Pick ball net rack pipe punching device

Abstract

The invention relates to the technical field of pipe punching, in particular to a Pick ball net rack pipe punching device which comprises the steps of building a hardness evaluation model, obtaining target pipe data based on the hardness evaluation model, conducting punching tests on historical pipe sets to obtain a punching frequency data set, and setting initial ultrasonic frequency according to the punching frequency data set. And the target pipe is punched on the basis of the target pipe data, the initial ultrasonic frequency and an intelligent punching unit in the punching device, a target punched pipe is obtained, an automatic chipping unit is used for chipping in real time, and the steps are repeated till all punching positions are punched. The punching precision of the Pick ball net rack pipe can be improved, and the intelligent degree of pipe punching is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of pipe punching, in particular to a Pickleball net rack pipe punching device. BACKGROUND

[0002] With the popularity of Pickleball sports worldwide, the demand for Pickleball net rack construction and maintenance is growing, and the quality of Pickleball net rack pipe punching directly affects the stability and safety of the net rack, which is a key link to ensure the smooth progress of the game and the safety of athletes. Therefore, precise and efficient punching technology is of great significance to improve the professionalism and durability of Pickleball venue facilities.

[0003] Traditional Pickleball net rack pipe punching devices mostly use mechanical die stamping method, which can achieve basic punching function, but the punching precision is insufficient, which will affect the tightness and stability of the net rack assembly, and this method is difficult to guarantee the punching effect when facing pipe materials of different hardness and thickness, and is prone to problems such as burr and deformation, and the intelligent degree needs to be improved. SUMMARY

[0004] The present application provides a Pickleball net rack pipe punching device, which mainly aims to improve the precision of Pickleball net rack pipe punching and improve the intelligent degree of pipe punching.

[0005] To achieve the above purpose, the Pickleball net rack pipe punching device provided by the present application comprises: receiving a pipe punching instruction, determining a target pipe based on the pipe punching instruction, wherein the target pipe is a Pickleball net rack pipe; constructing a hardness evaluation model based on the pre-acquired material database, performing data analysis on the target pipe based on the hardness evaluation model to obtain target pipe data, wherein the hardness evaluation model is a neural network model, and the target pipe data includes target pipe hardness value, hole position group and pipe thickness; obtaining a historical pipe group, performing a punching test on the historical pipe group to obtain a punching frequency data set, wherein the punching frequency data set includes multiple punching frequency data, and the punching frequency data includes historical pipe hardness value, hole deviation value and historical punching frequency; confirming the punching device, wherein the punching device includes an automatic debris unit and an intelligent punching unit, wherein the automatic debris unit includes a debris container, a suction fan and a push rod, and the intelligent punching unit includes an ultrasonic generator, a punching tool, a laser displacement sensor and a fixing clamp; setting the initial ultrasonic frequency of the target pipe according to the punching frequency data set; extracting a first hole position from the hole position group, and punching the target pipe based on the first hole position, the target pipe data, an initial ultrasonic frequency, and an intelligent punching unit in the punching device to obtain a target punched pipe; In the step of punching the target pipe, the automatic debris unit in the punching device is used for real-time debris until the punching is completed. The first hole position is removed from the hole position group to obtain a removed hole position group. The removed hole position group and the target punched pipe are taken as the hole position group and the target pipe respectively, and the step of extracting the first hole position from the hole position group is returned until the hole position group is empty, and the pipe punching is completed.

[0006] Optionally, the hardness evaluation model is constructed according to the pre-acquired material database, comprising: collecting a basic material set in the material database, wherein the basic material set includes a plurality of basic materials, and each basic material has a material attribute record in the material database; identifying a basic attribute group set of each basic material in the basic material set, wherein the basic attribute group set includes a plurality of basic attribute groups, and each basic attribute group corresponds to one basic material in the basic material set; acquiring a test pipe group based on the basic material set, wherein the test pipe group includes a plurality of test pipes, and each test pipe is prepared from one or more basic materials in the basic material set; extracting the test pipes in the test pipe group in turn, and cutting the test pipes to obtain a plurality of test pipe samples; measuring the hardness of the plurality of test pipe samples using a pre-acquired hardness tester to obtain a plurality of sample hardness values, and calculating the mean value of the plurality of sample hardness values to obtain a test pipe hardness value; constructing test pipe data of the test pipe based on the test pipe hardness value, the basic attribute group set, and the basic material set; summarizing the test pipe data corresponding to each test pipe in the test pipe group to obtain a test pipe data set; training a pre-constructed neural network using the test pipe data set to obtain a hardness evaluation model.

[0007] Optionally, the test pipe data of the test pipe is constructed based on the test pipe hardness value, the basic attribute group set, and the basic material set, comprising: identifying a plurality of similar materials corresponding to the test pipe in the basic material set, confirming a test material proportion group of the plurality of similar materials in the test pipe, and constructing a test material proportion vector based on the test material proportion group; identify a plurality of same-material attribute groups corresponding to the plurality of same materials in the basic attribute group set, and construct a test pipe material attribute vector according to the plurality of same-material attribute groups; construct a test pipe material feature vector based on the test material proportion vector and the test pipe material attribute vector; merge the test pipe material hardness value and the test pipe material feature vector to obtain test pipe material data.

[0008] Optionally, the data analysis on the target pipe material based on the hardness evaluation model obtains target pipe material data, including: perform size measurement on the target pipe material to obtain an opening position group and a pipe thickness; identify a preparation material group of the target pipe material, wherein the preparation material group includes one or more preparation materials; perform hardness evaluation on the target pipe material based on the preparation material group and the hardness evaluation model to obtain a target pipe material hardness value; merge the opening position group, the pipe thickness, and the pipe hardness value to obtain target pipe material data.

[0009] Optionally, the hardness evaluation on the target pipe material based on the preparation material group and the hardness evaluation model obtains a target pipe material hardness value, including: extract a preparation material from the preparation material group in sequence, and query a target material attribute group of the preparation material in a material database; confirm a target material proportion of the preparation material in the target pipe material; collect the target material attribute group and the target material proportion respectively to obtain a target material attribute group set and a target material proportion group, construct a target pipe material attribute vector based on the target material attribute group set, and construct a target material proportion vector according to the target material proportion group; construct a target pipe material feature vector based on the target pipe material attribute vector and the target material proportion vector; input the target pipe material feature vector into the hardness evaluation model to obtain a target pipe material hardness value.

[0010] Optionally, the piercing test on the historical pipe material group obtains a piercing frequency data set, including: extract a historical pipe material from the historical pipe material group in sequence, and determine a historical pipe material hardness value of the historical pipe material; set a historical piercing frequency; pierce the historical pipe material based on the historical piercing frequency to obtain a historical pierced pipe material; confirm a real-time hole in the historical pierced pipe material, and measure the real-time hole to obtain a historical hole diameter group; calculate a hole deviation value based on the historical hole diameter group and a preset standard hole diameter; Merge the historical pipe material hardness value, hole deviation value and historical punching frequency to obtain the punching frequency data; Adjust the historical punching frequency to obtain an adjusted punching frequency, take the adjusted punching frequency and the historical punching pipe material as the historical punching frequency and the historical pipe material respectively, and return to the step of punching the historical pipe material based on the historical punching frequency until the number of holes in the historical pipe material is equal to the preset standard hole number; Summarize the punching frequency data corresponding to the historical pipe material to obtain a punching frequency data set, and merge the punching frequency data set corresponding to each historical pipe material in the historical pipe material group to obtain a punching frequency data set.

[0011] Optionally, the ultrasonic frequency setting of the target pipe material according to the punching frequency data set obtains an initial ultrasonic frequency, which comprises: Extract the punching frequency data in the punching frequency data set in turn, and calculate the punching similarity according to the hardness value of the target pipe material and the hardness value of the historical pipe material in the punching frequency data; Calculate the deviation weight value according to the hole deviation value in the punching frequency data; Summarize the punching similarity and the deviation weight value respectively to obtain a punching similarity set and a deviation weight value set, and normalize the punching similarity set and the deviation weight value set respectively to obtain a normalized punching similarity set and a normalized deviation weight value set; Calculate the initial ultrasonic frequency according to the normalized punching similarity set and the normalized deviation weight value set, wherein the initial ultrasonic frequency is represented as: Wherein, represents the initial ultrasonic frequency, represents a preset similarity coefficient, represents a preset deviation coefficient, n represents the number of normalized punching similarities in the normalized punching similarity set or the number of normalized deviation weight values in the normalized deviation weight value set, represents the first normalized punching similarity in the normalized punching similarity set, represents the historical punching frequency in the first punching frequency data in the punching frequency data set, represents the first normalized deviation weight value in the normalized deviation weight value set, represents the historical punching frequency in the first punching frequency data.

[0012] Optionally, the target pipe material is punched based on the first hole position, the target pipe material data, the initial ultrasonic frequency and the intelligent punching unit in the punching device to obtain a target punched pipe material, which comprises: Fix the target pipe based on the first hole position and the fixed clamp in the intelligent punching unit to obtain a fixed pipe; Set an initial punching time; Based on the initial ultrasonic frequency and the initial punching time, and using an ultrasonic generator and a punching tool to perform single punching on the fixed pipe to obtain a punched pipe, wherein the frequency of the ultrasonic generator is the initial ultrasonic frequency; According to the initial punching time and a preset sampling interval, calculate a target punching time; Based on the laser displacement sensor in the intelligent punching unit, detect the real-time punching depth of the punched pipe, and use the pre-constructed vibration sensor to monitor the vibration of the fixed pipe during the step of using the ultrasonic generator and the punching tool to perform single punching on the fixed pipe to obtain a real-time vibration value; According to the real-time punching depth and the real-time vibration value, adjust the initial ultrasonic frequency to obtain an adjusted ultrasonic frequency; Take the adjusted ultrasonic frequency, the target punching time, and the punched pipe as the initial ultrasonic frequency, the initial punching time, and the fixed pipe respectively, and return to the step of using the ultrasonic generator and the punching tool to perform single punching on the fixed pipe based on the initial ultrasonic frequency and the initial punching time until the real-time punching depth is equal to the pipe thickness in the target pipe data; When the real-time punching depth is equal to the pipe thickness, record the punched pipe as the target punched pipe.

[0013] Optionally, the step of adjusting the initial ultrasonic frequency according to the real-time punching depth and the real-time vibration value to obtain an adjusted ultrasonic frequency comprises: According to the real-time punching depth and the sampling interval, calculate an instantaneous punching speed; Use the laser displacement sensor to measure the current punching depth, and calculate the to-be-punched depth according to the target punching depth and the current punching depth, wherein the to-be-punched depth is the difference between the target punching depth and the current punching depth; According to the to-be-punched depth and the instantaneous punching speed, calculate a to-be-punched time length, and based on the to-be-punched time length and a preset current punching time length, calculate a predicted punching time length; According to the predicted punching time length, the real-time vibration value, and the initial ultrasonic frequency, and using the following formula to calculate the adjusted ultrasonic frequency: Wherein, represents the adjusted ultrasonic frequency, represents the predicted punching time length, represents the current punching time length, represents the preset standard punching time length, represents the logarithmic function with base 10, represents the preset standard vibration value, represents a real-time vibration value, represents a preset minimum value.

[0014] To achieve the above object, the application further provides a picket ball net rack pipe punching system, comprising: The pipe data acquisition module is configured to receive a pipe punching instruction, determine a target pipe based on the pipe punching instruction, wherein the target pipe is a picket ball net rack pipe, construct a hardness evaluation model based on a pre-acquired material database, perform data analysis on the target pipe based on the hardness evaluation model, and obtain target pipe data, wherein the hardness evaluation model is a neural network model, and the target pipe data includes a target pipe hardness value, a hole position group, and a pipe thickness. The frequency data test module is configured to obtain a historical pipe group, perform a punching test on the historical pipe group, and obtain a punching frequency data set, wherein the punching frequency data set includes a plurality of punching frequency data, and the punching frequency data includes a historical pipe hardness value, a hole deviation value, and a historical punching frequency, and the punching device is confirmed, wherein the punching device includes an automatic debris unit and an intelligent punching unit, the automatic debris unit includes a debris container, a suction fan, and a push rod, and the intelligent punching unit includes an ultrasonic generator, a punching tool, a laser displacement sensor, and a fixed clamp. The target pipe punching module is configured to set an initial ultrasonic frequency for the target pipe based on the punching frequency data set, extract a first hole position from the hole position group, punch the target pipe based on the first hole position, the target pipe data, the initial ultrasonic frequency, and the intelligent punching unit in the punching device, and obtain a target punched pipe. The punching debris cleaning module is configured to use the automatic debris unit in the punching device to clean the debris in real time until the punching is completed, remove the first hole position from the hole position group to obtain a removed hole position group, and use the removed hole position group and the target punched pipe as the hole position group and the target pipe, respectively, and return to the step of extracting the first hole position from the hole position group until the hole position group is an empty set.

[0015] To solve the above problems, the application further provides an electronic device, which comprises: a memory storing at least one instruction; a processor executing the instructions stored in the memory to implement the picket ball net rack pipe punching device described above.

[0016] To solve the above problems, the application further provides a computer-readable storage medium having at least one instruction stored therein, which is executed by a processor in an electronic device to implement the picket ball net rack pipe punching device described above.

[0017] The present application is to solve the problems described in the background art, first, according to the material database, a hardness evaluation model is constructed, and data analysis is performed on the target pipe based on the hardness evaluation model to obtain target pipe data. This step can estimate the hardness value of the target pipe in advance by establishing a hardness evaluation model, providing key parameters for subsequent punching operation, avoiding contact hardness measurement of the target pipe, and improving the efficiency and quality of punching. Then, a historical pipe group is obtained, and a punching test is performed on the historical pipe group to obtain a punching frequency data set. This step can accumulate rich experimental data, which helps to improve the accuracy of subsequent ultrasonic frequency setting and improve the punching effect and efficiency. In addition, the present application introduces an automatic debris unit and an intelligent punching unit. The automatic debris unit can clean debris in real time to ensure the cleanliness of the punching environment and avoid the impact of debris accumulation on punching. The intelligent punching unit can realize high-precision punching operation and improve the punching quality. Further, according to the punching frequency data set, the ultrasonic frequency of the target pipe is set to obtain the initial ultrasonic frequency. This step uses historical data to provide a reasonable reference for the current punching task, which can quickly find the punching frequency suitable for the target pipe, thereby improving the punching efficiency and quality. Then, based on the first hole position, target pipe data, initial ultrasonic frequency and intelligent punching unit in the punching device, the target pipe is punched to obtain the target punched pipe. This step uses the intelligent punching unit combined with a laser displacement sensor and vibration monitoring to monitor the punching depth and vibration value in real time and adjust the ultrasonic frequency, realizing high-precision and stable punching operation. Finally, the automatic debris unit in the punching device is used to clean debris in real time until the punching is completed. The automatic debris unit helps to maintain the cleanliness of the punching area, avoiding problems such as punching position deviation, tool wear and hole size deviation caused by debris accumulation, and improving the quality of the pipe. Therefore, the present application can improve the precision of the picket ball net frame pipe punching and improve the intelligent degree of the pipe punching. BRIEF DESCRIPTION OF DRAWINGS

[0018] Figure 1 The flowchart of the picket ball net frame pipe punching device provided by an embodiment of the present application is shown. Figure 2 The functional module diagram of the picket ball net frame pipe punching system provided by an embodiment of the present application is shown. Figure 3 The structural diagram of the electronic device for realizing the picket ball net frame pipe punching device provided by an embodiment of the present application is shown.

[0019] Explanation of reference signs: 1, electronic device; 10, processor; 11, memory; 12, bus; 100, picket ball net frame pipe punching system; 101, pipe data acquisition module; 102, frequency data test module; 103, target pipe punching module; 104, punching debris cleaning module.

[0020] The objectives, functional characteristics and advantages of the present application will be further illustrated in conjunction with the embodiments, with reference to the accompanying drawings. DETAILED DESCRIPTION

[0021] It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.

[0022] Embodiments of the present application provide a Pickleball net rack pipe punching device. The execution body of the Pickleball net rack pipe punching device includes but is not limited to at least one of the electronic devices 1 capable of being configured to execute the device provided by the embodiments of the present application, such as a server, a terminal, etc. In other words, the Pickleball net rack pipe punching device can be executed by software or hardware installed in a terminal device or a server device, and the software can be a blockchain platform. The server includes but is not limited to a single server, a server cluster, a cloud server, or a cloud server cluster, etc.

[0023] Reference Figure 1 As shown in the flowchart of the Pickleball net rack pipe punching device provided by an embodiment of the present application. In this embodiment, the Pickleball net rack pipe punching device includes: S1, receiving a pipe punching instruction, determining a target pipe based on the pipe punching instruction, wherein the target pipe is a Pickleball net rack pipe.

[0024] It can be understood that the pipe punching instruction refers to a human-initiated instruction for punching a specific pipe, and the target pipe refers to the specific pipe indicated in the pipe punching instruction.

[0025] S2, constructing a hardness evaluation model according to a pre-acquired material database, performing data analysis on the target pipe based on the hardness evaluation model, and obtaining target pipe data, wherein the hardness evaluation model is a neural network model, and the target pipe data includes target pipe hardness value, hole position group, and pipe thickness.

[0026] It can be understood that the material database refers to a database containing a plurality of material articles and material literature, and relevant personnel can query the attribute values of each material through the material database, wherein the material refers to a material that can be used to prepare the pipe, for example: a certain material database is ASM material database, and a certain material that can be used to prepare the pipe is found in the material database: 6061 aluminum alloy.

[0027] It needs to be explained that the hardness evaluation model refers to a model capable of automatically evaluating the hardness of the target pipe material, and the model is a neural network model. The target pipe hardness value refers to a numerical value quantifying the hardness of the target pipe material. The greater the target pipe hardness value, the greater the hardness of the target pipe material. The target pipe hardness value is related to the materials of the target pipe material and the mass ratio of each material. The hole position group includes multiple hole positions, wherein the hole position refers to the position that needs to be punched on the surface of the target pipe material. The pipe thickness refers to the thickness of the target pipe material. The standard hole diameter refers to the diameter of the hole to be punched on the surface of the target pipe material.

[0028] In detail, the hardness evaluation model is constructed according to the pre-acquired material database, including: Collecting a basic material set in the material database, wherein the basic material set includes multiple basic materials, and each basic material has a material attribute record in the material database; Identifying a basic attribute group set of each basic material in the basic material set, wherein the basic attribute group set includes multiple basic attribute groups, and each basic attribute group corresponds to one basic material in the basic material set; Obtaining a test pipe material group based on the basic material set, wherein the test pipe material group includes multiple test pipe materials, and each test pipe material is prepared from one or more basic materials in the basic material set; Extracting the test pipe materials in the test pipe material group in sequence, and cutting the test pipe materials to obtain multiple test pipe samples; Measuring the hardness of the multiple test pipe samples using a pre-acquired hardness tester to obtain multiple sample hardness values, and calculating the mean value of the multiple sample hardness values to obtain a test pipe hardness value; Based on the test pipe hardness value, the basic attribute group set, and the basic material set, constructing test pipe data of the test pipe material; Summarizing the test pipe data corresponding to each test pipe material in the test pipe material group to obtain a test pipe data set; Training the pre-constructed neural network using the test pipe data set to obtain a hardness evaluation model.

[0029] It can be understood that the basic material set includes a plurality of basic materials, wherein the basic material refers to a material contained in the material database and capable of being used to prepare the pipe material, for example: 304 stainless steel, 7075 aluminum alloy, Ti-6Al-4V titanium alloy, and the collection step of the basic material set is collected by the relevant research and development personnel. The basic attribute group set includes a plurality of basic attribute groups, and the basic attribute group refers to a combination of numerical values capable of representing the attribute of the basic material in each direction, for example: the attributes in the basic attribute group can be defined as: elastic modulus (GPa), Poisson's ratio, yield strength (MPa), and each basic attribute group contained in the basic attribute group set is (elastic modulus, Poisson's ratio, yield strength).

[0030] It needs to be explained that the test pipe material group includes a plurality of test pipe materials, which refers to the pipe material prepared from one or more basic materials, which can be obtained by preparation or by querying the data of the pipe material prepared in the past. The test pipe sample refers to a part of the test pipe after cutting, wherein the cutting refers to the artificial cutting of the test pipe. The hardness tester refers to an instrument for measuring the hardness of the material, for example: Leeb hardness tester (LHT-1000). The sample hardness value refers to the hardness value of the test pipe sample after detection by the hardness tester, and each sample hardness value corresponds to a test pipe sample. The test pipe hardness value refers to the average value of a plurality of sample hardness values. The test pipe data refers to the data quantifying the characteristics of the test pipe material components. The neural network refers to a computational model simulating the structure of human brain neurons, and the neural network is selected as: BP neural network.

[0031] In detail, based on the test pipe hardness value, the basic attribute group set and the basic material set, the test pipe data of the test pipe is constructed, including: Identify a plurality of similar materials corresponding to the test pipe in the basic material set, confirm a test material proportion group of the plurality of similar materials in the test pipe, and construct a test material proportion vector based on the test material proportion group; Identify a plurality of similar material attribute groups corresponding to the plurality of similar materials in the basic attribute group set, and construct a test pipe attribute vector according to the plurality of similar material attribute groups; Based on the test material proportion vector and the test pipe attribute vector, a test pipe feature vector is constructed; The test pipe hardness value and the test pipe feature vector are combined to obtain the test pipe data.

[0032] It can be understood that the plurality of same materials refers to a plurality of base materials used to prepare the test pipe material in the base material set. The test material ratio group refers to the combination of the mass ratio of the plurality of same materials in the preparation of the test pipe material. The test material ratio vector refers to a vector composed of the test material ratio group, wherein the vector elements in the test material ratio vector correspond one-to-one to the test material ratio in the test material ratio group. The same material attribute group refers to the base attribute group corresponding to the same material. The test pipe material attribute vector refers to a vector composed of a plurality of same material attribute groups. It should be noted that the vector dimension of the test pipe material attribute vector is: , the vector dimension of the test material ratio vector is: , wherein, represents the maximum value of the number of same materials corresponding to the test pipe material in the test pipe material group, represents the number of base attributes in the base attribute group. Since different test pipe materials correspond to different same materials, the number of same material attribute groups corresponding to the test pipe material is also different. In order to ensure that the dimension of the input data (i.e. the test pipe material feature vector) in the subsequent training process is the same, the dimensions of the test pipe material attribute vector and the test material ratio vector are fixed.

[0033] For example, the test pipe material is composed of two same materials, the test material ratios corresponding to the two materials are 30% and 70% respectively, and the two same material attribute groups corresponding to them are: same material attribute group 1: (attribute A1, attribute B1, attribute C1), same material attribute group 2: (attribute A2, attribute B2, attribute C2), and the vector dimensions of the test material ratio vector and the test pipe material attribute vector are 3 and 9 respectively. The test material ratio vector and the test pipe material attribute vector are constructed as (0.3, 0.7, 0) (attribute A1, attribute B1, attribute C1, attribute A2, attribute B2, attribute C2, 0, 0, 0), that is, the spare vector position is supplemented with 0 value.

[0034] Further, the test pipe material feature vector refers to a vector composed of the test material ratio vector and the test pipe material attribute vector, wherein the test pipe material feature vector is constructed by supplementing the test material ratio vector to the end of the test pipe material attribute vector, thereby obtaining the test pipe material feature vector, for example: , wherein C represents the test pipe material feature vector, A represents the test pipe material attribute vector, and B represents the test material ratio vector.

[0035] In detail, the data analysis of the target pipe material based on the hardness evaluation model obtains the target pipe material data, including: Carrying out size measurement on the target pipe material to obtain a hole position group and a pipe thickness; Identifying a preparation material group of the target pipe material, wherein the preparation material group comprises one or more preparation materials; Carrying out hardness evaluation on the target pipe material based on the preparation material group and a hardness evaluation model to obtain a target pipe hardness value; Merging the hole position group, the pipe thickness and the target pipe hardness value to obtain target pipe data.

[0036] It can be understood that the size measurement refers to manual measurement by relevant operating personnel. The preparation material refers to a material used for preparing the target pipe material, and the preparation material is included in a base material set.

[0037] In detail, the hardness evaluation on the target pipe material based on the preparation material group and the hardness evaluation model to obtain the target pipe hardness value comprises: Extracting preparation materials in the preparation material group in sequence, and querying a target material attribute group of the preparation materials in a material database; Confirming a target material proportion of the preparation materials in the target pipe material; Respectively collecting the target material attribute group and the target material proportion to obtain a target material attribute group set and a target material proportion group, constructing a target pipe attribute vector based on the target material attribute group set, and constructing a target material proportion vector according to the target material proportion group; Constructing a target pipe feature vector based on the target pipe attribute vector and the target material proportion vector; Inputting the target pipe feature vector into the hardness evaluation model to obtain the target pipe hardness value.

[0038] It can be understood that the target material attribute group refers to a base attribute group corresponding to the preparation material, and the target material proportion refers to a mass proportion of the preparation material in the target pipe material. The construction manners of the target pipe attribute vector, the target material proportion vector and the target pipe feature vector are the same as those of the test pipe attribute vector, the test material proportion vector and the test pipe feature vector, and will not be described herein.

[0039] Further, the hardness evaluation model is used to obtain the target pipe hardness value, so that it is not necessary to carry out hardness measurement on the target pipe material, thereby avoiding damage to the target pipe material.

[0040] S3, obtaining a historical pipe group, carrying out a punching test on the historical pipe group to obtain a punching frequency data set, wherein the punching frequency data set comprises a plurality of punching frequency data, and the punching frequency data comprises a historical pipe hardness value, a hole deviation value and a historical punching frequency.

[0041] It can be understood that the historical pipe material group includes a plurality of historical pipe materials, wherein the historical pipe material refers to a pipe material artificially constructed for a piercing test or a pipe material with relevant piercing data recorded in the past period, and the composition material of the historical pipe material should also be in the base material set. The piercing test refers to piercing each historical pipe material in the historical pipe material group. The piercing frequency data refers to the data recorded in the piercing test, wherein the historical pipe material hardness value refers to the pipe material hardness value of the historical pipe material. The hole deviation value refers to a value quantifying the piercing effect, and the larger the hole deviation value, the worse the piercing effect. The historical piercing frequency refers to the ultrasonic frequency of the ultrasonic generator recorded in the piercing process.

[0042] In detail, the piercing test on the historical pipe material group to obtain the piercing frequency data set includes: extracting the historical pipe material in the historical pipe material group in turn, and determining the historical pipe material hardness value of the historical pipe material; setting the historical piercing frequency; piercing the historical pipe material based on the historical piercing frequency to obtain the historical piercing pipe material; confirming the real-time hole in the historical piercing pipe material, measuring the real-time hole to obtain the historical hole diameter group; calculating the hole deviation value based on the historical hole diameter group and the preset standard hole diameter; merging the historical pipe material hardness value, the hole deviation value and the historical piercing frequency to obtain the piercing frequency data; adjusting the historical piercing frequency to obtain the adjusted piercing frequency, taking the adjusted piercing frequency and the historical piercing pipe material as the historical piercing frequency and the historical pipe material respectively, and returning to the step of piercing the historical pipe material based on the historical piercing frequency until the number of holes in the historical pipe material is equal to the preset standard hole number; summarizing the piercing frequency data corresponding to the historical pipe material to obtain the piercing frequency data group, and merging the piercing frequency data group corresponding to each historical pipe material in the historical pipe material group to obtain the piercing frequency data set.

[0043] It can be understood that the historical pipe material hardness value refers to the pipe material hardness value of the historical pipe material, and the acquisition method of the historical pipe material hardness value is the same as that of the target pipe material hardness value. The historical piercing frequency refers to the frequency artificially set according to experience, which is used to guide the ultrasonic generator in the intelligent piercing unit to work. The historical piercing pipe material refers to the historical pipe material after piercing, wherein piercing refers to punching a hole on the surface of the historical pipe material. The historical hole diameter group refers to the combination of the diameters of the real-time holes at different thicknesses. The standard hole diameter refers to the diameter of the hole artificially set to be punched on the surface of the historical pipe material. The calculation method of the hole deviation value is as follows: wherein, hole deviation value, kth hole diameter in the historical hole diameter group, kth hole diameter in the historical hole diameter group, standard hole diameter, denotes taking absolute value. The adjusted piercing frequency refers to the historical piercing frequency after adjustment, wherein the adjustment is made by human, and optionally, the adjustment is made according to the following formula: wherein, denotes adjusted piercing frequency, denotes initial piercing frequency, denotes human-set frequency growth rate, and The standard hole number refers to a human-set constant, which represents the maximum number of holes present on a historical pipe surface.

[0044] S4, confirming the piercing device, wherein the piercing device comprises an automatic debris unit and an intelligent piercing unit, wherein the automatic debris unit comprises a debris container, a suction fan and a push rod, and the intelligent piercing unit comprises an ultrasonic generator, a piercing tool, a laser displacement sensor and a fixing clamp.

[0045] It can be understood that the piercing device refers to a device for piercing a pipe. The automatic debris unit refers to a device capable of cleaning debris generated in the piercing step in real time. The unit comprises a debris container, a suction fan and a push rod, wherein the debris container refers to a container for containing debris generated in the piercing step, the suction fan refers to a device installed in the debris container for sucking debris into the debris container, the push rod is connected with the debris container and can push the debris container to move, and when a certain hole position in the target pipe is completed, the push rod can push the debris container to the position below the next hole position to be pierced.

[0046] Further, the intelligent piercing unit refers to a device capable of piercing, which comprises an ultrasonic generator, a piercing tool, a laser displacement sensor and a fixing clamp, wherein the ultrasonic generator refers to a device for generating high-frequency ultrasonic waves, for example, a 2000W ultrasonic generator (frequency range 20kHz-40kHz), the piercing tool refers to a punch installed at the output end of the ultrasonic generator, for example, a hard alloy punch, the ultrasonic generator and the piercing tool are connected to pierce the target pipe, and the purpose of using ultrasonic waves for piercing is to reduce the piercing resistance, reduce material deformation and burrs, and thus improve the piercing precision. The laser displacement sensor refers to a device capable of detecting the depth of piercing during the piercing process. The fixing clamp refers to a device for fixing the target pipe.

[0047] S5. According to the punching frequency data set, the ultrasonic frequency is set for the target pipe to obtain the initial ultrasonic frequency.

[0048] It is understandable that the initial ultrasonic frequency refers to the frequency of the ultrasonic generator when punching the target pipe subsequently.

[0049] In detail, the ultrasonic frequency setting of the target pipe is performed according to the punching frequency data set to obtain the initial ultrasonic frequency, including: Extracting punching frequency data in sequence from the punching frequency data set, and calculating punching similarity based on the target pipe hardness value and the historical pipe hardness values ​​in the punching frequency data; Calculate the deviation weight value according to the hole deviation value in the punching frequency data; The punching similarities and deviation weight values ​​are summarized respectively to obtain a punching similarity set and a deviation weight value set, and the punching similarity set and the deviation weight value set are normalized respectively to obtain a normalized punching similarity set and a normalized deviation weight value set; The initial ultrasonic frequency is calculated based on the normalized punching similarity set and the normalized deviation weight value set, where the initial ultrasonic frequency is expressed as: ,in, represents the initial ultrasonic frequency, Represents the preset similarity coefficient, represents the preset deviation coefficient, n represents the number of normalized punching similarities in the normalized punching similarity set or the number of normalized deviation weight values ​​in the normalized deviation weight value set, represents the first A normalized punching similarity, Indicates the number of The historical punching frequency in the punching frequency data, Indicates the first A normalized deviation weight value, Indicates the The historical punching frequency in the punching frequency data.

[0050] It can be understood that the punching similarity refers to a numerical value that quantifies the similarity between the target pipe hardness value and the historical pipe hardness value. The greater the punching similarity, the higher the similarity between the target pipe hardness value and the historical pipe hardness value. The punching similarity is calculated as follows: ,in, represents the punching similarity, Indicates the target pipe hardness value, Indicates the historical pipe hardness value. The deviation weight value refers to the value used to calculate the weight of the quantitative hole deviation value when subsequently calculating the initial ultrasonic frequency. The deviation weight value is calculated as follows: wherein, represents a deviation weight value, represents an exponential function with a natural constant as a base, represents a hole deviation value. The normalized hole similarity set and the normalized deviation weight value set respectively refer to a hole similarity set and a deviation weight value set after normalization. The similarity coefficient refers to a constant artificially set for the weight of the normalized hole similarity in calculating the initial ultrasonic frequency, and the deviation coefficient refers to a constant artificially set for the weight of the normalized deviation weight value in calculating the initial ultrasonic frequency, wherein, optionally, are respectively set to 0.6 and 0.4.

[0051] S6, extracting a first hole position in the hole position group, and punching the target pipe based on the first hole position, the target pipe data, the initial ultrasonic frequency and the intelligent punching unit in the punching device to obtain a target punched pipe.

[0052] It can be understood that the first hole position refers to the hole position arranged at the first position in the hole position group. The target punched pipe refers to the target pipe that has completed punching at the first hole position.

[0053] In detail, the punching of the target pipe based on the first hole position, the target pipe data, the initial ultrasonic frequency and the intelligent punching unit in the punching device to obtain the target punched pipe comprises: fixing the target pipe based on the first hole position and a fixed clamp in the intelligent punching unit to obtain a fixed pipe; setting an initial punching time; based on the initial ultrasonic frequency and the initial punching time, and using an ultrasonic generator and a punching tool to perform single punching on the fixed pipe to obtain a punched pipe, wherein the frequency of the ultrasonic generator is the initial ultrasonic frequency; calculating a target punching time according to the initial punching time and a preset sampling interval; based on a laser displacement sensor in the intelligent punching unit, detecting a real-time punching depth of the punched pipe, and using a pre-constructed vibration sensor to perform vibration monitoring on the fixed pipe in the step of using the ultrasonic generator and the punching tool to perform single punching on the fixed pipe to obtain a real-time vibration value; adjusting the initial ultrasonic frequency according to the real-time punching depth and the real-time vibration value to obtain an adjusted ultrasonic frequency; adjusting the ultrasonic frequency, the target piercing time and the piercing pipe material as the initial ultrasonic frequency, the initial piercing time and the fixed pipe material respectively, and returning to the step of performing single piercing on the fixed pipe material based on the initial ultrasonic frequency and the initial piercing time by using the ultrasonic generator and the piercing tool until the real-time piercing depth is equal to the pipe thickness in the target pipe data; When the real-time piercing depth is equal to the pipe thickness, the piercing pipe material is recorded as the target piercing pipe material.

[0054] It can be understood that the fixed pipe material refers to the target pipe material after being fixed. The initial piercing time refers to a time constant artificially set, which represents the starting time of single piercing. The single piercing refers to piercing the fixed pipe material once, and the piercing time is , wherein represents the sampling interval. The piercing pipe material refers to the fixed pipe material after single piercing. The sampling interval refers to a constant artificially set. The target piercing time refers to the time after the sampling interval from the initial piercing time. The real-time piercing depth refers to the depth of the fixed pipe material pierced during single piercing. The calculation of the real-time piercing depth can be: detecting the thickness of the fixed pipe material pierced, detecting the thickness of the piercing pipe material pierced, and subtracting the thickness of the fixed pipe material pierced from the thickness of the piercing pipe material pierced to obtain the real-time piercing depth, wherein the above detection is detected by using a laser displacement sensor.

[0055] Further, the real-time vibration value refers to the average vibration amplitude of the surface of the fixed pipe material in the single piercing step, and the unit is: mm (millimeter). The adjusted ultrasonic frequency refers to the initial ultrasonic frequency after adjustment. Since the vibration amplitude of the fixed pipe material will affect the piercing effect, the adjusted ultrasonic frequency needs to be calculated combined with the real-time vibration value.

[0056] In detail, the initial ultrasonic frequency is adjusted according to the real-time piercing depth and the real-time vibration value to obtain the adjusted ultrasonic frequency, including: calculating the instantaneous piercing speed according to the real-time piercing depth and the sampling interval; measuring the current piercing depth by using a laser displacement sensor, calculating the to-be-pierced depth according to the target piercing depth and the current piercing depth, wherein the to-be-pierced depth is the difference between the target piercing depth and the current piercing depth; calculating the to-be-pierced time length according to the to-be-pierced depth and the instantaneous piercing speed, and calculating the predicted piercing time length based on the to-be-pierced time length and the preset current piercing time length; calculating the adjusted ultrasonic frequency according to the predicted piercing time length, the real-time vibration value and the initial ultrasonic frequency by using the following formula: , wherein represents the adjusted ultrasonic frequency, represents the predicted piercing time length, Indicates the current punching time. Indicates the preset standard punching time. represents the logarithmic function with base 10, Indicates the preset standard vibration value, Indicates the real-time vibration value, Indicates the preset minimum value.

[0057] It should be explained that the instantaneous punching speed refers to the speed of punching during a single punching, and its calculation method is: the real-time punching depth divided by the sampling interval. The current punching depth refers to the thickness of the punched pipe. The depth to be punched refers to the depth that still needs to be punched. The time to be punched refers to the time required to complete the punching according to the instantaneous punching speed, and its calculation method is: the depth to be punched divided by the instantaneous punching speed. The current punching time refers to the total time of a single punching that has been performed before the punching pipe is obtained, which is expressed as: the number of single punchings multiplied by the sampling interval. The predicted punching time refers to the sum of the time to be punched and the current punching time. The standard vibration value refers to the maximum amplitude that a fixed pipe can vibrate at, which is set manually. The standard punching time refers to the maximum time to complete the punching, which is set manually. The minimum value refers to a constant set manually, which is used to avoid the situation where the denominator is 0.

[0058] Furthermore, in the process of punching, in order to ensure the efficiency and stability of punching, the frequency of the ultrasonic wave needs to be adjusted in real time to obtain the adjusted ultrasonic frequency. The adjustment of the ultrasonic frequency needs to meet the following two points: First, it is necessary to ensure that a single punching can be completed within the preset standard punching time, that is, the above-mentioned calculation formula for adjusting the ultrasonic frequency is introduced: , secondly, under the premise of meeting the first point, ensure that the vibration of the pipe itself is within the controllable range (the controllable range means less than the standard vibration value), which corresponds to the above-mentioned formula for adjusting the ultrasonic frequency: In order to describe the vibration of the pipe, a real-time vibration value is introduced. The larger the real-time vibration value is, the more severe the vibration of the pipe is, which makes the possibility of deviation in punching greater.

[0059] S7. In the step of punching the target pipe, the automatic chipping unit in the punching device is used to perform real-time chipping until the punching is completed.

[0060] It can be understood that, in the punching step of the target pipe, in order to avoid the accumulation of debris generated in the punching process, thereby affecting the subsequent punching, for example: the accumulation of debris will cause the punching position to deviate, the punching tool to wear or the hole size to deviate, etc., the automatic debris unit is used to clean the debris in real time, wherein the cleaning process is: using the air suction machine to suck the debris into the debris container, and when the punching position changes, the push rod is used to move the debris container to the corresponding punching position.

[0061] S8, the first hole position is removed from the hole position group to obtain a removed hole position group, the removed hole position group and the target punched pipe are taken as the hole position group and the target pipe respectively, and the step of extracting the first hole position from the hole position group is returned until the hole position group is empty, and the pipe punching is completed.

[0062] It should be explained that the removed hole position group refers to the hole position group after the first hole position is removed. When the hole position group is empty, it means that all the hole positions in the target pipe have been punched.

[0063] The present application is to solve the problems described in the background art, first, according to the material database, the hardness evaluation model is constructed, the data of the target pipe is obtained based on the hardness evaluation model, this step can estimate the hardness value of the target pipe in advance by establishing the hardness evaluation model, which provides the key parameters for the subsequent punching operation, avoids the contact hardness measurement of the target pipe, and improves the efficiency and quality of the punching, then the historical pipe group is obtained, the punching test is carried out on the historical pipe group, and the punching frequency data set is obtained, this step can accumulate rich experimental data, which is helpful to the accuracy of the subsequent ultrasonic frequency setting, and improves the punching effect and efficiency, in addition, the automatic debris unit and the intelligent punching unit are introduced, the automatic debris unit can clean the debris in real time, ensure the cleanliness of the punching environment, avoid the influence of debris accumulation on the punching, the intelligent punching unit can realize high-precision punching operation and improve the punching quality, further, according to the punching frequency data set, the ultrasonic frequency of the target pipe is set, and the initial ultrasonic frequency is obtained, this step uses historical data to provide reasonable ultrasonic frequency reference for the current punching task, which can quickly find the punching frequency suitable for the target pipe, so as to improve the punching efficiency and quality, then the target pipe is punched based on the first hole position, the target pipe data, the initial ultrasonic frequency and the intelligent punching unit in the punching device, and the target punched pipe is obtained, this step adopts the intelligent punching unit combined with the laser displacement sensor and the vibration monitoring, which can monitor the punching depth and vibration value in real time and adjust the ultrasonic frequency, realize high-precision and stable punching operation, finally, the automatic debris unit in the punching device is used to clean the debris in real time until the punching is completed, and the automatic debris unit is used to clean the debris, which helps to maintain the cleanliness of the punching area, avoids the problems of punching position deviation, tool wear and hole size deviation caused by debris accumulation, and improves the quality of the pipe. Therefore, the present application can improve the precision of the picket ball net frame pipe punching and improve the intelligent degree of the pipe punching.

[0064] As Figure 2 shown, it is a functional module diagram of the picket ball net frame pipe punching system provided by an embodiment of the present application.

[0065] The picket ball net frame pipe punching system 100 can be installed in the electronic device 1. According to the realized function, the picket ball net frame pipe punching system 100 can include a pipe data acquisition module 101, a frequency data test module 102, a target pipe punching module 103 and a punching debris cleaning module 104. The modules of the present application can also be called units, which refer to a series of computer program segments that can be executed by the processor 10 of the electronic device 1 and can complete fixed functions, which are stored in the memory 11 of the electronic device 1.

[0066] The pipe material data acquisition module 101 is configured to receive a pipe material punching instruction, determine a target pipe material based on the pipe material punching instruction, wherein the target pipe material is a Pickleball net rack pipe material, construct a hardness evaluation model based on a pre-acquired material database, and perform data analysis on the target pipe material based on the hardness evaluation model to obtain target pipe material data, wherein the hardness evaluation model is a neural network model, and the target pipe material data includes a target pipe material hardness value, a hole position group, and a pipe material thickness. The frequency data test module 102 is configured to obtain a historical pipe material group, perform a punching test on the historical pipe material group to obtain a punching frequency data set, wherein the punching frequency data set includes a plurality of punching frequency data, and the punching frequency data includes a historical pipe material hardness value, a hole deviation value, and a historical punching frequency, and a punching device is confirmed, wherein the punching device includes an automatic debris unit and an intelligent punching unit, the automatic debris unit includes a debris container, a suction fan, and a push rod, and the intelligent punching unit includes an ultrasonic generator, a punching tool, a laser displacement sensor, and a fixed clamp. The target pipe material punching module 103 is configured to set an initial ultrasonic frequency for the target pipe material based on the punching frequency data set, extract a first hole position from the hole position group, and punch the target pipe material based on the first hole position, the target pipe material data, the initial ultrasonic frequency, and the intelligent punching unit in the punching device to obtain a target punched pipe material. The punching debris cleaning module 104 is configured to use the automatic debris unit in the punching device to clean debris in real time until the punching is completed, remove the first hole position from the hole position group to obtain a removed hole position group, and use the removed hole position group and the target punched pipe material as the hole position group and the target pipe material, respectively, and return to the step of extracting the first hole position from the hole position group until the hole position group is empty.

[0067] In detail, the modules in the Pickleball net rack pipe material punching system 100 in the embodiment of the present application use the same technical means as the Pickleball net rack pipe material punching device in the above Figure 1 , and can produce the same technical effects, which will not be described here.

[0068] As shown in Figure 3 , it is a structural schematic diagram of an electronic device 1 for implementing a Pickleball net rack pipe material punching device according to an embodiment of the present application.

[0069] The electronic device 1 can include a processor 10, a memory 11, and a bus 12, and can further include a computer program stored in the memory 11 and executable on the processor 10, such as a Pickleball net rack pipe material punching device program.

[0070] The memory 11 includes at least one type of readable storage medium, such as flash memory, mobile hard disk, multimedia card, card-type memory (e.g., SD or DX memory, etc.), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of the electronic device 1, such as a mobile hard disk of the electronic device 1. In other embodiments, the memory 11 can also be an external storage device of the electronic device 1, such as a plug-in mobile hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device 1. Further, the memory 11 includes both an internal storage unit and an external storage device of the electronic device 1. The memory 11 can be used to store application software and various data installed on the electronic device 1, such as the code of the pickle ball net frame pipe punching device program, and can also be used to temporarily store data that has been output or will be output.

[0071] The processor 10 can be composed of an integrated circuit in some embodiments, such as a single packaged integrated circuit, or a plurality of packaged integrated circuits with the same or different functions, including one or more combinations of central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips, etc. The processor 10 is the control core (Control Unit) of the electronic device 1, which connects various components of the entire electronic device 1 through various interfaces and lines, and executes various functions and processes data of the electronic device 1 by running or executing programs or modules stored in the memory 11 (such as the pickle ball net frame pipe punching device program, etc.) and calling data stored in the memory 11.

[0072] The bus 12 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus 12 can be divided into an address bus, a data bus, a control bus, etc. The bus 12 is configured to realize the connection and communication between the memory 11 and at least one processor 10, etc.

[0073] Figure 3 Only the electronic device 1 with components is shown, and those skilled in the art can understand that, Figure 3The illustrated structure does not constitute a limitation on the electronic device 1, and can include fewer or more components than illustrated, or combine certain components, or different component arrangements.

[0074] For example, although not shown, the electronic device 1 can also include a power source (such as a battery) to power the various components, and preferably the power source can be logically connected to the at least one processor 10 through a power management system, so that the power management system can implement functions such as charge management, discharge management, and power consumption management. The power source can also include one or more DC or AC power sources, a recharging system, a power failure detection circuit, a power converter or inverter, a power status indicator, and any other components. The electronic device 1 can also include various sensors, Bluetooth modules, Wi-Fi modules, and the like, which are not described here.

[0075] Further, the electronic device 1 can also include a network interface, which can optionally include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), and is typically used to establish a communication connection between the electronic device 1 and other electronic devices.

[0076] Optionally, the electronic device 1 can also include a user interface, which can be a display (Display), an input unit (such as a keyboard (Keyboard)), and optionally a standard wired interface, a wireless interface. Optionally, in some embodiments, the display can be an LED display, a liquid crystal display, a touch liquid crystal display, and an OLED (Organic Light-Emitting Diode) touch, etc. The display can also be appropriately referred to as a display screen or a display unit, and is used to display information processed in the electronic device 1 and to display a visualized user interface.

[0077] The program stored in the memory 11 in the electronic device 1 is a combination of a plurality of instructions, which, when executed in the processor 10, can implement: receiving a pipe punching instruction, determining a target pipe based on the pipe punching instruction, wherein the target pipe is a picket ball net rack pipe; constructing a hardness evaluation model based on the pre-acquired material database, performing data analysis on the target pipe based on the hardness evaluation model to obtain target pipe data, wherein the hardness evaluation model is a neural network model, and the target pipe data includes target pipe hardness value, hole position group, and pipe thickness; The historical pipe material group is obtained, a punching test is performed on the historical pipe material group, and a punching frequency data set is obtained, wherein the punching frequency data set includes a plurality of punching frequency data, and the punching frequency data includes a historical pipe material hardness value, a hole deviation value and a historical punching frequency; The punching device is confirmed, wherein the punching device includes an automatic debris unit and an intelligent punching unit, the automatic debris unit includes a debris container, a suction fan and a push rod, and the intelligent punching unit includes an ultrasonic generator, a punching tool, a laser displacement sensor and a fixed clamp; According to the punching frequency data set, the initial ultrasonic frequency is obtained by setting the ultrasonic frequency of the target pipe material; The first hole position is extracted from the hole position group, and the target pipe material is punched based on the first hole position, the target pipe material data, the initial ultrasonic frequency and the intelligent punching unit in the punching device, to obtain a target punched pipe material; In the step of punching the target pipe material, the automatic debris unit in the punching device is used for real-time debris until the punching is completed; The first hole position is removed from the hole position group to obtain a removed hole position group, and the removed hole position group and the target punched pipe material are taken as the hole position group and the target pipe material respectively, and the step of extracting the first hole position from the hole position group is returned until the hole position group is empty, and the pipe material punching is completed.

[0078] Specifically, the specific implementation device of the processor 10 to the above instructions can refer to Figures 1 to 3 The description of related steps in the corresponding embodiments will not be repeated here.

[0079] Further, the modules / units integrated in the electronic device 1 are stored in a computer readable storage medium if they are realized in the form of software function units and sold or used as independent products. The computer readable storage medium can be volatile or non-volatile. For example, the computer readable medium can include any entity or system capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory).

[0080] The application also provides a computer readable storage medium, which stores a computer program, and the computer program can realize the following when executed by the processor 10 of the electronic device 1: Receiving a pipe punching instruction, determining a target pipe material based on the pipe punching instruction, wherein the target pipe material is a picket net rack pipe material; The hardness evaluation model is constructed according to the pre-acquired material database, data analysis is carried out on the target pipe based on the hardness evaluation model, and target pipe data is obtained, wherein the hardness evaluation model is a neural network model, and the target pipe data includes target pipe hardness value, hole position group and pipe thickness; A historical pipe group is acquired, and a punching test is carried out on the historical pipe group to obtain a punching frequency data set, wherein the punching frequency data set includes a plurality of punching frequency data, and the punching frequency data includes historical pipe hardness value, hole deviation value and historical punching frequency; The punching device is confirmed, wherein the punching device includes an automatic debris unit and an intelligent punching unit, wherein the automatic debris unit includes a debris container, a suction fan and a push rod, and the intelligent punching unit includes an ultrasonic generator, a punching tool, a laser displacement sensor and a fixed clamp; According to the punching frequency data set, the initial ultrasonic frequency of the target pipe is set, and the initial ultrasonic frequency is obtained; The first hole position is extracted from the hole position group, and the target pipe is punched based on the first hole position, the target pipe data, the initial ultrasonic frequency and the intelligent punching unit in the punching device, and the target punched pipe is obtained; In the step of punching the target pipe, the automatic debris unit in the punching device is used for real-time debris until the punching is completed; The first hole position is removed from the hole position group to obtain a removed hole position group, and the removed hole position group and the target punched pipe are respectively taken as the hole position group and the target pipe, and the step of extracting the first hole position from the hole position group is returned until the hole position group is empty, and the pipe punching is completed.

[0081] In several embodiments provided by the present application, it should be understood that the disclosed devices, systems and apparatuses can be implemented in other ways. For example, the system embodiments described above are only illustrative, and actual implementation can have another division way.

[0082] The modules described as separate components can or can not be physically separated, and the components displayed as modules can or can not be physical units, that is, they can be located in one place, or distributed on multiple network units. Part or all of the modules can be selected to achieve the purpose of the embodiment scheme according to actual needs.

[0083] In addition, the functional modules in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of hardware plus software functional module.

[0084] It is apparent for a person skilled in the art that the present application is not limited to the details of the above-described exemplary embodiments, but that the present application can be implemented in other concrete forms without departing from the spirit or essential characteristics of the present application.

[0085] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application but not to limit the present application, and although the present application has been described in detail with reference to the preferred embodiments, those ordinarily skilled in the art should understand that the technical solutions of the present application can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present application.

Claims

1. A pickle ball net frame pipe punching device, characterized in that: The device comprises: receiving a pipe punching instruction, and determining a target pipe based on the pipe punching instruction, wherein the target pipe is a pickleball net frame pipe; A hardness evaluation model is constructed based on a pre-acquired material database, and data analysis is performed on the target pipe based on the hardness evaluation model to obtain target pipe data, wherein the hardness evaluation model is a neural network model, and the target pipe data includes: target pipe hardness value, hole location group, and pipe thickness; Obtain a historical pipe group, perform a punching test on the historical pipe group, and obtain a punching frequency data set, wherein the punching frequency data set includes multiple punching frequency data, and the punching frequency data includes: historical pipe hardness values, hole deviation values, and historical punching frequencies; Identify the punching device, wherein the punching device includes: an automatic debris unit and an intelligent punching unit, wherein the automatic debris unit includes: a debris container, a suction fan and a push rod, and the intelligent punching unit includes: an ultrasonic generator, a punching tool, a laser displacement sensor and a fixing fixture; According to the punching frequency data set, the ultrasonic frequency of the target pipe is set to obtain the initial ultrasonic frequency; Extracting the first hole position from the hole position group, punching the target pipe based on the first hole position, target pipe data, initial ultrasonic frequency, and the intelligent punching unit in the punching device to obtain a target punched pipe; In the step of punching the target pipe, an automatic chipping unit in the punching device is used to perform real-time chipping until punching is completed; The first hole position is removed from the hole position group to obtain a removed hole position group. The removed hole position group and the target punching pipe are used as the hole position group and the target pipe respectively, and the process of extracting the first hole position from the hole position group is returned to the step of until the hole position group is an empty set, and the pipe punching is completed.

2. The pickle ball net frame tube punching device according to claim 1, characterized in that: The step of constructing a hardness evaluation model based on a pre-acquired material database includes: Collecting a basic material set in a material database, wherein the basic material set includes a plurality of basic materials, and the basic materials have material property records in the material database; identifying a basic attribute group set for each basic material in the basic material set, wherein the basic attribute group set includes a plurality of basic attribute groups, and one basic attribute group corresponds to one basic material in the basic material set; Acquire a test pipe group based on the base material set, wherein the test pipe group includes a plurality of test pipes, and the test pipes are prepared from one or more base materials in the base material set; Sequentially extracting test pipes from the test pipe group and cutting the test pipes to obtain a plurality of test pipe samples; Using a pre-obtained hardness tester, the hardness of multiple test pipe samples is measured to obtain multiple sample hardness values, and the average of the multiple sample hardness values ​​is calculated to obtain the test pipe hardness value; Constructing test pipe data of the test pipe based on the test pipe hardness value, the basic property group set, and the basic material set; Summarize the test pipe data corresponding to each test pipe in the test pipe group to obtain a test pipe data set; The pre-built neural network is trained using the test pipe dataset to obtain a hardness assessment model.

3. The pickle ball net frame tube punching device according to claim 2, characterized in that: The constructing of the test pipe data of the test pipe based on the test pipe hardness value, the basic attribute set and the basic material set includes: Identifying multiple similar materials corresponding to the test pipe in the basic material set, determining test material proportion groups of the multiple similar materials in the test pipe, and constructing a test material proportion vector based on the test material proportion groups; Identifying multiple similar material attribute groups corresponding to the multiple similar materials in the basic attribute group set, and constructing a test pipe attribute vector based on the multiple similar material attribute groups; Construct the test pipe feature vector based on the test material proportion vector and the test pipe attribute vector; The test pipe hardness value and the test pipe characteristic vector are combined to obtain the test pipe data.

4. The pickle ball net frame tube punching device according to claim 3, characterized in that: The target pipe data is analyzed based on the hardness evaluation model to obtain target pipe data, including: Measure the dimensions of the target pipe to obtain the hole position group and pipe thickness; Identifying a preparation material group of a target pipe, wherein the preparation material group includes one or more preparation materials; Based on the preparation material group and the hardness evaluation model, the hardness of the target pipe is evaluated to obtain the hardness value of the target pipe; The hole position group, pipe thickness and pipe hardness values ​​are combined to obtain target pipe data.

5. The pickle ball net frame tube punching device according to claim 4, characterized in that: The hardness evaluation of the target pipe is performed based on the preparation material group and the hardness evaluation model to obtain the target pipe hardness value, including: Extracting preparation materials in the preparation material group in sequence, and querying the target material attribute group of the preparation materials in the material database; Determining the target material ratio of the prepared material in the target pipe; Summarizing the target material attribute groups and target material proportions respectively to obtain a target material attribute group set and a target material proportion group, constructing a target pipe attribute vector based on the target material attribute group set, and constructing a target material proportion vector based on the target material proportion group; Construct a target pipe feature vector based on the target pipe property vector and the target material proportion vector; The target pipe feature vector is input into the hardness evaluation model to obtain the target pipe hardness value.

6. The pickle ball net frame tube punching device according to claim 5, characterized in that: The punching test is performed on the historical pipe group to obtain a punching frequency data set, including: Sequentially extracting historical pipes from the historical pipe group and determining historical pipe hardness values ​​of the historical pipes; Set the historical punching frequency; Punching historical pipes based on historical punching frequencies to obtain historical punched pipes; Identify the real-time holes in the historically punched pipes, measure the real-time holes, and obtain a historical hole diameter group; Calculate the hole deviation value based on the historical hole diameter group and the preset standard hole diameter; Combine historical pipe hardness values, hole deviation values, and historical punching frequencies to obtain punching frequency data; Adjusting the historical punching frequency to obtain an adjusted punching frequency, using the adjusted punching frequency and the historical punched pipe as the historical punching frequency and the historical pipe, respectively, and returning to the step of punching the historical pipe based on the historical punching frequency until the number of holes in the historical pipe equals a preset standard number of holes; The punching frequency data corresponding to the historical pipes are summarized to obtain a punching frequency data group, and the punching frequency data group corresponding to each historical pipe in the historical pipe group is merged to obtain a punching frequency data set.

7. The pickle ball net frame tube punching device according to claim 6, characterized in that: The step of setting the ultrasonic frequency of the target pipe according to the punching frequency data set to obtain the initial ultrasonic frequency includes: Extracting punching frequency data in sequence from the punching frequency data set, and calculating punching similarity based on the target pipe hardness value and the historical pipe hardness values ​​in the punching frequency data; Calculate the deviation weight value according to the hole deviation value in the punching frequency data; The punching similarities and deviation weight values ​​are summarized respectively to obtain a punching similarity set and a deviation weight value set, and the punching similarity set and the deviation weight value set are normalized respectively to obtain a normalized punching similarity set and a normalized deviation weight value set; The initial ultrasonic frequency is calculated based on the normalized punching similarity set and the normalized deviation weight value set, where the initial ultrasonic frequency is expressed as: ,in, represents the initial ultrasonic frequency, Represents the preset similarity coefficient, represents the preset deviation coefficient, n represents the number of normalized punching similarities in the normalized punching similarity set or the number of normalized deviation weight values ​​in the normalized deviation weight value set, represents the first A normalized punching similarity, Indicates the number of punching frequency data sets The historical punching frequency in the punching frequency data, Indicates the first A normalized deviation weight value, Indicates the The historical punching frequency in the punching frequency data.

8. The pickle ball net frame tube punching device according to claim 7, characterized in that: The method of punching the target pipe based on the first hole position, target pipe data, initial ultrasonic frequency, and the intelligent punching unit in the punching device to obtain the target punched pipe includes: Fixing the target pipe based on the first hole position and the fixing fixture in the intelligent punching unit to obtain a fixed pipe; Set the initial punching time; Based on the initial ultrasonic frequency and the initial punching time, the fixed pipe is punched once using an ultrasonic generator and a punching tool to obtain a punched pipe, wherein the frequency of the ultrasonic generator is the initial ultrasonic frequency; Calculate the target punching time according to the initial punching time and the preset sampling interval; Based on the laser displacement sensor in the intelligent punching unit, the real-time punching depth of the punched pipe is detected, and the pre-built vibration sensor is used to monitor the vibration of the fixed pipe during the step of punching the fixed pipe with the ultrasonic generator and the punching tool, and obtain the real-time vibration value; Adjusting the initial ultrasonic frequency according to the real-time punching depth and the real-time vibration value to obtain an adjusted ultrasonic frequency; The adjusted ultrasonic frequency, the target punching time, and the punched pipe are respectively used as the initial ultrasonic frequency, the initial punching time, and the fixed pipe, and the process of performing a single punching on the fixed pipe using the ultrasonic generator and the punching tool based on the initial ultrasonic frequency and the initial punching time is returned until the real-time punching depth is equal to the pipe thickness in the target pipe data. When the real-time punching depth is equal to the pipe thickness, the punched pipe is recorded as the target punched pipe.

9. The pickle ball net frame tube punching device according to claim 8, characterized in that: The adjusting the initial ultrasonic frequency according to the real-time punching depth and the real-time vibration value to obtain the adjusted ultrasonic frequency includes: Calculating the instantaneous punching speed according to the real-time punching depth and sampling interval; The current punching depth is measured using a laser displacement sensor, and the depth to be punched is calculated based on the target punching depth and the current punching depth, wherein the depth to be punched is the difference between the target punching depth and the current punching depth; Calculate the punching time based on the depth of the hole to be punched and the instantaneous punching speed, and calculate the predicted punching time based on the punching time and the preset current punching time; According to the predicted punching time, real-time vibration value and initial ultrasonic frequency, the ultrasonic frequency is calculated and adjusted using the following formula: ,in, Indicates adjusting the ultrasonic frequency. Indicates the predicted punching time, Indicates the current punching time. Indicates the preset standard punching time. represents the logarithmic function with base 10, Indicates the preset standard vibration value, Indicates the real-time vibration value, Indicates the preset minimum value.

10. A system using the pickle ball net tube punching device according to any one of claims 1 to 9, characterized in that: The system comprises: a pipe data acquisition module, configured to receive a pipe punching instruction, determine a target pipe based on the pipe punching instruction, wherein the target pipe is a pickleball net frame pipe, construct a hardness assessment model based on a pre-acquired material database, perform data analysis on the target pipe based on the hardness assessment model, and obtain target pipe data, wherein the hardness assessment model is a neural network model, and wherein the target pipe data includes: a target pipe hardness value, a hole location group, and a pipe thickness; A frequency data test module is used to obtain a historical pipe group, perform a punching test on the historical pipe group, and obtain a punching frequency data set, wherein the punching frequency data set includes multiple punching frequency data, and the punching frequency data includes: historical pipe hardness values, hole deviation values, and historical punching frequencies, and identify a punching device, wherein the punching device includes: an automatic chip removal unit and an intelligent punching unit, wherein the automatic chip removal unit includes: a chip container, a suction fan, and a push rod, and the intelligent punching unit includes: an ultrasonic generator, a punching tool, a laser displacement sensor, and a fixing fixture; The target pipe punching module is used to set the ultrasonic frequency of the target pipe according to the punching frequency data set to obtain the initial ultrasonic frequency, extract the first hole position in the hole position group, and punch the target pipe based on the first hole position, target pipe data, initial ultrasonic frequency, and the intelligent punching unit in the punching device to obtain the target punched pipe; The punching debris cleaning module is used to use the automatic debris unit in the punching device to perform real-time debris removal until punching is completed, remove the first hole position from the hole position group, obtain a removed hole position group, use the removed hole position group and the target punching pipe as the hole position group and the target pipe respectively, and return to the step of extracting the first hole position in the hole position group until the hole position group is an empty set.

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