip steel, the method for determining the zinc dross pattern of the zinc bath state is specifically as Figure 4 shown. A total of four patterns of zinc dross patterns are defined, and the online discrimination results of zinc dross pattern recognition are shown in Table 1 below,

[0083] Table 1 Online Discrimination Results of Zinc Dross Pattern Recognition

[0084] Volume Number steel grades dross_Al dross_Fe dross θ pattern 11130032000 DQ 0.00271 0.01668 0.01690 9.2 2 11130032000 DQ 0.00263 0.01697 0.01717 8.8 2 11130032600 DQ 0.00415 0.01461 0.01520 15.8 2 11130032600 DQ 0.00793 0.02345 0.02475 18.7 4 11130476700 590DP-c2 0.01032 0.01734 0.02018 30.8 4 11130476700 590DP-c2 0.02345 0.00954 0.02531 67.9 3 11423782900 590DP-c2 0.01455 0.00456 0.01525 72.6 1

[0085] This zinc slag pattern recognition method for hot-dip galvanizing units is used for online identification of zinc slag patterns in the zinc bath state during the strip steel production process on a certain production line. During a month of on-site operation, the zinc slag pattern recognition results were displayed in real-time on the online zinc bath composition analysis system. Since the zinc slag patterns defined in this technical solution are based on mathematical classification rather than artificial intelligence, verification using three days of selected production data showed that the pattern recognition results were consistent with the four zinc slag patterns initially defined by mathematical classification. Therefore, the zinc slag pattern recognition accuracy can reach over 95%, achieving low error in pattern recognition. This method has significant guiding significance for zinc addition and zinc slag cleaning during strip steel production, enabling qualitative identification of the current zinc bath state. It plays a very positive role in guiding strip steel production, improving strip steel galvanizing quality, and reducing costs.

[0086] Finally, it should be noted that although the present invention has been described with reference to specific embodiments, those skilled in the art should recognize that the above embodiments are only used to illustrate the present invention and are not intended to limit the present invention. Various equivalent changes or substitutions can be made without departing from the concept of the present invention. Therefore, any changes or modifications to the above embodiments within the essential spirit of the present invention will fall within the scope of the claims of the present invention.

Claims

1. A method for recognizing zinc dross pattern of a hot galvanizing line, characterized in that, Comprise the following steps: S1. Based on the data platform, obtain the slag aluminum content data and slag iron content data in the zinc bath area; S2. Define several variables, substitute the data in S1 into the variables, and calculate the real-time values of the variables; S3. According to the real-time value of the variable, the state of the zinc slag is judged, and the production is guided, S2 specifically comprises the following steps: S21. Define two variables, namely zinc slag mode and zinc slag amplitude angle; S22. According to the current slag aluminum content and slag iron content in the zinc bath area, substitute into the zinc slag mode and zinc slag amplitude angle respectively to calculate, and obtain the calculation value of the zinc slag mode and the zinc slag amplitude angle, The calculation formula of the zinc slag mode dross in S21 is as follows: ， The calculation formula of the zinc slag amplitude angle θ is as follows: ， S3 specifically comprises the following steps: S31. According to the historical production record, define the limit value of the zinc slag mode and the zinc slag amplitude angle; S32. According to the limit value of the zinc slag mode and the zinc slag amplitude angle, the mode of the zinc slag is defined as four modes; S33. According to the real value of the variable, the content and the component of the zinc slag are mode-identified, the state of the zinc slag is judged, and the production is guided, The four modes of the zinc slag in S32 are as follows: °C °C, represents less zinc pot suspended slag, tends to surface slag; °C, representing less zinc pot suspended slag, and tending to bottom slag; °C °C, which represents more zinc pot suspension slag and tends to surface slag; °C, which represents more zinc pot suspension slag and tends to bottom slag.

2. The method of claim 1, wherein the zinc dross pattern is identified by using a pattern recognition algorithm. The data platform in S1 comprises two parts, which are steel coil data center and zinc bath state online analysis system.

3. The zinc dross pattern recognition method for hot-dip galvanizing units as described in claim 2, characterized in that, S1 comprises the following steps: S11. The zinc bath state online analysis system obtains the slag aluminum content, slag iron content and zinc pot working state data in the zinc bath area, and sends the above data to the server of the steel coil data center; S12. The steel coil data center part collects and stores the steel coil production data during strip steel production on the server, and receives the data sent by the zinc bath state online analysis system; S13. The zinc bath state online analysis system and the steel coil data center communicate to obtain real-time steel coil production data, integrate and further calculate and analyze the steel coil production data and the zinc bath area data, and visually display through the front-end page.

4. A device for detecting zinc dross in a hot galvanizing line, characterized in that, Comprise: Galvalibs detection probe, which is connected with the upper computer equipment in the PLC control cabinet through cable communication, shoots laser beam into the zinc bath, obtains the content and existing state of each chemical element in the zinc bath, then amplifies and filters the signal, and transmits it to the upper computer equipment through cable; Feeding mechanism, which is mechanically connected with the Galvalibs detection probe, controls the rising and falling and left and right movement of the Galvalibs detection probe; PLC control cabinet, which is electrically connected with the feeding mechanism, controls the operation of the feeding mechanism, and sends device information to the zinc bath state online analysis system in the form of TCP / IP; Camera, which is electrically connected with the PLC control cabinet and the Galvalibs detection probe respectively, monitors the running condition of the detection site hardware system and the hot dip galvanizing production condition of the zinc pot area in real time, The hot dip galvanizing unit zinc slag detection device is used to execute the hot dip galvanizing unit zinc slag detection method in any one of claims 1-3.

5. A device for detecting zinc dross in a galvanizing line according to claim 4, characterized in that, The PLC control cabinet comprises: A Galvalibs host computer device is used to transmit excitation signals to the Galvalibs detection probe, acquire the detection signals transmitted from the Galvalibs detection probe, process the detection signals, and transmit the signals to the zinc bath status online analysis system in the form of TCP / IP; and / or A PLC control device is used to control the operation of the feeding mechanism and transmit device information to the zinc bath status online analysis system in the form of TCP / IP.

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