Characteristic analysis method, device and equipment for projectile flow and medium

Abstract

The invention discloses a shot flow characteristic analysis method, device and equipment and a medium, and relates to the field of shot blasting. The method comprises the following steps: after shot blasting is carried out on an experimental assembly formed by target test piece units, obtaining the arc height value of each target test piece unit; calculating a projectile flow distribution variance according to the test piece positioning coordinate of each target test piece unit, the arc height value of each target test piece unit and a target arc height value calculation function; and according to the shot flow distribution variance and the shot blasting correlation parameters, shot flow characteristic analysis is carried out. According to the technical scheme provided by the embodiment of the invention, the accurate variance of the shot flow distribution model can be reliably determined, so that shot flow characteristics in an actual production scene can be effectively analyzed.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of shot forming technology, and in particular to a shot flow characteristic analysis method, device, equipment and medium. BACKGROUND

[0002] In the shot forming process, the shot flow randomly impacts on the surface of the part to form one after another concave pits, and then form one after another shot strips. Generally speaking, the shot flow is a two-dimensional normal distribution probability model. In the normal distribution model, the value of the variance plays a very key role in the final process effect of the shot forming. How to effectively obtain the variance of the shot flow distribution model after the shot forming is very important and key.

[0003] At present, one method that can be used is to analyze the shot flow distribution model theoretically based on fluid finite element simulation analysis, but this method is a purely theoretical method. Even if the variance of the shot flow distribution model can be determined, the reliability of the result cannot be verified, and it cannot be applied to the shot flow characteristic analysis in the actual production scene. SUMMARY

[0004] The present application provides a shot flow characteristic analysis method, device, equipment and medium to solve the problem that the existing shot flow distribution model analysis is a purely theoretical method, the corresponding variance of the distribution model cannot be verified, and it cannot be applied to the actual shot flow characteristic analysis.

[0005] According to one aspect of the present application, a shot flow characteristic analysis method is provided, comprising:

[0006] After shot forming on the experimental combination body composed of target test piece units, the arc height value of each target test piece unit is obtained;

[0007] According to the test piece positioning coordinates of each target test piece unit, the arc height value of each target test piece unit, and the target arc height value calculation function, the shot flow distribution variance is calculated;

[0008] According to the shot flow distribution variance and the shot forming correlation parameters, the shot flow characteristic analysis is performed.

[0009] According to another aspect of the present application, a shot flow characteristic analysis device is provided, comprising:

[0010] The arc height value acquisition module is configured to obtain the arc height value of each target test piece unit after shot forming on the experimental combination body composed of target test piece units;

[0011] The shot flow variance calculation module is configured to calculate the shot flow distribution variance according to the test piece positioning coordinates of each target test piece unit, the arc height value of each target test piece unit, and the target arc height value calculation function;

[0012] The shot stream feature analysis module is configured to perform shot stream feature analysis according to the shot stream distribution variance and the shot-related parameters.

[0013] According to another aspect of the present application, there is provided an electronic device comprising:

[0014] at least one processor; and

[0015] a memory in communication with the at least one processor; wherein

[0016] the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to perform the shot stream feature analysis method according to any one of the embodiments of the present application.

[0017] According to another aspect of the present application, there is provided a computer readable storage medium storing computer instructions for enabling a processor to perform the shot stream feature analysis method according to any one of the embodiments of the present application when executed by the processor.

[0018] The technical solution of the embodiments of the present application comprises the following steps: after shot peening is performed on the experimental combination body composed of target specimen units, the arc height value of each target specimen unit is obtained, the shot stream distribution variance is calculated according to the specimen positioning coordinates of each target specimen unit, the arc height value of each target specimen unit, and a target arc height value calculation function, and then the shot stream feature analysis is performed according to the shot stream distribution variance and the shot-related parameters. In the present solution, the target specimen units are used to divide the area of the experimental combination body to determine the arc height value with finer granularity, and the variance of the shot stream distribution model is obtained from the actual scene to further realize more accurate and effective shot stream feature analysis. The present solution solves the problem that the existing shot stream distribution model analysis is a purely theoretical method, the variance corresponding to the distribution model cannot be verified, and the shot stream feature analysis cannot be applied to the actual shot stream feature analysis. The accurate variance of the shot stream distribution model can be reliably determined to effectively analyze the shot stream feature in the actual production scene.

[0019] It should be understood that the content described in this part is not intended to identify key or important features of the embodiments of the present application, nor to limit the scope of the present application. Other features of the present application will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings needed in the embodiments description. Obviously, the drawings in the following description only show some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative effort based on these drawings.

[0021] Figure 1 A flow chart of a characteristic analysis method of a projectile flow provided for the first embodiment of the present application;

[0022] Figure 2 A flow chart of a characteristic analysis method of a projectile flow provided for the second embodiment of the present application;

[0023] Figure 3 A schematic diagram of an experimental assembly of a target test piece unit provided for the second embodiment of the present application;

[0024] Figure 4 A structural schematic diagram of a characteristic analysis device of a projectile flow provided for the third embodiment of the present application;

[0025] Figure 5 A structural schematic diagram of an electronic device that can be used to implement the embodiments of the present application is shown. DETAILED DESCRIPTION

[0026] In order to make the person skilled in the art better understand the present application, the following will combine the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative effort should be within the scope of the present application.

[0027] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but can include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0028] Embodiment one

[0029] Figure 1 A flowchart of a characteristic analysis method of a projectile flow is provided for an embodiment of the present application. The embodiment can be applicable to reliably determine the accurate variance of the projectile flow distribution model. The method can be performed by a projectile flow characteristic analysis device, which can be realized in the form of hardware and / or software, and can be configured in an electronic device. As shown in the figure, the method comprises the following steps. Figure 1

[0030] Step 110: After the target test piece units are subjected to shot peening, the arc height value of each target test piece unit is obtained.

[0031] The target test piece unit can be an elongated test piece, and the length-width ratio of the target test piece unit can be adjusted as needed. The experimental combination can be an experimental object subjected to shot peening detection, which is formed by splicing multiple target test piece units. The material of the target test piece unit can be the same as that of the almen test piece, but is not limited to the material of the almen test piece. The arc height value can be used to describe the bending value of the center position of the test piece.

[0032] In the embodiment of the present application, the shot peening experiment can be performed on the experimental combination formed by splicing multiple target test piece units, and then the arc height value of each target test piece unit after the shot peening experiment is obtained.

[0033] In an optional embodiment of the present application, the experimental combination can be formed by sequentially splicing multiple target test piece units in a long-side alignment manner, and the width of the experimental combination is greater than the effective width of the projectile flow strip.

[0034] The effective width of the projectile flow strip can be the width of the shot peening strip that can reflect the shot peening effect, that is, the width of the strip on which the shot peening intensity is effectively applied during the shot peening process.

[0035] In the embodiment of the present application, multiple target test piece units can be sequentially spliced in a long-side alignment manner, and a workpiece can be used to fix the experimental combination, so that the width of the experimental combination is greater than the effective width of the projectile flow strip.

[0036] Step 120: According to the test piece positioning coordinates of each target test piece unit, the arc height value of each target test piece unit, and a target arc height value calculation function, the projectile flow distribution variance is calculated.

[0037] The test piece positioning coordinates can be used to determine the splicing position of the target test piece unit in the experimental combination. The target arc height value calculation function can be a function for calculating the arc height value of the test piece in the field of shot peening. The projectile flow distribution variance can be the variance of the projectile flow distribution model after shot peening. A large projectile flow distribution variance means that the projectile flow is more dispersed, and the strip width is large. A small projectile flow distribution variance means that the projectile flow is more concentrated, and the strip width is small.​

[0038] In the embodiment of the present application, a coordinate system for describing the position of the target specimen unit can be established, and then the specimen positioning coordinates of each target specimen unit in the coordinate system are determined, and then the corresponding specimen positioning coordinates of each target specimen unit and the camber value are input as a data pair into a target camber value calculation function, and the projectile flow distribution variance is obtained through a fitting algorithm.

[0039] Optionally, the fitting algorithm can include but is not limited to the least square method or the algorithm in the fitting function toolkit.

[0040] In step 130, the projectile flow characteristics are analyzed according to the projectile flow distribution variance and the shot-related parameters.

[0041] The shot-related parameters can be parameters related to the current shot operation. The shot-related data can include but is not limited to the shot speed and the shot flow during the shot.

[0042] In the embodiment of the present application, the shot-related parameters during the current shot operation are obtained, and then the projectile flow distribution variance and the shot-related parameters are analyzed according to the existing shot effect evaluation method.

[0043] Optionally, the discrete element analysis of the projectile flow can be performed based on the projectile flow distribution variance and the shot-related parameters, or the finite element simulation analysis of the equivalent heat source can be performed based on the projectile flow distribution variance and the shot-related parameters.

[0044] In the technical scheme of the embodiment of the present application, after the shot is performed on the experimental combination body formed by the target specimen units, the camber value of each target specimen unit is obtained, and then the specimen positioning coordinates of each target specimen unit, the camber value of each target specimen unit, and the target camber value calculation function are used to calculate the projectile flow distribution variance, and then the projectile flow characteristics are analyzed according to the projectile flow distribution variance and the shot-related parameters. In the present scheme, the target specimen units are used to divide the regions of the experimental combination body to determine the camber values of finer granularity, and the variance of the projectile flow distribution model is obtained from the actual scene to further analyze the projectile flow characteristics more accurately and effectively. The present scheme solves the problem that the existing analysis of the projectile flow distribution model is a pure theoretical method, the variance corresponding to the distribution model cannot be verified, and the projectile flow characteristics cannot be applied to the actual analysis in one step. The accurate variance of the projectile flow distribution model can be reliably determined to effectively analyze the projectile flow characteristics in the actual production scene.

[0045] Embodiment two

[0046] Figure 2A flow chart of a characteristic analysis method of a projectile flow provided for the second embodiment of the present application, the embodiment is based on the above-mentioned embodiment and is particularized, and a specific optional implementation of calculating the projectile flow distribution variance is given according to the specimen positioning coordinates of each target specimen unit, the arc height value of each target specimen unit and the target arc height value calculation function. As shown in Figure 2 The method comprises the following steps:

[0047] Step 210: After the target specimen units constitute the experimental combination and are subjected to shot peening, the arc height value of each target specimen unit is obtained.

[0048] In an optional embodiment of the present application, obtaining the arc height value of each target specimen unit can comprise: for each target specimen unit, determining the target forward distance of the measuring rod in the three-point measuring assembly along the rod diameter direction based on the arc height measurement of the measuring rod in the three-point measuring assembly; and taking the target forward distance determined for each target specimen unit as the arc height value of the corresponding target specimen unit.

[0049] The three-point measuring assembly can be an assembly for measuring the arc height value by using a three-point measurement method. The target forward distance can be used to describe the elongation of the measuring rod along the rod diameter direction.

[0050] In the embodiment of the present application, after the experimental combination is subjected to shot peening, the arc height of each target specimen unit is measured by the three-point measuring assembly to obtain the target forward distance of the measuring rod in the three-point measuring assembly along the rod diameter direction when the arc height of each target specimen unit is detected, and the target forward distance determined for each target specimen unit is taken as the arc height value of the corresponding target specimen unit.

[0051] In an optional embodiment of the present application, the three-point measuring assembly can comprise two fixed rods and one measuring rod, and the interval and rod diameter of the fixed rods meet the arc height measurement operation standard.

[0052] The arc height measurement operation standard can be an execution standard for arc height measurement in the shot peening process. For example, the arc height measurement operation standard can refer to the arc height measurement part of SAE J442.

[0053] Specifically, unlike the existing arc height value measuring device, the three-point measuring assembly in the embodiment is specifically composed of two fixed rods and one measuring rod, and the interval and rod diameter of the fixed rods in the three-point measuring assembly need to meet the current industry arc height measurement operation standard, so that the measurement result of the arc height value can meet the industry standard.

[0054] Exemplarily, the fixed rod head is spherical, with a diameter of 4.76 mm, and the distance between the two fixed rods is 31.74 mm; the measuring rod head is curved and located in the middle of the two fixed rods. The measuring method of the three-point measuring assembly is as follows: when the two fixed rod heads are in contact with the target test piece unit, the measuring rod is in contact with the target test piece unit in the forward direction of the rod diameter, and the extension amount (target forward distance) is the arc height value of the target test piece unit.

[0055] In step 220, the test piece positioning coordinates of each target test piece unit and the arc height value of each target test piece unit are input into a target arc height value calculation function.

[0056] The target arc height value calculation function can include a first target arc height value calculation function or a second target arc height value calculation function. The first target arc height value calculation function and the second target arc height value calculation function can be two functions for calculating arc height values based on two different arc height value and shot time satisfying saturation curve formulas and a shot time distribution function.

[0057] In the embodiment of the present application, the corresponding test piece positioning coordinates and arc height values of each target test piece unit are input into the target arc height value calculation function selected by the user based on calculation needs, and the shot flow distribution variance is obtained through a fitting algorithm.

[0058] In an optional embodiment of the present application, the first target arc height value calculation function can have the following form: Wherein, H represents the arc height value of the target test piece unit, a represents the first to-be-fitted parameter, c represents the second to-be-fitted parameter, σ represents the shot flow distribution variance, and v represents the mean value of the normal distribution.

[0059] Wherein, y represents the independent variable of the first target arc height value calculation function. The size of v is related to the position of the origin of the coordinate system used to describe the position of the target test piece unit. a, c and σ are fitting parameters obtained through a fitting algorithm in the first target arc height value calculation function. v can be obtained through a fitting algorithm or can be pre-set according to the position of the origin of the coordinate system used to describe the position of the target test piece unit.

[0060] In an optional embodiment of the present application, the second target arc height value calculation function has the following form: Wherein, H represents the arc height value of the target test piece unit, a represents the first to-be-fitted parameter, c represents the second to-be-fitted parameter, σ represents the shot flow distribution variance, and v represents the mean value of the normal distribution.

[0061] The a, c and σ in the second target arc height value calculation function are fitting parameters obtained by a fitting algorithm, and v can be obtained by a fitting algorithm or can be preset according to the origin position of the coordinate system of the target specimen unit position.

[0062] Generally, it can be considered that in the shot blasting process, the projectile flow is ejected from the gun mouth, which presents a two-dimensional normal distribution random probability model. The two-dimensional random probability distribution model is as follows:

[0063]

[0064] Since x and y in the two-dimensional random normal distribution model are independent variables, the cumulative probability of the random projectile in the y direction still satisfies the one-dimensional random normal distribution model, which is expressed by the following formula:

[0065]

[0066] In the y-axis direction, the projectile flow density presents a normal distribution with the position directly below the spray gun as the origin, so it can be considered that the number of projectile impacts at positions with different y values also presents a normal distribution. Further, it can be known that the shot blasting time t at positions with different y values also presents a normal distribution. Therefore, the following formula exists:

[0067]

[0068] In the case of fixed shot blasting parameters, the arc height value H satisfies the saturation curve formula as the shot blasting time t increases, specifically, the following formula: H=a*(1-e -b*t );

[0069] The arc height value satisfying the saturation curve as the shot blasting time t increases can also satisfy the following formula:

[0070]

[0071] It can be known from the above saturation curve formula that as the shot blasting time increases, the arc height value also gradually tends to the a value. By combining the distribution function of the shot blasting time t with H=a*(1-e -b*t ), the following formula is obtained: By combining the distribution function of the shot blasting time t with , the following formula is obtained:

[0072] Since the final purpose of the present solution is to obtain the variance σ, and the variable values t0, b, etc. in the above formula are not related to the size, these variables and constants can be combined to simplify the formula to obtain the first target camber value calculation function and the second target camber value calculation function. The above two-dimensional random probability distribution model and one-dimensional random probability distribution model are well-known models in probability theory, and the saturation curve formula is also a well-recognized formula in the industry. The specific parameter meanings are not described again.

[0073] If the shot strip is divided into numerous independent and non-connected small areas, and the width of each small area is assumed to be Then, since the actual shot time t of each small area is not the same, the camber value H after bending deformation is also not the same. In theory, if tends to 0, then the relationship between H and the distance y is as shown in the first target camber value calculation function and the second target camber value calculation function.

[0074] Step 230, determining the shot stream distribution variance according to the fitting result of the target camber value calculation function.

[0075] The fitting result can be the fitting parameter determined by the fitting algorithm in the target camber value calculation function.

[0076] In the embodiment of the present application, the shot stream distribution variance can be analyzed from the fitting result of the target camber value calculation function.

[0077] Step 240, performing shot stream feature analysis according to the shot stream distribution variance and the shot correlation parameter.

[0078] In a specific example, as shown in Figure 3 , a plurality of elongated target test piece units are tightly spliced together, and the final width after splicing is preferably greater than the effective width of the shot stream strip. After the above target test piece units are fixed by a tool, shot is performed in the shot direction as shown in Figure 3 . Since each target test piece unit is different from the central distance of the strip, the number of shots it receives is also different. The farther away from the central part of the shot strip, the lower the number of shots it receives, and the camber value H generated after the target test piece unit is shot is also not the same. The camber value H will present a functional relationship with the coordinate position of the y-axis, and the functional relationship satisfies the first target camber value calculation function and the second target camber value calculation function. Figure 3 In the above formula, each target test piece unit has a corresponding coordinate value on the y-axis. Assuming that there are n target test piece units, and the width of each target test piece unit is Assuming Figure 3 the y value of the leftmost target test piece unit in the above formula is y0, then the y coordinate values corresponding to each target test piece unit are as follows:

[0079] The y-axis coordinate value y of the nth test piece from left to right n for:

[0080] right Figure 3 The test piece in the almen is shot peened, so that the curvature of the target test piece unit in each place is inconsistent. Specifically, the curvature of the target test piece unit can be measured by a profilometer, and then converted into the corresponding arc height value H according to the size of the almen test piece through the formula, the y value at different positions can be obtained. n The arc height H n This will result in n sets of data pairs input to the first target arc height calculation function or the second target arc height calculation function, namely: (y0, H1); Among them, the y coordinate value corresponding to the target test piece unit is substituted into y in the first target arc height value calculation function or the second target arc height value calculation function, and the arc height value corresponding to the y coordinate value is substituted into H in the first target arc height value calculation function or the second target arc height value calculation function.

[0081] The technical solution of the embodiment of the present invention is to obtain the arc height value of each target test piece unit after shot peening on the experimental assembly composed of target test piece units, thereby inputting the test piece positioning coordinates of each target test piece unit and the arc height value of each target test piece unit into the target arc height value calculation function, and then determine the variance of the projectile flow distribution according to the fitting result of the target arc height value calculation function, and perform projectile flow feature analysis according to the projectile flow distribution variance and the shot peening associated parameters. In this solution, the regional division of the experimental assembly is achieved by the target test piece unit to determine the arc height value of finer granularity, and obtain the variance of the projectile flow distribution model from the actual scene, so as to further achieve more accurate and effective analysis of the projectile flow characteristics, solving the problem that the existing projectile flow distribution model analysis is a purely theoretical method, and there is a problem that the corresponding variance of the distribution model cannot be verified, and it cannot be applied to the actual projectile flow feature analysis in one step. It can reliably determine the accurate variance of the projectile flow distribution model to effectively analyze the projectile flow characteristics in the actual production scene.

[0082] Example 3

[0083] Figure 4 This is a schematic diagram of the structure of a device for analyzing the characteristics of a projectile flow provided by the third embodiment of the present invention. Figure 4 As shown, the device includes:

[0084] The arc height value acquisition module 310 is used to obtain the arc height value of each target test piece unit after shot peening is performed on the experimental assembly consisting of the target test piece units;

[0085] The shot flow variance calculation module 320 is configured to calculate a shot flow distribution variance according to the specimen positioning coordinates of each target specimen unit, the arc height value of each target specimen unit, and a target arc height value calculation function.

[0086] The shot flow characteristic analysis module 330 is configured to perform shot flow characteristic analysis according to the shot flow distribution variance and a shot correlation parameter.

[0087] The technical scheme of the embodiment of the present application comprises the following steps: after shot blasting is performed on an experimental combination body composed of target specimen units, arc height values of each target specimen unit are obtained; a shot flow distribution variance is calculated according to the specimen positioning coordinates of each target specimen unit, the arc height value of each target specimen unit, and a target arc height value calculation function; and shot flow characteristic analysis is performed according to the shot flow distribution variance and a shot correlation parameter. In the present scheme, the target specimen units are used to divide the experimental combination body into regions, so as to determine arc height values of finer granularity, and the variance of the shot flow distribution model is obtained from an actual scene, so as to further realize more accurate and effective shot flow characteristic analysis. The present scheme solves the problem that the existing shot flow distribution model analysis is a purely theoretical method, the variance corresponding to the distribution model cannot be verified, and the shot flow characteristic analysis cannot be applied to actual production scenes. The accurate variance of the shot flow distribution model can be reliably determined, so as to effectively analyze the shot flow characteristic in actual production scenes.

[0088] Optionally, the experimental combination body is composed of a plurality of target specimen units which are sequentially spliced in a long-side alignment manner, and the experimental combination body has a width greater than an effective width of a shot flow strip.

[0089] Optionally, the arc height value acquisition module 310 is specifically configured to determine, for each target specimen unit, a target forward extension distance of a measuring rod in the three-point measuring assembly along a rod diameter direction based on the arc height measurement of the measuring rod in the three-point measuring assembly; and determine the target forward extension distance of each target specimen unit as the arc height value of the corresponding target specimen unit.

[0090] Optionally, the three-point measuring assembly comprises two fixed rods and one measuring rod, and the interval and rod diameter of the fixed rods meet the arc height measurement operation standard.

[0091] Optionally, the shot flow variance calculation module 320 is specifically configured to input the specimen positioning coordinates of each target specimen unit and the arc height value of each target specimen unit into the target arc height value calculation function; wherein the target arc height value calculation function comprises a first target arc height value calculation function or a second target arc height value calculation function; and determine the shot flow distribution variance according to a fitting result of the target arc height value calculation function.

[0092] Optionally, the first target arc height calculation function includes the following form: Wherein, H represents the arc height value of the target test piece unit, a represents the first parameter to be fitted, c represents the second parameter to be fitted, σ represents the variance of the projectile flow distribution, and v represents the mean of the normal distribution.

[0093] Optionally, the second target arc height calculation function includes the following form: Wherein, H represents the arc height value of the target test piece unit, a represents the first parameter to be fitted, c represents the second parameter to be fitted, σ represents the variance of the projectile flow distribution, and v represents the mean of the normal distribution.

[0094] The device for analyzing the characteristics of a projectile flow provided in an embodiment of the present invention can execute the method for analyzing the characteristics of a projectile flow provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0095] Example 4

[0096] Figure 5 A schematic diagram of the structure of an electronic device that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0097] like Figure 5 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., which is communicatively connected to the at least one processor 11. The memory stores a computer program that can be executed by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. Various programs and data required for the operation of the electronic device 10 can also be stored in the RAM 13. The processor 11, ROM 12, and RAM 13 are connected to each other via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0098] A plurality of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network, such as the Internet, and / or various telecommunication networks.

[0099] The processor 11 can be various general and / or special purpose processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 performs various methods and processes described above, such as the method of analyzing characteristics of a stream of projectiles.

[0100] In some embodiments, the method of analyzing characteristics of a stream of projectiles can be implemented as a computer program tangibly embodied in a computer readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded onto the RAM 13 and executed by the processor 11, one or more steps of the method of analyzing characteristics of a stream of projectiles described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to perform the method of analyzing characteristics of a stream of projectiles by any other appropriate means, such as by means of firmware.

[0101] Various implementations of the systems and techniques described above can be realized in digital electronic circuitry, integrated circuitry, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on a chip (SOC), a programmable logic device (PLD), a computer hardware, firmware, software, and / or combinations thereof. These various implementations can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0102] Computer programs for implementing the methods of the present application can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer program, when executed, can cause instructions defined in the flow charts and / or block diagrams to be implemented. The computer program can be executed entirely on a machine, partially on a machine, partially on a machine as a stand-alone software package and partially on a remote machine or entirely on a remote machine or server.

[0103] In the context of the present application, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. A computer-readable storage medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of a machine-readable storage medium will include one or more lines of a program of instructions in a transitory signal, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0104] To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0105] The systems and techniques described herein can be implemented in a computing system that includes a back end component, e.g., as a data server, or that includes a middleware component, e.g., an application server, or that includes a front end component, e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described herein, or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication, e.g., a communication network. Examples of communication networks include a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0106] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. A server can be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of large management difficulty and weak business scalability of traditional physical hosts and VPS servers.

[0107] The embodiments of the present application further disclose a computer program product, which comprises a computer program, and the computer program, when executed by a processor, implements the projectile flow feature analysis method provided in any of the embodiments of the present application. The program product and the projectile flow feature analysis method disclosed in the embodiments of the present application belong to the same inventive concept, and thus will not be repeated here.

[0108] It should be understood that the various forms of flow shown above can be reordered, added to, or deleted from without departing from the scope of the present application. For example, the steps recited in the present application can be executed in parallel, in series, or in a different order, without departing from the desired results of the technical solutions of the present application, and the present application is not limited herein.

[0109] The specific embodiments described above are not meant to limit the scope of the present application. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions of the present application can be made depending on design requirements and other factors. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present application should be included in the scope of the present application.

Claims

1. A method for analyzing the characteristics of a projectile flow, characterized in that: include: After shot peening is performed on the experimental assembly consisting of target test piece units, an arc height value of each target test piece unit is obtained; Calculating the variance of the projectile flow distribution according to the test piece positioning coordinates of each target test piece unit, the arc height value of each target test piece unit, and the target arc height value calculation function; According to the shot flow distribution variance and shot peening associated parameters, shot flow characteristic analysis is performed.

2. The method according to claim 1, characterized in that The experimental assembly is composed of a plurality of target test piece units sequentially spliced ​​in a manner of long-side alignment, and the width of the experimental assembly is greater than the effective width of the projectile stream strip.

3. The method according to claim 2, characterized in that The obtaining of the arc height value of each target test piece unit includes: For each target test piece unit, performing arc height measurement based on a measuring rod in a three-point measurement assembly to determine a target forward extension distance of the measuring rod in the three-point measurement assembly along the rod diameter direction; The target protruding distance determined for each target test piece unit is used as the arc height value of the corresponding target test piece unit.

4. The method according to claim 3, characterized in that The three-point measuring assembly includes two fixed rods and a measuring rod, and the spacing and rod diameters of the fixed rods both meet arc height measurement operation standards.

5. The method according to claim 1, characterized in that The calculation of the pellet stream distribution variance based on the test piece positioning coordinates of each target test piece unit, the arc height value of each target test piece unit, and the target arc height value calculation function includes: Inputting the test piece positioning coordinates of each target test piece unit and the arc height value of each target test piece unit into the target arc height value calculation function; wherein the target arc height value calculation function includes a first target arc height value calculation function or a second target arc height value calculation function; The projectile flow distribution variance is determined according to the fitting result of the target arc height value calculation function.

6. The method according to claim 5, characterized in that The first target arc height calculation function includes the following form: Wherein, H represents the arc height value of the target test piece unit, a represents the first parameter to be fitted, c represents the second parameter to be fitted, σ represents the variance of the projectile flow distribution, and v represents the mean of the normal distribution.

7. The method according to claim 5, characterized in that The second target arc height value calculation function includes the following form: Wherein, H represents the arc height value of the target test piece unit, a represents the first parameter to be fitted, c represents the second parameter to be fitted, σ represents the variance of the projectile flow distribution, and v represents the mean of the normal distribution.

8. A device for analyzing characteristics of a projectile flow, characterized in that: include: An arc height value acquisition module is used to obtain the arc height value of each target test piece unit after shot peening is performed on the experimental assembly consisting of the target test piece units; a pellet flow variance calculation module, configured to calculate the pellet flow distribution variance based on the test piece positioning coordinates of each target test piece unit, the arc height value of each target test piece unit, and a target arc height value calculation function; The shot flow characteristic analysis module is used to perform shot flow characteristic analysis based on the shot flow distribution variance and shot peening associated parameters.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor. The computer program is executed by the at least one processor to enable the at least one processor to perform the characteristic analysis method of projectile flow according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the characteristic analysis method of projectile flow according to any one of claims 1 to 7 when executed.

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