Anti-splashing safety protection method and system for machine tool

Abstract

The invention discloses an anti-splashing safety protection method and system for a machine tool, and the method comprises the steps: S1, the system predicts the type of a splash possibly generated in the machining process of the machine tool based on a machining material and a tool type; s2, simulating splash generation conditions under different processing conditions in combination with the processing parameters, and obtaining key characteristics of the splash; s3, the influence of cooling liquid spraying on the splash is simulated, and a distribution diagram of the splash is output; s4, performing risk assessment on the splash based on a simulation result, and determining a protection priority level; and S5, formulating protection measures according to the protection priority level, and monitoring generation and distribution conditions of splash in real time for early warning. According to the invention, by predicting the type of the splash, simulating the generation condition of the splash, simulating the influence of the cooling liquid, evaluating the risk and formulating and implementing protective measures, the generation and behavior of the splash are comprehensively predicted and simulated from multiple angles, the application strategy of the cooling liquid is optimized, and the generation of the splash is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of a safety protection method, and in particular to an anti-splash safety protection method and system for a machine tool. Background Art

[0002] With the continuous improvement of the level of industrial automation, machine tools play a vital role in modern manufacturing. However, in the actual production process, especially when performing high-precision processing tasks such as metal cutting and drilling, they often face the problem of splashing metal debris, cutting fluid and high-temperature particles; these problems not only seriously threaten the personal safety of operators, but also cause wear and even damage to machine tools and equipment, and may also reduce product quality and increase the operating costs of enterprises.

[0003] At present, one of the most commonly used methods is to use physical barriers as a basic means of protection. Such barriers are usually made of high-strength, wear-resistant materials, such as polycarbonate, tempered glass or other synthetic materials. They are designed in the form of protective covers or protective doors and installed at key positions of machine tools to prevent fragments generated by high-speed rotating tools from directly hitting operators or other equipment; another method is to adjust the direction and speed of the airflow inside the machine tool to direct the splashes to specific areas, such as dust collectors or collection tanks, thereby reducing the impact on the working environment; set protective baffles in the cutting area of ​​the machine tool to prevent the spread of splashes; this machine tool anti-splash safety protection method and system is suitable for various types of machine tools. Although the existing anti-splash technology has achieved certain results, due to the complex and changeable operating environment of the machine tool, the harm of splashes is still great, so there is still a lot of room for improvement;

[0004] Therefore, it is necessary to improve the anti-splash safety protection method and system for machine tools in the prior art to solve the above problems. Summary of the invention

[0005] The present invention overcomes the deficiencies of the prior art and provides a method and system for anti-splash safety protection for machine tools, aiming to solve the problem that the protective devices in the prior art lack specificity and cannot comprehensively assess the risk of splashes.

[0006] To achieve the above object, the technical solution adopted by the present invention is: a splash protection method for machine tools, comprising:

[0007] S1. The system predicts the type of spatter that may be generated during machine tool processing based on the processing material and tool type;

[0008] S2. Combine processing parameters to simulate the generation of spatter under different processing conditions and obtain the key characteristics of spatter;

[0009] S3, simulating the effect of coolant spraying on splashes, and outputting a distribution map of the splashes;

[0010] S4. Conduct risk assessment on splashes based on simulation results and determine the protection priority level;

[0011] S5. Develop protective measures based on protection priority levels, and monitor the generation and distribution of splashes in real time to provide early warnings.

[0012] In a preferred embodiment of the present invention, in step S1,

[0013] S11. The system collects basic information about the physical and chemical properties of the processed materials, as well as the geometry, material, and cutting angle of different tool types;

[0014] S12. Based on the collected basic information, combined with historical processing experience and experimental data, establish a database containing the types of spatter that may be generated under different processing materials, tool types and their combinations;

[0015] S13. According to the current processing material, tool type and cutting parameters, the type of spatter that may be generated during the machine tool processing is predicted based on the database.

[0016] In a preferred embodiment of the present invention, in step S13, the prediction step includes:

[0017] Input the current processing materials and their physical and chemical properties into the system;

[0018] Enter the type of tool currently being used and its geometry, material and cutting angle;

[0019] According to the input processing material and tool type, similar historical records or experimental data are searched in the established spatter database;

[0020] Match the retrieved historical records or experimental data with the current processing conditions to find the most similar cases.

[0021] In a preferred embodiment of the present invention, the similarity between the current processing conditions and the historical records or experimental data in the database is calculated by a similarity matching method to find the closest case;

[0022] Given the current processing condition P = (p1, p2, ..., p n ), where n is the dimension of the processing condition, p i represents the value of the i-th processing condition;

[0023] A historical record or experimental data in the database is H = (h1, h2, ..., h n); Weighted Euclidean distance between the current processing condition P and the data H in the database Among them, ω i is the weight of the i-th processing condition;

[0024] Sort the calculated weighted Euclidean distances from small to large, and select the smallest data as the most similar case.

[0025] In a preferred embodiment of the present invention, in step S2,

[0026] The system receives the currently used processing material, tool type and specific processing parameters, including: cutting speed, feed rate and cutting depth;

[0027] Configure the machining parameters required for simulation, cutting speed V c , feed speed f, cutting depth a p ;

[0028] The cutting process is simulated using numerical simulation technology of finite element analysis or discrete element method to obtain the key characteristics of spatter, including: spatter speed, spatter movement trajectory, and spatter quantity.

[0029] In a preferred embodiment of the present invention, the speed of the splashing object is estimated by the principle of conservation of energy. Among them, W c is the cutting power, m is the mass of spatter, and l is a coefficient related to cutting speed, feed rate, and cutting depth;

[0030] Use Newton's second law and the air resistance equation to simulate the trajectory of the splash: in, is the position vector, is the acceleration due to gravity, k is the drag coefficient, is the velocity vector of the splash;

[0031] The relationship between the amount of spatter and cutting parameters can be fitted by experimental data Among them, a, b, c, and d are fitting coefficients.

[0032] In a preferred embodiment of the present invention, in step S3,

[0033] The flow of coolant is simulated by computational fluid dynamics software, and the effects of coolant injection angle, injection pressure and injection flow rate on coolant distribution are calculated;

[0034] Simulate the interaction between coolant and splash;

[0035] The coolant slows down the speed of the splashes by increasing the resistance. Suppose the resistance F rand splash velocity V p is proportional to the square of r =k v V p , where k v is the drag coefficient, which depends on the properties of the coolant and the surface characteristics of the splash;

[0036] The speed of splash V p The relationship with time t is Among them, V p0 is the initial velocity of the splash;

[0037] The impact of the coolant changes the trajectory of the splashing objects, which can be simulated by adding an additional force term to Newton's second law, F = F g +F d +F c , where F g ,F d ,F c The force is gravity, air resistance and coolant impact;

[0038] Coolant reduces the amount of spatter, coolant helps stabilize the cutting area and reduce irregular fracture of the material; Among them, N s is the amount of splash after cooling, and Q is the coolant flow rate.

[0039] In a preferred embodiment of the present invention, in step S4, based on the simulation results of steps S1 to S3, a risk assessment is performed on the splashes to determine the protection priority level;

[0040] Identify risk indicators:

[0041] Splash velocity V p 、Number of splashes s , splash shape M, splash size S, splash distribution range R;

[0042] According to the risk indicators, assign weights to each indicator and calculate the total risk score: R s =ω v V p +ω n N s +ω m M+ω s S+ω R R, where ω v is the splash velocity weight, ω n is the splash weight, ω m is the splash shape weight, ω s is the splash size weight, ω R is the splash distribution range weight.

[0043] In a preferred embodiment of the present invention, the protection levels of different areas of the machine tool are ranked according to the risk scores to determine the protection priority levels; the priority levels are divided into three categories: low risk, medium risk, and high risk; the higher the risk score, the more dangerous it is.

[0044] The present invention provides a splash protection system for a machine tool, comprising:

[0045] Data collection and processing module, used to collect data such as physical and chemical properties of processing materials, basic information of tool types, and processing parameters;

[0046] A spatter prediction module is used to predict the type of spatter that may be generated during machine tool processing based on the collected data;

[0047] The spatter simulation module is used to combine the processing parameters, simulate the spatter generation under different processing conditions, and obtain the key characteristics of the spatter;

[0048] Coolant impact simulation module, used to simulate the impact of coolant spray on splashes and output the distribution map of splashes;

[0049] The risk assessment module is used to conduct risk assessment of splashes based on simulation results, determine the protection priority level, and calculate the risk score by comprehensively considering factors such as splash speed, quantity, shape, size and distribution range;

[0050] The protection level module ranks the protection levels of different areas according to risk scores;

[0051] The protection measures formulation module is used to formulate corresponding protection measures according to the protection priority level;

[0052] The monitoring module is used to monitor the generation and distribution of splashes in real time and issue early warnings.

[0053] The present invention solves the defects existing in the background technology and has the following beneficial effects:

[0054] (1) The present invention predicts and simulates the generation and behavior of spatter from multiple angles, optimizes the coolant application strategy, and reduces the generation of spatter by predicting the type of spatter, simulating the generation of spatter, simulating the impact of coolant, conducting risk assessment, and formulating and implementing protective measures. It also ensures that potential risks are discovered and handled in a timely manner through accurate risk assessment and dynamic protective measures, significantly improving the safety of the machine tool processing environment, protecting operators and equipment from damage by spatter, and realizing intelligent management and optimization, thereby improving the overall protection effect and production efficiency.

[0055] (2) Step S2 of the present invention simulates the generation of splashes, and step S3 simulates the effect of coolant injection on splashes, and outputs a distribution map of splashes; through the combination of steps S2 and S3, the system can simulate the cooling and impact effects of coolant on splashes, thereby optimizing the injection parameters of the coolant and reducing the generation and diffusion of splashes. This combination not only improves the efficiency of coolant use, but also significantly reduces the risk of splashes to operators and equipment; it makes the application of coolant more scientific and efficient, can effectively reduce the generation of splashes, and improve the safety of the processing environment.

[0056] (3) Through the combination of steps S3 and S4, the system of the present invention can comprehensively evaluate the risk of splashing on the basis of considering the influence of coolant, so as to determine the most reasonable protective measures; it not only improves the accuracy of risk assessment, but also can dynamically adjust the protection strategy according to actual conditions, which can better guide the formulation of protective measures and improve the protection effect.

[0057] (4) In step S4 of the present invention, a risk assessment is performed on the splashes to determine the protection priority level. In step S5, protective measures are formulated according to the protection priority level, and the generation and distribution of the splashes are monitored in real time for early warning. Through the combination of steps S4 and S5, the system can formulate targeted protective measures according to the risk assessment results, and ensure the effective implementation of the protective measures through real-time monitoring and early warning mechanisms, which not only improves the pertinence and effectiveness of the protective measures, but also can timely discover and deal with potential risks.

[0058] (5) The present invention directly improves the pertinence and accuracy of protective measures by predicting the types of spatter that may be generated during machine tool processing based on the processing materials and tool types in step S1. Compared with the lack of pertinence in the design of protective devices in the prior art, the present invention can be flexibly adjusted according to the characteristics of spatter under different processing conditions, thereby significantly enhancing the protective effect. Furthermore, by systematically collecting basic information on processing materials and tool types, and combining historical processing experience and experimental data, the present invention establishes a comprehensive spatter database, which provides solid data support for subsequent risk assessment and formulation of protective measures. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art are briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative work.

[0060] Figure 1 is a flow chart of a preferred embodiment of the present invention. DETAILED DESCRIPTION

[0061] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0062] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0063] Application Overview:

[0064] At present, there are many anti-splash safety protection methods and technologies for machine tools on the market, such as the use of protective covers, baffles, suction fans and other devices to block or absorb the splashes generated during the processing process. These technologies can reduce the damage caused by splashes to operators and equipment to a certain extent and improve the safety of the processing environment; however, with the continuous changes in processing requirements and the continuous advancement of technology, the existing anti-splash safety protection methods and technologies still have certain limitations and shortcomings.

[0065] Although the existing anti-splash safety protection methods and technologies for machine tools have achieved certain results, the following problems still exist: First, the design and installation of protective devices often lack specificity and cannot be flexibly adjusted according to specific processing conditions and splash characteristics, resulting in limited protection effects; second, for splashes of different types and characteristics, the existing protection measures often lack comprehensiveness and systematicness, making it difficult to form an effective protection system; in addition, the existing anti-splash safety protection methods and technologies also have deficiencies in real-time monitoring and effect evaluation, and are unable to promptly detect and deal with failures or deficiencies in protective devices, affecting the reliability and stability of protection.

[0066] In view of the deficiencies in the prior art, the present invention proposes a method and system for anti-splash safety protection for machine tools, establishes a comprehensive and effective anti-splash safety protection system for machine tools, and provides all-round safety protection for operators and equipment.

[0067] Exemplary methods:

[0068] like Figure 1 As shown, a splash protection method for machine tools comprises the following steps:

[0069] S1. The system predicts the type of spatter that may be generated during machine tool processing based on the processing material and tool type;

[0070] S2. Combine processing parameters to simulate the generation of spatter under different processing conditions and obtain the key characteristics of spatter;

[0071] S3, simulating the effect of coolant spraying on splashes, and outputting a distribution map of the splashes;

[0072] S4. Conduct risk assessment on splashes based on simulation results and determine the protection priority level;

[0073] S5. Formulate protective measures according to the protection priority level, and monitor the generation and distribution of splashes in real time to issue early warnings;

[0074] Specifically, in step S1, the step of predicting the type of spatter that may be generated during the machining process of the machine tool includes:

[0075] S11. The system collects basic information about the physical and chemical properties of the processed materials, as well as the geometry, material, and cutting angle of different tool types;

[0076] S12. Based on the collected basic information, combined with historical processing experience and experimental data, establish a database containing the types of spatter that may be generated under different processing materials, tool types and their combinations;

[0077] S13, predicting the type of spatter that may be generated during the machine tool processing based on the database according to the current processing material, tool type and cutting parameters;

[0078] Processed materials include: metals, plastics and composites;

[0079] Physical properties include: hardness, toughness, and melting point;

[0080] Chemical properties include: whether it is easily oxidized and whether it contains harmful ingredients;

[0081] Tool types include: turning tools, milling cutters and drills;

[0082] Tool geometry includes: tip radius, rake angle, and relief angle;

[0083] Tool material: high speed steel, carbide, ceramic;

[0084] Cutting angle: including rake angle, back angle and main deflection angle;

[0085] By systematically collecting this basic information, accurate data support can be provided for the subsequent establishment of a spatter database and prediction of spatter types.

[0086] Design the database table structure, including the processing material table, tool type table, and spatter type table; the table contains necessary fields, including: material name, physical properties, chemical properties, tool type, geometry, material, cutting angle, spatter type, shape, and size;

[0087] Set the relationship between tables, the association between the processing material table and the tool type table, and the association between the processing material table, the tool type table and the spatter type table to ensure that data can be easily queried and retrieved.

[0088] In step S12, based on the collected basic information, combined with historical processing experience and experimental data, the system establishes a database containing the types of spatter that may be produced under different processing materials, tool types and their combinations. This database will serve as an important basis for the subsequent prediction of spatter types.

[0089] In step S13, the system needs to predict the type of spatter that may be generated during the machine tool processing process based on the current processing material, tool type and cutting parameters, using the spatter database established in step S12.

[0090] The prediction steps include:

[0091] Input the current processing materials and their physical and chemical properties into the system;

[0092] Enter the type of tool currently being used and its geometry, material and cutting angle;

[0093] According to the input processing material and tool type, similar historical records or experimental data are searched in the established spatter database;

[0094] Match the retrieved historical records or experimental data with the current processing conditions to find the most similar case;

[0095] Based on the matching results, the system predicts the types of spatter that may be generated under the current processing conditions, including the shape and size of the spatter; the shapes of the spatter include: granular, flake and mist; the sizes of the spatter include: microparticles, small particles and large particles.

[0096] Particle splashes have a diameter of less than 1 mm; small particle splashes have a diameter between 1 mm and 5 mm; large particle splashes have a diameter greater than 5 mm; flake splashes are thin flakes formed by tearing or peeling of materials during the cutting process, and have irregular shapes and sizes; mist splashes are composed of extremely fine droplets or particles.

[0097] Specifically, through the similarity matching method, the similarity between the current processing conditions and the historical records or experimental data in the database is calculated to find the closest case.

[0098] Take the weighted Euclidean distance method as an example:

[0099] Given the current processing condition P = (p1, p2, ..., p n ), where n is the dimension of the processing condition, p i represents the value of the i-th processing condition;

[0100] A historical record or experimental data in the database is H = (h1, h2, ..., h n ); Weighted Euclidean distance between the current processing condition P and the data H in the database Among them, ω i is the weight of the i-th processing condition;

[0101] Sort the calculated weighted Euclidean distances from small to large, and select the smallest data as the most similar case.

[0102] Specifically, in step S2,

[0103] The system receives the currently used processing material, tool type and specific processing parameters, including: cutting speed, feed rate and cutting depth;

[0104] Configure the machining parameters required for simulation, cutting speed V c , feed speed f, cutting depth a p ;

[0105] Use finite element analysis or discrete element method numerical simulation technology to simulate the cutting process and obtain the key characteristics of spatter, including: spatter speed, spatter trajectory, spatter quantity;

[0106] The speed of the splash is estimated by the principle of conservation of energy. Among them, W c is the cutting power, m is the mass of spatter, and l is a coefficient related to cutting speed, feed rate, and cutting depth;

[0107] Use Newton's second law and the air resistance equation to simulate the trajectory of the splash:

[0108] in, is the position vector, is the acceleration due to gravity, k is the drag coefficient, is the velocity vector of the splash;

[0109] The relationship between the amount of spatter and cutting parameters can be fitted by experimental data Among them, a, b, c, and d are fitting coefficients.

[0110] The specific content of step S3 is to simulate the influence of the coolant spray mode and flow rate on the splashes and output the distribution map of the splashes. The purpose is to observe the influence of the coolant spray mode and flow rate on the splash behavior by changing the coolant spray mode and flow rate, so as to find the best coolant application strategy to reduce the generation and diffusion of splashes.

[0111] In step S3,

[0112] The flow of coolant is simulated by computational fluid dynamics software, and the effects of coolant injection angle, injection pressure and injection flow rate on coolant distribution are calculated;

[0113] Simulate the interaction between coolant and splash, including the cooling effect and impact effect of coolant on splash;

[0114] The coolant can slow down the speed of the splashes by increasing the resistance. Suppose the resistance F r and splash velocity V p is proportional to the square of r =k v V p , where k v is the drag coefficient, which depends on the properties of the coolant and the surface characteristics of the splash;

[0115] The speed of splash V p The relationship with time t is Among them, V p0 is the initial velocity of the splash;

[0116] The impact of the coolant changes the trajectory of the splashing objects, which can be simulated by adding an additional force term to Newton's second law, F = F g +F d +F c , where F g ,F d ,F c The force is gravity, air resistance and coolant impact;

[0117] Coolant can reduce the amount of spatter. Coolant helps stabilize the cutting area and reduce irregular fracture of the material. Among them, N s is the amount of splash after cooling, Q is the coolant flow rate;

[0118] As the coolant action time increases, the speed of the splashing material gradually decreases. By adjusting the coolant spray parameters including spray angle, pressure, and flow rate, k v value, thereby more effectively slowing down the speed of the splash and achieving the purpose of controlling the splash.

[0119] During the simulation, the system generates a series of data, including the location, speed, and quantity of splashes, which are updated over time;

[0120] Collect the x, y, z coordinates of all splashes at each time, as well as their speed and size characteristics;

[0121] Based on the above simulation results, a distribution map of the splash is generated.

[0122] In step S4, based on the simulation results of steps S1 to S3, a risk assessment is performed on the splashes to determine the protection priority level;

[0123] Identify risk indicators:

[0124] Splash velocity V p : High-speed splashing objects are more likely to cause harm;

[0125] Number of splashes N s : Large number of splashes increases potential risks;

[0126] Splash form M: Splashes of different forms have different effects on operators and equipment;

[0127] Splash size S: Large particle splashes may cause greater physical damage, while fine particles and mist splashes may cause harm to the respiratory system;

[0128] Distribution range R of splash: The wider the distribution range, the more difficult it is to protect and the higher the risk;

[0129] According to the above risk assessment indicators, assign weights to each indicator and calculate the total risk score: R s =ω v V p +ω n N s +ω m M+ω s S+ω R R, where ω v is the splash velocity weight, ω n is the splash weight, ω m is the splash shape weight, ω s is the splash size weight, ω R is the splash distribution range weight;

[0130] According to the calculated risk scores, the protection levels of different areas are ranked and the protection priority is determined; the priority levels are divided into three categories: low risk, medium risk, and high risk; the higher the risk score, the more dangerous it is.

[0131] In step S5, formulating protective measures includes:

[0132] Low-risk areas: Wear basic personal protective equipment; regularly inspect and maintain equipment to ensure it operates normally;

[0133] Medium-risk areas: Install transparent protective screens around machine tools to prevent splashes from flying directly toward operators; use local ventilation systems to reduce airborne particles and mist splashes; increase the amount of coolant sprayed to further reduce the generation of splashes;

[0134] High-risk areas: Install fully enclosed protective covers to ensure that operators are completely isolated from splashes; install efficient ventilation equipment to promptly exhaust air containing particles and mist splashes to prevent operators from inhaling harmful substances; set emergency stop buttons in high-risk areas to immediately stop machine operation if any abnormal situation is found.

[0135] Example systems:

[0136] A splash protection system for a machine tool, comprising:

[0137] Data collection and processing module, used to collect data such as physical and chemical properties of processing materials, basic information of tool types, and processing parameters;

[0138] A spatter prediction module is used to predict the type of spatter that may be generated during machine tool processing based on the collected data;

[0139] The spatter simulation module is used to combine the processing parameters, simulate the spatter generation under different processing conditions, and obtain the key characteristics of the spatter;

[0140] Coolant impact simulation module, used to simulate the impact of coolant spray on splashes and output the distribution map of splashes;

[0141] The risk assessment module is used to conduct risk assessment of splashes based on simulation results, determine the protection priority level, and calculate the risk score by comprehensively considering factors such as splash speed, quantity, shape, size and distribution range;

[0142] The protection level module ranks the protection levels of different areas according to risk scores;

[0143] The protection measures formulation module is used to formulate corresponding protection measures according to the protection priority level;

[0144] The monitoring module is used to monitor the generation and distribution of splashes in real time and issue early warnings.

[0145] The above is based on the ideal embodiment of the present invention. Through the above description, relevant personnel can make various changes and modifications without departing from the technical concept of the present invention. The technical scope of the present invention is not limited to the content in the specification, and the technical scope must be determined according to the scope of the claims.

Claims

1. A splash protection method for machine tools, characterized in that: Includes steps: S1. The system predicts the type of spatter that may be generated during machine tool processing based on the processing material and tool type; S2. Combine processing parameters to simulate the generation of spatter under different processing conditions and obtain the key characteristics of spatter; S3, simulating the effect of coolant spraying on splashes, and outputting a distribution map of the splashes; S4. Conduct risk assessment on splashes based on simulation results and determine the protection priority level; S5. Develop protective measures based on protection priority levels, and monitor the generation and distribution of splashes in real time to provide early warnings.

2. A splash protection method for machine tools according to claim 1, characterized in that: In step S1, S11. The system collects basic information about the physical and chemical properties of the processed materials, as well as the geometry, material, and cutting angle of different tool types; S12. Based on the collected basic information, combined with historical processing experience and experimental data, establish a database containing the types of spatter that may be generated under different processing materials, tool types and their combinations; S13. According to the current processing material, tool type and cutting parameters, the type of spatter that may be generated during the machine tool processing is predicted based on the database.

3. A splash protection method for machine tools according to claim 2, characterized in that: In step S13, the prediction step includes: Input the current processing materials and their physical and chemical properties into the system; Enter the type of tool currently being used and its geometry, material and cutting angle; According to the input processing material and tool type, similar historical records or experimental data are searched in the established spatter database; Match the retrieved historical records or experimental data with the current processing conditions to find the most similar cases.

4. A splash protection method for machine tools according to claim 3, characterized in that: By using the similarity matching method, the similarity between the current processing conditions and the historical records or experimental data in the database is calculated to find the closest case; Given the current processing condition P = (p1, p2, ..., p n ), where n is the dimension of the processing condition, p i represents the value of the i-th processing condition; A historical record or experimental data in the database is H = (h1, h2, ..., h n ); Weighted Euclidean distance between the current processing condition P and the data H in the database Among them, ω i is the weight of the i-th processing condition; Sort the calculated weighted Euclidean distances from small to large, and select the smallest data as the most similar case.

5. The splash protection method for machine tools according to claim 1, characterized in that: In step S2, The system receives the currently used processing material, tool type and specific processing parameters, including: cutting speed, feed rate and cutting depth; Configure the machining parameters required for simulation, cutting speed V c , feed speed f, cutting depth a p ; The cutting process is simulated using numerical simulation technology of finite element analysis or discrete element method to obtain the key characteristics of spatter, including: spatter velocity, spatter motion trajectory, and spatter quantity.

6. A splash protection method for machine tools according to claim 5, characterized in that: The velocity of the splash is estimated by the principle of conservation of energy. Among them, W c is the cutting power, m is the mass of spatter, and l is a coefficient related to cutting speed, feed rate, and cutting depth; Use Newton's second law and the air resistance equation to simulate the trajectory of the splash: in, is the position vector, is the acceleration due to gravity, k is the drag coefficient, is the velocity vector of the splash; The relationship between the amount of spatter and cutting parameters can be fitted by experimental data Among them, a, b, c, and d are fitting coefficients.

7. The splash protection method for machine tools according to claim 1, characterized in that: In step S3, The flow of coolant is simulated by computational fluid dynamics software, and the effects of coolant injection angle, injection pressure and injection flow rate on coolant distribution are calculated; Simulate the interaction between coolant and splash; The coolant slows down the speed of the splashes by increasing the resistance. Suppose the resistance F r and splash velocity V p is proportional to the square of r =k v V p , where k v is the drag coefficient, which depends on the properties of the coolant and the surface characteristics of the splash; The speed of splash V p The relationship with time t is Among them, V p0 is the initial velocity of the splash; The impact of the coolant changes the trajectory of the splashing objects, which can be simulated by adding an additional force term to Newton's second law, F = F g +F d +F c , where F g ,F d ,F c The force is gravity, air resistance and coolant impact; Coolant reduces the amount of spatter, coolant helps stabilize the cutting area and reduce irregular fracture of the material; Among them, N s is the amount of splash after cooling, and Q is the coolant flow rate.

8. The splash protection method for machine tools according to claim 7, characterized in that: In step S4, based on the simulation results of steps S1 to S3, a risk assessment is performed on the splashes to determine the protection priority level; Identify risk indicators: Splash velocity V p 、Number of splashes s , splash shape M, splash size S, splash distribution range R; Based on the risk indicators, assign weights to each indicator and calculate the overall risk score: R s =ω v V p +ω n N s +ω m M+ω s S+ω R R, where ω v is the splash velocity weight, ω n is the splash weight, ω m is the splash shape weight, ω s is the splash size weight, ω R is the splash distribution range weight.

9. A splash protection method for machine tools according to claim 8, characterized in that: According to the risk score, the protection levels of different areas of the machine tool are ranked to determine the protection priority; the priority levels are divided into three categories: low risk, medium risk, and high risk; The higher the risk score, the more dangerous it is.

10. A splash protection system for machine tools, based on the splash protection method and system for machine tools according to any one of claims 1 to 9, characterized in that: include: Data collection and processing module, used to collect data such as physical and chemical properties of processing materials, basic information of tool types, and processing parameters; A spatter prediction module is used to predict the type of spatter that may be generated during machine tool processing based on the collected data; The spatter simulation module is used to combine the processing parameters, simulate the spatter generation under different processing conditions, and obtain the key characteristics of the spatter; Coolant impact simulation module, used to simulate the impact of coolant spray on splashes and output the distribution map of splashes; The risk assessment module is used to conduct risk assessment of splashes based on simulation results, determine the protection priority level, and calculate the risk score by comprehensively considering factors such as splash speed, quantity, shape, size and distribution range; The protection level module ranks the protection levels of different areas according to risk scores; The protection measures formulation module is used to formulate corresponding protection measures according to the protection priority level; The monitoring module is used to monitor the generation and distribution of splashes in real time and issue early warnings.

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