Spraying equipment

Abstract

Spraying equipment comprises a mounting frame and a spraying mechanism mounted on the mounting frame, and the spraying mechanism comprises an atomizer, an atomizing liquid outlet, an atomizing liquid outlet, an atomizing liquid outlet and a spraying liquid outlet, the spraying arm is arranged independent of the atomizer, at least two nozzles are distributed on the spraying arm, a liquid spraying flow channel for spraying the atomized release agent is arranged in each nozzle, an atomized liquid pipeline is arranged in the spraying arm, the liquid inlet end of the atomized liquid pipeline is communicated with the atomized liquid outlet through a connecting pipe, and the liquid outlet end of the atomized liquid pipeline is communicated with the atomized liquid outlet through a connecting pipe. And the liquid outlet end of the atomized liquid pipeline is communicated with fluid in the liquid spraying flow channel. According to the spraying equipment, the atomizer and the spraying arm are independently arranged, so that only the liquid spraying flow channel needs to be arranged in the spraying head arranged on the spraying arm, the flow channel is simple in structure, when the spraying head is blocked, only the liquid spraying flow channel needs to be dredged and cleaned, and dredging of the spraying head is facilitated; meanwhile, the spray head only needs to spray the atomized release agent, and the particle size of the atomized release agent is small, so that the probability of blockage of the spray head is reduced.

Description

Technical Field

[0001] The invention relates to the technical field of automobile parts spraying, and in particular to a spraying device. Background Art

[0002] In the forging industry, mold release agents are usually sprayed onto the mold surface, which has the following effects on the mold surface: first, the mold release agent is sprayed onto the mold surface after being atomized to cool the mold surface to achieve the mold temperature required by the process; second, the mold release agent is sprayed onto the mold surface to form a uniform protective film on the mold surface to prevent sticking and corrosion caused by physical and chemical reactions between the forging and the mold.

[0003] The equipment used for spraying the release agent in the prior art, such as the "Spray Assembly for Three-Plate Mold" disclosed in the Chinese utility model patent with patent number CN201822222542.X (authorization announcement number CN209477252U), includes a mounting frame and a plurality of spray heads mounted on the mounting frame. The mounting frame is provided with a gas flow channel and a liquid flow channel. The release agent passes through the liquid flow channel and the liquid spray flow channel and is sprayed from the liquid spray port. The gas passes through the gas flow channel, the vent hole of the guide ring and the jet flow channel in sequence and is sprayed from the jet hole. The jet hole gradually tilts toward the center of the nozzle along the direction of gas flow. The gas sprayed from the jet hole atomizes the release agent sprayed from the liquid spray hole, thereby expanding the spraying area, making the release agent evenly sprayed on the mold, and improving the cooling rate of the mold and the demolding effect of the forging.

[0004] However, the above-mentioned atomizing nozzle may have the following problems during use: First, in order to atomize the sprayed release agent, a liquid spray hole and a plurality of gas jet holes need to be provided in the nozzle, the liquid spray hole needs to be connected to the liquid spray channel, and each gas jet hole needs to be connected to its corresponding gas channel, which makes the internal flow channel of the spray head complicated. If there are larger particles of solid impurities in the gas or release agent that block the gas jet hole or the liquid spray hole, the complicated flow channel brings inconvenience to the unblocking and cleaning of the spray head; second, the release agent inlet and the gas inlet are both provided on the mounting plate, and the liquid flow channel connected to the release agent inlet and the gas flow channel connected to the gas inlet need to pass through the mounting frame to connect the spray head, and the mounting frame includes a mounting plate and a spray plate. If the connection between the mounting plate and the spray plate becomes loose due to the shaking of the spray plate during operation, and a gap is generated in the liquid flow channel, the release agent will leak from the gap. Summary of the invention

[0005] The first technical problem to be solved by the present invention is to provide a spraying device for spraying a release agent, which has a simple flow channel structure and is easy to clear and clean, in response to the above-mentioned existing technical status.

[0006] The second technical problem to be solved by the present invention is to provide a spraying device for spraying a release agent, which can prevent the release agent from leaking from the flow channel, in response to the above-mentioned existing technical status.

[0007] The technical solution adopted by the present invention to solve the above-mentioned first technical problem is: the spraying equipment includes a mounting frame and a spraying mechanism mounted on the mounting frame,

[0008] Characterized in that the spraying mechanism comprises:

[0009] An atomizer, used for atomizing the release agent, and having an atomized liquid outlet for the atomized release agent to flow out;

[0010] A spray arm is arranged independently of the atomizer, and at least two nozzles are distributed on the spray arm. A spray flow channel is arranged in the nozzle for spraying the atomized release agent. An atomized liquid pipeline is arranged in the spray arm, and the liquid inlet end of the atomized liquid pipeline is connected to the atomized liquid outlet by means of a connecting pipe, and the liquid outlet end of the atomized liquid pipeline is connected to the spray flow channel fluid.

[0011] In order to install the spray head on the spray arm, preferably, the spray arm includes a peripheral wall, the peripheral wall is closed into a tubular arm body, and each of the spray heads is spaced apart along the peripheral wall in the circumferential direction or the length direction thereof. The nozzles are spaced apart along the circumferential direction of the peripheral wall so that the nozzles can be arranged in multiple directions, so that when spraying the release agent on the forging die, the spray arm can be extended between the movable die and the fixed die to spray the release agent toward the movable die and the fixed die at the same time; and when spraying the release agent on the forging die with a certain length, the nozzles spaced apart along the length direction can spray the release agent simultaneously in the length direction of the die, avoiding the problem of uneven cooling of the die caused by the order of spraying when the nozzle is moved by the driving mechanism to spray the die.

[0012] Furthermore, the spray mechanism also includes a mounting seat, the atomizer and the spray arm are connected by means of the mounting seat, and in the fluid flow direction, the atomizer is located upstream. The atomizer and the spray arm are both mounted on the mounting seat to shorten the length of the connecting pipe connecting the atomized liquid pipeline and the atomized liquid outlet, so as to avoid the atomized release agent being transported in a longer pipeline, resulting in the atomized droplets re-aggregating and reducing the atomization effect.

[0013] In order to respectively mount the spray arm and the atomizer on the mounting seat, preferably, the mounting seat includes a bottom wall and a side wall extending at least partially from the edge of the bottom wall perpendicular to the fluid direction, the bottom wall and the side wall surround a mounting cavity, the end of the spray arm has a mounting portion, the mounting portion extends into the mounting cavity and is connected to the first end of the side wall, and the atomizer is connected to the bottom wall by a connecting member. The method of extending the end of the spray arm into the mounting cavity and connecting to the side wall of the mounting cavity limits the space for the spray arm to shake when the spray mechanism is used, thereby avoiding the problem of the spray arm loosening during use.

[0014] In order to solve the second technical problem mentioned above, preferably, the mounting portion and the arm body are integrally formed, the mounting portion is partially provided with a chamber connected to the arm body fluid, and the chamber is provided with a connecting portion corresponding to the liquid inlet end of the atomized liquid pipeline to connect it with the corresponding connecting pipe. The integrally formed mounting portion and arm body avoid the loosening problem between the mounting portion and the arm body due to shaking. At the same time, the integrally formed spray arm allows the atomized liquid pipeline to pass through the mounting portion and the arm body. Even if the spray arm still has a small amplitude of shaking during use, there is no leakage problem caused by the loosening of the connection between the separately arranged mounting portion and the arm body during use.

[0015] In order to connect the spraying mechanism to the mounting frame, preferably, the second end of the side wall extends out of the mounting cavity to form a first connecting portion, and is connected to the mounting frame by means of the first connecting portion.

[0016] In order to improve the efficiency of spraying the release agent, preferably, the spraying mechanism is provided with at least two, and the mounting frame includes a first mounting arm arranged parallel to the direction of fluid movement, and a second mounting arm connected to the first mounting arm and arranged perpendicular to the direction of fluid movement, and the second mounting arm is connected to the mounting seat of each of the spraying mechanisms. In this way, a plurality of spraying mechanisms are arranged on the mounting frame, and each spraying mechanism is connected to the mounting frame by means of the second mounting arm, so that the release agent can be sprayed on a plurality of forging dies at the same time, thereby improving the working efficiency.

[0017] In order to make the connection between each spray mechanism and the mounting frame more stable, preferably, there is a mounting space between adjacent spray mechanisms, the first mounting arm is arranged in the mounting space, and the mounting frame is also provided with a connecting piece connected to the first mounting arm and parallel to the second mounting arm, the connecting piece part protrudes toward the direction of the mounting seat to form a second connecting part, and the second connecting part is connected to the first connecting part of each mounting seat by means of a fastener. The provision of the connecting piece increases the connection points between the spray mechanism and the mounting frame, that is, the mounting seat is connected to the second connecting arm and to the first connecting arm by means of the connecting piece, so that the spray device is installed more stably and the reliability of the device is improved.

[0018] Compared with the prior art, the advantages of the present invention are: the spraying equipment independently sets the atomizer and the spray arm, so that only a spray flow channel needs to be set in the nozzle arranged on the spray arm, and the flow channel structure is simple. When the nozzle is blocked, only the spray flow channel needs to be unblocked and cleaned, which is convenient for unblocking the nozzle; at the same time, since the nozzle only needs to spray the atomized release agent, and the particle size of the release agent after atomization is small, the probability of nozzle blockage is reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a structural schematic diagram of an embodiment of the present invention;

[0020] Figure 2 It is a structural schematic diagram of the spraying equipment in an embodiment of the present invention;

[0021] Figure 3 It is a structural schematic diagram of the spraying mechanism in an embodiment of the present invention;

[0022] Figure 4 An exploded view of the spraying mechanism in an embodiment of the present invention;

[0023] Figure 5 Schematic diagram of the structure of the spray arm in the embodiment of the present invention;

[0024] Figure 6 It is a structural schematic diagram of a mounting frame in an embodiment of the present invention;

[0025] Figure 7 Schematic diagram of the structure of another spraying mechanism in an embodiment of the present invention. DETAILED DESCRIPTION

[0026] The present invention is further described in detail below with reference to the accompanying drawings.

[0027] like Figure 1-7 FIG. 1 is a preferred embodiment of the present invention. The spraying equipment of this embodiment includes a mounting frame 1 and a spraying mechanism 2 mounted on the mounting frame 1 .

[0028] Among them, Figure 1-2 As shown, the spraying equipment of this embodiment is provided with three spraying mechanisms 2. Among them, two spraying mechanisms 2 have the same structure, and the description is firstly made by taking the same two spraying mechanisms 2 as an example. Figure 3The spray mechanism 2 includes an atomizer 21 for atomizing the release agent, and a spray arm 22 independently provided from the atomizer 21. The atomizer 21 has an atomized liquid outlet 211 for the atomized release agent to flow out. The spray arm 22 is provided with an atomized liquid pipeline, and the liquid inlet end 3a of the atomized liquid pipeline is connected with the atomized liquid outlet 211 by means of a connecting pipe 24. The spray arm 22 includes a peripheral wall, which is closed into a tubular arm body 221. A plurality of spray heads 23 are arranged at intervals along the peripheral wall in the circumferential direction thereof, so that the spray heads 23 can spray the release agent in multiple directions at the same time, so that when spraying the release agent on the forging die, the spray arm 22 can be extended between the movable die P and the fixed die Q to spray the release agent in the movable die P and the fixed die Q at the same time. The nozzle 23 is provided with a liquid spray channel for spraying the atomized release agent, and the liquid outlet end 3b of the atomized liquid pipeline is fluidly connected to the liquid spray channel. The atomizer 21 and the nozzle 23 are independently provided, so that only the liquid spray channel needs to be provided in the nozzle 23, and the channel structure is simple. When the nozzle 23 is blocked, only the liquid spray channel needs to be cleared, which facilitates the clearing of the nozzle 23.

[0029] The spray mechanism 2 further includes a mounting seat 25, through which the atomizer 21 and the spray arm 22 are connected, and in the fluid flow direction, the atomizer 21 is located upstream. Figure 4 The mounting seat 25 includes a bottom wall 251 and a side wall 252 extending from the edge of the bottom wall 251 in a direction perpendicular to the fluid direction. The bottom wall 251 and the side wall 252 surround a mounting cavity 253. The end of the spray arm 22 has a mounting portion 222, which extends into the mounting cavity 253 and is connected to the first end 252a of the side wall 252. The atomizer 21 is connected to the bottom wall 251 by means of a connecting member. Figure 5 The mounting portion 222 and the arm body 221 of the spray arm 22 are integrally formed. The integrally formed mounting portion 222 and the arm body 221 and the mounting portion 222 extend into the mounting cavity 253 and are connected to the side wall 252 of the mounting cavity 253. This avoids shaking between the mounting portion 222 and the arm body 221 and between the spray arm 22 and the mounting seat 25, thereby avoiding the problem of loosening of the spray arm 22 during use. At the same time, the integrally formed spray arm 22 allows the atomized liquid pipeline to pass through the mounting portion 222 and the arm body 221. Even if the spray arm 22 still has a small amplitude of shaking during use, there is no leakage problem caused by loosening of the connection between the separately arranged mounting portion 222 and the arm body 221 during use.

[0030] like Figure 6As shown, the mounting frame 1 includes a first mounting arm 11 arranged parallel to the direction of fluid movement, and a second mounting arm 12 connected to the first mounting arm 11 and arranged perpendicular to the direction of fluid movement. There is a mounting space 4 between the two spraying mechanisms 2, the first mounting arm 11 is arranged in the mounting space 4, and the second mounting arm 12 is connected to the mounting seat 25 of each spraying mechanism 2. The mounting frame 1 is also provided with a connecting member 13 connected to the first mounting arm 11 and parallel to the second mounting arm 12, the second end 252b of the side wall 252 of the mounting seat 25 extends out of the mounting cavity 253 to form a first connecting portion 254, and a portion of the connecting member 13 protrudes toward the direction of the mounting seat 25 to form a second connecting portion 131, and the second connecting portion 131 is connected to the first connecting portion 254 of each mounting seat 25 by means of a fastener.

[0031] like Figure 7 As shown, the structure of the third spray mechanism 2 is basically the same as that of the above-mentioned spray mechanism 2, and is connected to the second mounting arm 12 and the connecting member 13 in the same manner, except that the spray heads 23 of the spray mechanism 2 are arranged only in a spaced relationship along the length direction of the peripheral wall of the spray arm 22, and the spray arm 22 rotates at an angle α with the fluid movement direction as the axis. The spray heads 23 can be selectively arranged in a direction perpendicular to the peripheral wall or in a direction parallel to the peripheral wall, so as to achieve simultaneous spraying of the movable die P and the fixed die Q of the forging die, and the spray arm 22 rotates at an angle α so that the direction in which the release agent is sprayed from the spray head 23 has an inclination. Compared with the solution of spraying perpendicular to the forging die, the spray mechanism 2 can shorten the installation distance with other spray mechanisms 2, thereby shortening the width of the entire device perpendicular to the fluid movement direction and reducing the overall volume of the device.

[0032] Furthermore, considering that the micro-roughness of the mold surface affects the adhesion ability of the release agent on its surface, the spraying equipment is equipped with a micro-roughness detection device for detecting the micro-roughness of the mold surface.

[0033] Based on the test results of the micro-roughness test equipment, the spray equipment makes relevant spray parameter adjustments. The specific execution steps are as follows:

[0034] Step S100, before the spraying equipment sprays, the micro-roughness detection equipment is started to perform micro-roughness detection on the mold surface to obtain the mold micro-roughness detection result.

[0035] Micro-roughness is an important indicator to describe the micro-geometric morphology of the mold surface, reflecting the unevenness and undulations of the mold surface at a very small scale. From a microscopic perspective, even if the mold surface looks relatively smooth to the naked eye, there are actually various tiny peaks and valleys. These microscopic fluctuations will directly affect the adhesion and spreading of the release agent on the mold surface and the subsequent demolding effect. Usually, multiple parameters are used to quantify micro-roughness, the most common of which are the arithmetic mean deviation (Ra), the maximum height of the profile (Rz), the average width of the profile unit (RSm), etc.

[0036] The micro-roughness detection equipment can be an atomic force microscope or a laser confocal microscope. The micro-roughness detection equipment is usually installed in a location close to the spraying equipment and convenient for operation. It is necessary to ensure that its environment is stable to avoid external vibrations, electromagnetic interference and other factors that affect the measurement accuracy.

[0037] The process of data recording and storage is as follows: The collected mold micro-roughness data needs to be recorded and stored in a standardized manner for subsequent query, comparison, and correlation analysis with other related data (such as release agent performance data, mold temperature data, etc.). Generally, a standardized data format is used, and the common ones are text file formats (such as CSV format, each line records the relevant information of a test area, including test time, mold number, test location coordinates, Ra value, Rz value and other parameters), or stored in a special database (such as SQL database, create corresponding data tables, and store various types of test information according to fields). At the same time, add detailed identification information to each test data record, such as the unique number of the mold, the specific location description of the test (such as a specific coordinate area of ​​the mold cavity, a certain side of the parting surface, etc.), so as to facilitate the subsequent quick and accurate search for the micro-roughness data of a specific mold or a specific part.

[0038] Step S200, taking the mold micro-roughness detection result as an input object, inputting it into a pre-trained spray parameter analysis model, outputting the optimal spray parameters, and controlling the spray equipment to execute according to the optimal spray parameters, wherein the spray parameters include spraying amount, spraying speed, atomizer power, and nozzle angle.

[0039] Spraying volume: refers to the volume or mass of the release agent sprayed onto the mold surface per unit time, usually measured in units such as milliliters per minute (ml / min) and grams per minute (g / min). It directly affects the thickness of the release agent coating formed on the mold surface. Too little spraying may result in insufficient release agent coverage, inability to effectively isolate the mold and the molded product, and affect the demolding effect; while too much spraying may cause waste of release agent, too thick coating, and even quality problems such as release agent mixing into the product during the molding process. For example, in the spraying of release agent on injection molds, for small precision injection molds, the appropriate spraying volume may be between 5-10ml / min, and the specific value should be determined based on factors such as the size and complexity of the mold and the demolding requirements.

[0040] Spraying speed: refers to the speed at which the nozzle moves when spraying on the mold surface, and the unit is generally meters per minute (m / min) or millimeters per second (mm / s). The speed of spraying will affect the uniformity of the release agent on the mold surface. If the speed is too fast, the release agent may not have enough time to fully adhere to certain areas, resulting in leakage or uneven coating; if the speed is too slow, the production efficiency will be reduced. For example, when spraying a large forging mold, if the spraying speed of the nozzle is set to 500mm / s, it can better ensure that the release agent evenly covers the entire mold surface while taking into account a certain production efficiency.

[0041] Atomizer power: Atomizer is a key device that converts liquid release agent into mist particles. Atomizer power determines its atomization effect on the release agent. The power affects the particle size of the release agent droplets, the uniformity of distribution, and the range of the spray. Higher atomizer power usually produces finer and more uniform droplets, which is conducive to the uniform adhesion of the release agent on the mold surface and good atomization coverage, but too high power may also cause excessive atomization of the release agent, and some droplets evaporate before reaching the mold surface. For example, for some release agents with higher viscosity, a higher atomizer power (such as 1500W) may be required to achieve a good atomization effect so that it can form a uniform coating on the mold surface like a low-viscosity release agent.

[0042] Nozzle angle: refers to the tilt angle of the nozzle relative to the mold surface, which determines the direction and coverage of the release agent. The appropriate nozzle angle can ensure that the release agent is accurately sprayed to various parts of the mold, especially for molds with complex shapes and curved surfaces. By adjusting the nozzle angle, the release agent can better fit the mold surface and avoid spraying dead angles. For example, when spraying an injection mold with a deep cavity structure, adjusting the nozzle angle to a certain tilt angle with the mold cavity wall (such as 45°) can allow the release agent to be smoothly sprayed into the cavity to achieve full coverage.

[0043] The spraying parameter analysis model is a mathematical model based on a large amount of experimental data, actual production data and related theoretical knowledge. Through machine learning, data analysis and other technical means, the correlation between mold micro-roughness and spraying parameters is established. It can predict the most suitable spraying parameter combination (i.e. spraying amount, spraying speed, atomizer power, nozzle angle, etc.) under the current mold surface state according to the input mold micro-roughness detection results, so as to achieve the best demoulding effect and spraying quality. The model can be constructed using a variety of algorithms, such as neural network algorithms (including multi-layer perceptron, convolutional neural network, etc.), support vector machine algorithms, regression analysis algorithms, etc. For example, the model constructed using the neural network algorithm uses many known mold micro-roughness values ​​and the corresponding spraying parameters with good effects in actual production as training data, allowing the model to learn the nonlinear mapping relationship therein. After multiple iterative training, the model can accurately output the corresponding optimal spraying parameters for the newly input mold micro-roughness data.

[0044] The model input and operation are as follows:

[0045] Input method: Input the sorted mold micro-roughness test result data according to the input interface specifications set by the model. This may involve converting the data into a specific data format (such as arrays, matrices, etc.). If the model is developed based on a specific programming software or platform (such as a model built with Python language combined with the Scikit-learn library), it is necessary to follow the corresponding function call rules and data input format requirements. For example, if the input requirement of the model is a two-dimensional array, in which each row represents the data of a test position, and each column corresponds to the mold number, Ra value, Rz value and other information, then the original data sorted in the early stage must be converted to the corresponding format before entering the model.

[0046] Model operation process: The spraying parameter analysis model performs operations based on the pre-set algorithm and the parameters obtained through training. Taking the neural network model as an example, the input mold micro-roughness data is first passed through the input layer, and then nonlinear transformation and feature extraction are performed in the hidden layer through the activation function (such as ReLU function, Sigmoid function, etc.). Different neurons are connected through appropriate weights to continuously process and transmit data, and finally the corresponding spraying parameter prediction value is output in the output layer. The entire operation process is based on the mapping relationship from micro-roughness to spraying parameters learned by the model before. The model will calculate the most suitable spraying amount, spraying speed, atomizer power, nozzle angle and other parameter values ​​based on the specific micro-roughness of the input and comprehensive consideration of various factors.

[0047] The output results are as follows: After the model operation is completed, the corresponding spray parameter results will be output, usually in the form of numerical values. For example, the output spray volume is 8ml / min, the spray speed is 400mm / s, the atomizer power is 1200W, and the nozzle angle is 30°. These values ​​are the parameter combinations predicted by the model to achieve the best spray effect under the current mold micro-roughness conditions.

[0048] In addition, considering that different batches of release agents may have certain differences in composition and performance due to factors such as raw material sources and production process fluctuations, for example, changes in key performance indicators such as viscosity, surface tension, volatility, etc. of the release agent will affect its atomization effect, adhesion ability and flow characteristics on the mold surface, making the spraying parameters designed based on fixed release agent performance no longer applicable. Therefore, after obtaining the mold micro-roughness test results, the key performance parameters of the release agent should also be tested and analyzed, and the spraying parameters should be optimized in combination with the release agent performance test results and the mold micro-roughness test results. The specific steps are as follows:

[0049] Step SA00, detect and obtain the key performance parameter data of the release agent, and analyze whether the actual fluctuation range of the key performance parameter data meets the preset fluctuation range. If yes, execute step SB00; if no, execute step SC00.

[0050] The key performance parameters of release agents include viscosity, surface tension and volatility.

[0051] Viscosity: refers to the ability of the release agent to resist flow, which reflects the thickness of the release agent. The viscosity has a crucial influence on the flow characteristics of the release agent on the mold surface. For example, a high-viscosity release agent flows more slowly and may form a thicker coating on the mold surface, but if the viscosity is too high, it may cause difficulty in atomization and fail to evenly cover the mold surface; while a low-viscosity release agent is easy to atomize and flow, but it may be difficult to form a protective film of sufficient thickness on the mold surface due to excessive fluidity. Viscosity is usually measured in millipascals seconds (mPa·s). Common release agent viscosities may range from tens to thousands of mPa·s, and the specific value depends on the type of release agent and the application scenario. The viscosity detection equipment can use a rotational viscometer or a capillary viscometer.

[0052] Surface tension: It is the tension on any boundary along the surface caused by the uneven molecular attraction of the liquid surface layer. The surface tension of the release agent determines its spreading ability and wetting performance on the mold surface. Lower surface tension helps the release agent spread quickly on the mold surface, better fill the microscopic depressions on the mold surface, and form a continuous and uniform coating; on the contrary, a release agent with high surface tension may form droplets on the mold surface, making it difficult to achieve full coverage and affecting the demolding effect. The unit of surface tension is generally millinewton per meter (mN / m), and the surface tension of release agents with different formulations usually fluctuates around 20-50mN / m. Surface tension testing equipment can use a pendant drop method surface tension meter and a maximum bubble pressure method surface tension meter.

[0053] Volatility: refers to the ability of the release agent to convert from liquid to gas under specific temperature and pressure conditions. The volatility is directly related to the drying speed and residue of the release agent on the mold surface. Release agents with strong volatility can dry quickly and shorten the production cycle, but if the volatilization speed is too fast, a large amount may be lost during the atomization and adhesion process, resulting in uneven coating or insufficient thickness; while release agents with too low volatility may have too much residue during the molding process, affecting the quality of the product or requiring additional cleaning steps. Volatility can be characterized by measuring the mass loss rate or volume reduction rate of the release agent over a certain period of time, such as the percentage of mass loss of the release agent after 1 hour at a specific temperature. Volatility detection equipment can use a thermogravimetric analyzer

[0054] The preset fluctuation range is the allowable fluctuation range of the key performance parameters of the release agent, which is pre-set based on a large amount of experimental data, past production experience and the quality standards of the release agent. The determination of the preset fluctuation range is intended to ensure that the release agent within this range can basically meet the normal spraying process requirements and demolding effect. For example, for a certain type of release agent, the preset fluctuation range of its viscosity may be set to ±10%, that is, if the standard viscosity of the release agent is 500mPa·s, then the actual detected viscosity value between 450-550mPa·s is considered to be within the acceptable fluctuation range; the preset fluctuation range of surface tension may be ±5mN / m, and the preset fluctuation range of volatility is set to a certain mass loss rate or volume reduction rate range according to the specific production process requirements and the type of release agent, such as the mass loss rate within 1 hour at a specific temperature is between 5%-15%. These preset fluctuation ranges need to be comprehensively considered and adjusted according to factors such as different types of release agents, mold types, production environments, and quality requirements of the final product. In the actual production process, with the improvement of the process and the change of product quality requirements, the preset fluctuation range may also be optimized.

[0055] The process of fluctuation range analysis involves data collection and collation, and comparative analysis with the preset range.

[0056] Data collection and collation: After testing the key performance parameters of the release agent such as viscosity, surface tension and volatility using the above-mentioned corresponding testing equipment, a series of test data are obtained. These data need to be collated and recorded to ensure the accuracy and completeness of the data. For example, each test must record the time of the test, the batch information of the release agent, the number of the testing equipment used, and the test environment conditions (such as temperature, humidity, etc.), and form a complete data record together with the performance parameter values ​​obtained by the test. For the data of repeated tests, statistical analysis should be performed to remove outliers (such as data that obviously deviates from the normal range due to measurement errors or sample contamination), and then calculate statistical quantities such as the mean and standard deviation to more accurately evaluate the actual situation of the release agent performance parameters.

[0057] Comparison analysis with preset range: Compare the actual data of the key performance parameters of the release agent with the preset fluctuation range. Taking viscosity as an example, if the standard viscosity of a batch of release agent is 600mPa·s, the preset fluctuation range is ±10%, that is, 540-660mPa·s. When the actual average viscosity value detected is within this range, the viscosity parameter is considered to meet the preset fluctuation range; if the actual viscosity value is lower than 540mPa·s or higher than 660mPa·s, the viscosity parameter is judged to exceed the preset fluctuation range. For surface tension and volatility parameters, the comparison and judgment are also carried out according to their respective preset fluctuation ranges. For example, the preset fluctuation range of the surface tension of a release agent is 30-40mN / m. If the actual detection value is 38mN / m, it is within the range; if the preset fluctuation range of volatility is 8%-18% mass loss rate (at a specific temperature and time), the actual detection value is 20%, which is beyond the range. Through this comparative analysis, it is determined whether the key performance parameters of the release agent meet the requirements, thereby deciding the subsequent operation steps (if they meet the requirements, execute step SB00; if they do not meet the requirements, execute step SC00).

[0058] Step SB00, maintain the original settings.

[0059] Step SC00, input the actual fluctuation range of the key performance parameter data of the release agent and the mold micro-roughness test results into the established and verified spray parameter optimization analysis model, output the optimal spray parameters, and control the spray equipment to execute according to the optimal spray parameters.

[0060] The spraying parameter optimization analysis model is a comprehensive mathematical model that integrates the actual fluctuation range of key performance parameter data of the release agent and the micro-roughness test results of the mold. It is constructed through complex algorithms and a large amount of experimental and production data training. Its purpose is to accurately predict and output the spraying parameter combination that can achieve the best spraying effect under the current working conditions based on these input information.

[0061] After receiving the input data, the spray parameter optimization analysis model performs complex calculations based on the algorithm built inside and the parameters obtained by pre-training. Taking the neural network model based on deep learning as an example, the data first enters the input layer, and then passes through multiple hidden layers for feature extraction and information processing. In the hidden layer, neurons are nonlinearly transformed through weighted connections and activation functions (such as ReLU function, Sigmoid function, etc.), and the key features and rules in the data are gradually extracted. For example, the model may learn the poor matching relationship between the high viscosity of the release agent and the low atomizer power, and the association between the specific pattern of the mold micro-roughness and the adjustment of the nozzle angle. After processing through multiple hidden layers, the predicted optimal spray parameter values ​​are finally output in the output layer, including spraying amount, spraying speed, atomizer power and nozzle angle. The entire operation process is based on the model's learning of a large amount of historical data and experimental data, so that it can intelligently predict the most suitable spray parameter combination based on the current input release agent performance and mold micro-roughness.

[0062] Further considering that if heating elements or cooling pipes are arranged around the mold, the mold is heated or cooled by heat conduction. The temperature sensor monitors the mold surface temperature in real time, and the temperature control system automatically adjusts the heating or cooling power according to the difference between the set target temperature and the actual temperature to achieve precise control of the mold temperature. The control of the mold temperature is conducive to creating more favorable conditions for the subsequent spraying process and further optimizing the actual effect of the spraying parameters. Therefore, the steps before step SC00 are also included, which are as follows:

[0063] Step SD00, input key performance parameter data and mold micro-roughness detection results into the mold temperature analysis model, and output the optimal mold temperature as the optimal mold temperature under the current working conditions.

[0064] The mold temperature analysis model is a specially constructed mathematical model that aims to predict the most suitable mold temperature by analyzing the key performance parameter data of the release agent and the mold micro-roughness test results. The model is developed and trained based on a large amount of experimental data, heat conduction theory, and actual production experience data. It can adopt a variety of modeling methods, such as multiple linear regression models, deep learning models based on neural networks, or hybrid models based on physical principle deduction combined with data fitting. The multiple linear regression model predicts the optimal temperature by establishing a linear relationship between the release agent performance parameters (such as viscosity, surface tension, volatility, etc.) and the mold micro-roughness and mold temperature.

[0065] The optimal mold temperature refers to the mold temperature value that enables the release agent to achieve the best atomization effect, adhesion performance and subsequent demolding effect on the mold surface under the current key performance parameters of the release agent and the micro-roughness of the mold.

[0066] The specific implementation process of step SD00 is as follows: 1. First, collect and organize the key performance parameter data of the release agent and the mold micro-roughness test result data. Ensure the accuracy and completeness of the data. For example, for the viscosity data of the release agent, it is necessary to clarify the measurement temperature conditions, the accuracy of the measuring instrument, and the number of significant digits of the data; for the mold micro-roughness data, it is necessary to include detailed detection information of different key parts of the mold (such as the cavity, parting surface, etc.). Then, preprocess these data. It may include data cleaning, removing outliers and erroneous data. 2. Input the preprocessed key performance parameter data of the release agent and the mold micro-roughness test result data according to the input format specified by the mold temperature analysis model. If the model is developed based on a specific programming framework or software platform (such as a multivariate linear regression model built with Python language combined with the Scikit-learn library or a neural network model built with TensorFlow), the data needs to be converted to the corresponding format. For example, for a neural network model, it may be necessary to organize the viscosity, surface tension, volatility of the release agent, and the micro-roughness data of different parts of the mold into a multidimensional array, where each row represents a set of data samples and each column corresponds to a different parameter variable, and then pass this array to the model as the input tensor of the model. 3. After receiving the input data, the mold temperature analysis model performs calculations based on its internally constructed algorithm and pre-trained parameters. The entire calculation process is based on the model's learning and training of a large amount of historical data and experimental data, so that it can accurately predict the most suitable mold temperature based on the current input release agent performance and mold micro-roughness.

[0067] Step SE00, based on the calculated optimal mold temperature and the actual temperature of the current mold, a model predictive control algorithm is used to calculate the power and time required for heating or cooling, which is used as an adjustment plan and executed to make the mold reach the optimal mold temperature.

[0068] Model predictive control is an advanced control algorithm that is based on a dynamic model of the system (in this case, the heat conduction model of the mold and the related process parameter model). It predicts the future behavior of the system and combines it with the current actual measurements to calculate the optimal control strategy (i.e., the power and time required for heating or cooling).

[0069] The model operation and solution generation are as follows: 1. The prediction model in the model predictive control algorithm calculates the temperature change curve of the mold under different future control strategies (i.e. different heating or cooling power sequences) based on the input mold current state, optimal mold temperature, various thermal characteristics and equipment parameters, based on the heat conduction principle and related empirical models. For example, the prediction model will calculate the temperature change curve of the mold under different future control strategies (i.e. different heating or cooling power sequences) based on the heat conduction equation. (Where Q is the heat flow, k is the thermal conductivity, A is the heat transfer area, is the temperature gradient), combined with the geometry and material properties of the mold, calculate the change of temperature distribution inside and on the surface of the mold over time during the heating or cooling process. At the same time, consider the influence of the presence of the release agent on the mold surface on the heat exchange (such as the thermal conductivity of the release agent, its state change at different temperatures, etc.) and the heat exchange between the mold and the surrounding environment (such as natural convection, radiation heat dissipation, etc.), and generate a series of temperature prediction curves, each curve corresponding to a possible heating or cooling power sequence. 2. Rolling optimization calculation: Based on the temperature change curve calculated by the prediction model, the rolling optimization module optimizes the future heating or cooling power sequence in each control cycle according to the set performance indicators (such as minimizing temperature control error, minimizing energy consumption, etc.). For example, using optimization algorithms such as linear programming and quadratic programming, under the constraint that the mold temperature finally reaches the optimal mold temperature and the temperature change process is smooth (avoiding excessive temperature fluctuations), find the heating or cooling power sequence that optimizes the performance indicators. If the weight of the temperature control error is set high, the optimization algorithm will tend to select a power sequence that can make the mold temperature reach the optimal mold temperature faster and more accurately; if the energy consumption weight is high, it will try to reduce the energy consumption of heating or cooling while ensuring that the temperature is controlled within a reasonable range. Through this rolling optimization calculation, a new, optimized heating or cooling power sequence is generated in each control cycle as the control strategy for the current control cycle.

[0070] According to the heating or cooling power and time scheme calculated by the model predictive control algorithm, a control command is issued to the heating element or cooling system of the mold. For the heating process, if it is calculated that the heating power needs to be set to 12 kW for 25 minutes, the control system adjusts the power supply of the heating element to stabilize it at 12 kW, and starts the timer to start timing. For the cooling process, if the cooling fan speed needs to be increased to 1500 rpm for 10 minutes, the control system adjusts the speed of the cooling fan drive motor and monitors the time. During the execution process, ensure that the control equipment (such as power regulators, motor drivers, etc.) can accurately execute control commands and monitor the operating status of the equipment in real time, such as monitoring whether the current and voltage of the heating element are normal, whether the water flow of the cooling system is unobstructed, and whether the fan is operating normally.

[0071] Step SF00, based on the influence model of the temperature reached by the mold on the key performance parameters of the release agent and the micro-roughness test results of the mold, analyze the influence of the mold temperature on the key performance parameters of the release agent and the micro-roughness test results of the mold, and adjust the optimal spraying parameters output by step SC00 according to the influence.

[0072] The analysis model of the influence of the temperature reached by the mold on the key performance parameters of the release agent and the mold micro-roughness test results is a specially constructed multivariate analysis model used to quantify the influence of mold temperature changes on the key performance parameters of the release agent (such as viscosity, surface tension, volatility, etc.) and the mold micro-roughness test results.

[0073] The model operation and influence degree analysis are as follows: 1. The influence degree analysis model operates according to the input data. Taking the neural network model as an example, after the mold temperature data enters the input layer, the neurons in the hidden layer perform complex nonlinear transformation and feature extraction, and establish a connection with the release agent performance parameters and the mold micro-roughness data. In the multivariate linear regression model, the influence coefficient of mold temperature change on the release agent performance parameters and mold micro-roughness is calculated according to the predetermined regression equation coefficient. For example, the model calculates that when the mold temperature increases by 10°C, the release agent viscosity reduction coefficient is 0.2 (i.e., the viscosity decreases by 20%), and the surface tension reduction coefficient is 0.15 (i.e., the surface tension decreases by 15%), and there is no significant effect on the mold micro-roughness (the influence coefficient is close to 0). These calculation results reflect the quantitative influence of mold temperature changes on other variables, and provide specific data basis for subsequent spraying parameter adjustments. 2. Evaluate and classify the influence degree results calculated by the model. According to the pre-set threshold or standard, judge whether the influence of mold temperature changes on release agent performance and mold micro-roughness is slight, moderate or severe. For example, if the coefficient of variation of the release agent performance parameters is within ±0.1, it is considered a slight impact; between ±0.1-±0.3, it is considered a moderate impact; and exceeding ±0.3 is considered a severe impact. Different spray parameter adjustment strategies are used for different degrees of impact. For example, when there is a slight impact, only fine-tuning of the spray parameters may be performed; when there is a moderate impact, moderate adjustments are made; when there is a severe impact, the spray parameters need to be adjusted to a greater extent to adapt to the change in mold temperature and ensure the spray quality.

[0074] Determination and implementation of spray parameter adjustment plan: According to the results and evaluation classification of the impact degree analysis model, a specific spray parameter adjustment plan is formulated. For example, if the mold temperature increases and the volatility of the release agent increases, the model analysis shows that the impact is medium, and the possible adjustment plan is: increase the spray volume by 15%, increase the spray speed by 10%, reduce the atomizer power by 10%, and optimize the nozzle angle according to the mold shape (such as adjusting the angle by 5° for a specific curved mold).

[0075] Furthermore, in order to detect the temperature distribution of the mold surface, it is possible to install an infrared thermal imager above or on the side of the spraying equipment, preferably with an adjustable pan-tilt installation method, so that the shooting angle or height of the infrared thermal imager can be adjusted according to the shape and size of the mold, thereby obtaining a temperature image of the entire mold surface. During the execution of step SE00, the detection and feedback of the infrared thermal imager can be performed in parallel, and the specific steps are as follows:

[0076] Step Sa00, start the infrared thermal imager to detect and obtain the mold surface temperature distribution data, and perform data preprocessing.

[0077] Infrared thermal imager is a device that uses the principle of infrared radiation to measure the temperature distribution on the surface of an object. It receives infrared radiation emitted by the target object through the detector, and then calculates the temperature information of the object surface based on the relationship between radiation intensity and temperature, and presents it in the form of an image. Each pixel in the image corresponds to the temperature value of a specific area on the surface of the target object. Data preprocessing involves noise removal and data calibration.

[0078] Step Sb00, the mold surface temperature distribution data transmitted by the infrared thermal imager and the key position temperature data obtained by the temperature sensor are merged using a preset weighted average algorithm.

[0079] The weighted average algorithm is a data fusion method that assigns corresponding weights according to the importance or reliability of data from different data sources, and then calculates the weighted average as the fusion result.

[0080] The data fusion process is as follows:

[0081] 1. Data preparation and correspondence: First, ensure that the temperature distribution data on the mold surface collected and preprocessed by the infrared thermal imager and the temperature data at the key position obtained by the temperature sensor are synchronized or close in time, so as to ensure the validity of the fused data. Parse the temperature image data of the infrared thermal imager to extract the regional temperature data corresponding to the key position of the temperature sensor. For example, if the temperature sensor is installed at the center of the parting surface of the mold, then find the temperature data of the corresponding central area of ​​the parting surface in the temperature image of the infrared thermal imager.

[0082] 2. Weight determination: The weight is determined based on the performance characteristics of the infrared thermal imager and temperature sensor and the actual application experience. As mentioned earlier, if the infrared thermal imager model is newer, the measurement accuracy can reach 0.1°C and can cover the entire mold surface, but the stability is slightly poor in complex environments; and the temperature sensor is a high-precision platinum resistance temperature sensor with an accuracy of 0.05°C, but it can only measure the temperature of several key points. Comprehensive consideration can determine that the weight of the infrared thermal imager data is 0.6 and the weight of the temperature sensor data is 0.4. Of course, the determination of weights is not fixed and can be dynamically adjusted according to different mold types, different production environments, and equipment usage. For example, when the environmental interference is small and the mold shape is simple, making the infrared thermal imager data more reliable, the weight of the infrared thermal imager data can be appropriately increased.

[0083] 3. Weighted average calculation: Assuming that the temperature value measured by the temperature sensor at a key position of the mold is T1 = 50°C, and the average temperature value measured by the infrared thermal imager in the corresponding area is T2 = 52°C, according to the weights determined above, the fused temperature value T = T2×0.6+T1×0.4=52×0.6+50×0.4=51.2°C. Such weighted average calculation is performed on each key position on the mold surface and its corresponding infrared thermal imager area, thereby obtaining a complete set of fused mold surface temperature data, which contains both the high-precision local information of the temperature sensor and the large-area distribution information of the infrared thermal imager, and can more accurately reflect the overall temperature state of the mold.

[0084] Step Sc00, analyzing the uniformity of the temperature distribution on the mold surface based on the fused temperature data and calculating the temperature gradient.

[0085] Temperature distribution uniformity: refers to the degree of temperature difference between different areas on the mold surface. Good uniformity means that there are no local overheated or overcooled areas on the mold surface, and the temperature of the entire surface is relatively consistent.

[0086] The temperature gradient indicates the rate of change of the mold surface temperature in space, that is, the change in temperature per unit distance. It reflects the direction and rate of heat transfer on the mold surface.

[0087] The analysis and calculation process is as follows:

[0088] Data collation and regional division: The fused mold surface temperature data is divided into regions according to the mold geometry and process requirements. For example, for injection molds, it can be divided into cavity area, core area, parting surface area, etc.; for forging molds, it can be divided according to the working part and edge area of ​​the mold. This makes it easier to analyze the temperature distribution uniformity and temperature gradient in different areas. Taking a simple rectangular mold as an example, it can be divided into four quadrants, each containing several temperature data points.

[0089] Calculation of temperature distribution uniformity: For each divided area, calculate the standard deviation and range of its temperature distribution. Take a certain area as an example, assuming that the area has n temperature data points T1, T2, …, Tn, first calculate the average temperature of the area T_avg = (T1 + T2 + … + Tn) / n. Then calculate the standard deviation σ, the calculation formula is: σ = sqrt [((T1-T_avg)^2 + (T2-T_avg)^2 + … + (Tn-T_avg)^2) / (n-1)]. The range is the difference between the highest temperature T_max and the lowest temperature T_min in the area, that is, R = T_max-T_min. For example, the temperature data of a certain area is [52℃, 55℃, 53℃, 54℃, 56℃], the average temperature T_avg = 54℃, the standard deviation σ = 1.58℃, and the range R = 4℃. By comparing the standard deviation and range of each area, we can intuitively understand the differences in the uniformity of temperature distribution in different areas of the mold surface, find out the areas with poor temperature uniformity, and provide a basis for subsequent temperature adjustments.

[0090] 3. Temperature gradient calculation: In each area, choose a suitable method to calculate the temperature gradient. A commonly used method is to use the difference method. For a two-dimensional mold surface, in the x-axis direction, the temperature gradient component Gx at a certain point (i, j) can be approximately calculated as: Gx(i, j) = [T(i+1, j)-T(i-1, j)] / (2Δx), where T(i, j) represents the temperature value at the coordinate (i, j), and Δx is the distance between adjacent data points in the x-axis direction; in the y-axis direction, the temperature gradient component Gy is: Gy(i, j) = [T(i, j+1)-T(i, j-1)] / (2Δy), and Δy is the distance between adjacent data points in the y-axis direction. For example, in a mold surface area, the coordinates of a point are (3,4), Δx = Δy = 5mm, T(2,4) = 50℃, T(4,4) = 53℃, T(3,3) = 51℃, T(3,5) = 52℃, then Gx(3,4) = (53-50) / (2×5) = 0.3℃ / mm, Gy(3,4) = (52-51) / (2×5) = 0.1℃ / mm, and the temperature gradient vector of this point is (Gx(3,4), Gy(3,4)) = (0.3℃ / mm, 0.1℃ / mm). By calculating the temperature gradients of different points in each area of ​​the mold surface, a temperature gradient distribution diagram can be drawn, which clearly shows the temperature change trend on the mold surface and the regional distribution of the degree of change.

[0091] Step Sd00: Based on the temperature gradient distribution in different regions and according to the corresponding relationship between the preset temperature gradient distribution and the adjustment scheme, an adjustment scheme is analyzed and determined, and the corresponding adjustment scheme is executed.

[0092] The correspondence between the preset temperature gradient distribution and the adjustment scheme is a pre-established rule or model. Based on a large amount of experimental data, simulation analysis and actual production experience, different temperature gradient distributions on the mold surface are associated and matched with corresponding temperature control adjustment schemes. For example, when the temperature gradient of a certain area on the mold surface exceeds a certain threshold (such as 0.5°C / mm) and presents a specific direction (such as along the parting surface of the mold), it corresponds to a specific cooling or heating strategy, which may include adjusting the flow distribution of the cooling pipe, turning on or off the heating elements in a specific area, etc. This correspondence can exist in the form of a table, a mathematical function, or a model trained based on a machine learning algorithm. Taking the table form as an example, there may be multiple rows of data, each row containing the range, direction and corresponding adjustment scheme description of the temperature gradient, such as "temperature gradient: 0.3-0.5°C / mm, direction: horizontal, adjustment scheme: moderately increase the flow of the horizontal cooling pipe by 10%".

[0093] According to the temperature gradient distribution data of different areas on the mold surface calculated in step Sc00, the size and direction of the temperature gradient in each area are analyzed in detail. For example, for an injection mold with a complex shape, there may be multiple areas with different temperature gradients. In the bottom area of ​​the mold cavity, it was found through analysis that the temperature gradient was 0.4℃ / mm, and the direction was radiating from the center to the edge; in the area near the parting surface, the temperature gradient was 0.6℃ / mm, and the direction was along the longitudinal direction of the parting surface. These temperature gradient distribution characteristics are matched and searched with the preset corresponding relationship. Taking the area near the parting surface as an example, the corresponding adjustment plan is found by comparing with the preset relationship table, which may be "temperature gradient: 0.5-0.8℃ / mm, direction: longitudinal, adjustment plan: increase the flow rate of the longitudinal cooling pipe of the parting surface by 20%, and check whether the adjacent heating elements have abnormal heating."

Claims

1. A spraying device, comprising a mounting frame (1) and a spraying mechanism (2) mounted on the mounting frame (1), It is characterized in that The spraying mechanism (2) comprises: An atomizer (21) for atomizing the release agent and having an atomized liquid outlet (211) for the atomized release agent to flow out; A spray arm (22) is arranged independently of the atomizer (21), and at least two spray heads (23) are distributed on the spray arm (22). A spray flow channel for spraying the atomized release agent is arranged in the spray head (23). An atomized liquid pipeline is arranged in the spray arm (22), and a liquid inlet end (3a) of the atomized liquid pipeline is connected to the atomized liquid outlet (211) by means of a connecting pipe (24), and a liquid outlet end (3b) of the atomized liquid pipeline is connected to the spray flow channel fluid.

2. The spraying equipment according to claim 1, characterized in that: The spray arm (22) comprises a peripheral wall, the peripheral wall is closed into a tubular arm body (221), and the spray heads (23) are arranged at intervals along the peripheral wall in the circumferential direction or the length direction thereof.

3. The spraying equipment according to claim 2, characterized in that: The spray mechanism (2) further comprises a mounting seat (25), the atomizer (21) and the spray arm (22) are connected by means of the mounting seat (25), and in the fluid flow direction, the atomizer (21) is located upstream.

4. The spraying equipment according to claim 3, characterized in that: The mounting seat (25) comprises a bottom wall (251) and a side wall (252) extending at least partially from the edge of the bottom wall (251) in a direction perpendicular to the fluid direction; the bottom wall (251) and the side wall (252) surround a mounting cavity (253); the end of the spray arm (22) has a mounting portion (222); the mounting portion (222) extends into the mounting cavity (253) and is connected to a first end (252a) of the side wall (252); the atomizer (21) is connected to the bottom wall (251) by means of a connecting member.

5. The spraying equipment according to claim 4, characterized in that: The mounting portion (222) and the arm body (221) are integrally formed, and the mounting portion (222) is partially provided with a chamber in fluid communication with the arm body (221), and the chamber is provided with a connecting portion (31) corresponding to the liquid inlet end (3a) of the atomized liquid pipeline for connecting the chamber with the corresponding connecting pipe (24).

6. The spraying equipment according to claim 4, characterized in that: The second end (252b) of the side wall (252) extends outward from the installation cavity (253) to form a first connection portion (254), and is connected to the installation frame (1) by means of the first connection portion (254).

7. The spraying equipment according to claim 6, characterized in that: The spraying mechanism (2) is provided with at least two, and the mounting frame (1) comprises a first mounting arm (11) arranged parallel to the direction of fluid movement, and a second mounting arm (12) connected to the first mounting arm (11) and arranged perpendicular to the direction of fluid movement, wherein the second mounting arm (12) is connected to the mounting seat (25) of each of the spraying mechanisms (2).

8. The spraying equipment according to claim 7, characterized in that: An installation space (4) is provided between adjacent spraying mechanisms (2), the first installation arm (11) is arranged in the installation space (4), and the installation frame (1) is also provided with a connecting member (13) connected to the first installation arm (11) and parallel to the second installation arm (12), and a portion of the connecting member (13) protrudes in the direction of the installation seat (25) to form a second connecting portion (131), and the second connecting portion (131) is connected to the first connecting portion (254) of each installation seat (25) by means of a fastener.

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