Pellet Radial Distribution Measuring Device, Pellet Distribution Prediction Method and Device

Abstract

The present application discloses a device for measuring the radial distribution of pellets, a method and a device for predicting the pellet distribution. The method for predicting the pellet distribution includes calculating the pellet mass distribution parameter; constructing a fitting function; and calculating the pellet coverage parameter per unit area of the surface to be processed. The present application can, based on the radial mass distribution law of the fixed-point shot peening measured by the device for measuring the radial distribution of pellets, establish a fitting function, calculate the number of shot pellets at any radial position of the fixed-point shot peening, and based on the number of shot pellets, predict the pellet coverage parameter per unit area of any position on the surface to be processed during the moving shot peening process, thereby helping to optimize the moving shot peening process to ensure uniform coverage of the pellets, which is of great significance for improving the fatigue strength of the workpiece.

Description

Technical Field

[0001] This application belongs to the technical field of material surface strengthening, and specifically relates to a device for measuring the radial distribution of pellets, a method and a device for predicting pellet distribution. Background Art

[0002] Shot peening is a widely used surface strengthening process, which is a cold working process that uses pellets to bombard the surface of a workpiece and implant residual compressive stress to improve the fatigue strength of the workpiece. It is widely used to improve the mechanical strength, wear resistance, fatigue resistance, and corrosion resistance of parts. When shot peening a workpiece, in addition to requiring the shot peening to indent the surface of the workpiece to cause plastic deformation of the workpiece, thereby increasing the residual compressive stress, it is also required that the pellets uniformly cover the surface of the workpiece to form uniform indentations and compressive stress layers on the surface of the workpiece, so as to avoid local stress concentration caused by non-uniformly distributed indentations and compressive stress layers, further affecting the fatigue strength and service life of the workpiece and causing unnecessary losses.

[0003] In the traditional shot peening process, it is easy to have non-uniform coverage on the surface of the workpiece, that is, some areas are oversaturated and some areas are undersaturated, which further affects the strengthening quality and service life of the workpiece surface. Summary of the Invention

[0004] The purpose of this application is to provide a device for measuring the radial distribution of pellets, a method and a device for predicting pellet distribution, so as to solve the technical problem in the prior art that due to the non-uniformity of the distribution of the sprayed pellets, it is bound to cause non-uniform coverage of the sprayed area, that is, some areas are oversaturated and some areas are undersaturated, which further affects the strengthening quality and service life of the workpiece surface.

[0005] To achieve the above purpose, a technical solution adopted in this application is:

[0006] Provide a device for measuring the radial distribution of pellets, including:

[0007] A receiving member having a receiving surface, the receiving surface including a plurality of concentric circles dividing it into several annular regions and a central circular region arranged in sequence from the inside to the outside, the radii of the plurality of concentric circles are arranged in an arithmetic progression, and the central circular region and each of the annular regions are provided with receiving grooves, and the receiving grooves extend into the receiving member along a direction perpendicular to the receiving surface;

[0008] A shot peening member disposed on one side of the receiving surface of the receiving member, the shot peening member being used to spray pellets toward the receiving surface along a direction perpendicular to the receiving surface;

[0009] A detecting member disposed at the bottom of the receiving groove, the detecting member being used to detect the mass of the pellets sprayed into the receiving groove.

[0010] In one or more embodiments, a data acquisition unit is further included, and the data acquisition unit is respectively in signal connection with the shot peening part and the detection part to acquire the injection duration of the shot peening part and the feedback signal of the detection part.

[0011] To achieve the above object, another technical solution adopted by this application is:

[0012] Provide a method for predicting pellet distribution, including:

[0013] Based on the preset radial distribution information of pellet quality, calculate the radial mass distribution parameter of pellets. The pellet mass distribution parameter includes the number of pellets distributed per unit time and per unit area in several annular regions and a central circular region of the surface to be processed. The several annular regions and the central circular region are obtained by dividing with a plurality of concentric circles whose radii are arranged in an arithmetic progression;

[0014] Based on the radial mass distribution parameter of pellets, construct a fitting function, and the fitting function represents the number of injected pellets per unit area and per unit time at any radial position;

[0015] Based on the fitting function, the moving shot peening trajectory and the moving shot peening rate, calculate the pellet coverage parameter per unit area of the surface to be processed.

[0016] In one or more embodiments, the step of constructing a fitting function based on the pellet mass distribution parameter includes:

[0017] Based on the pellet mass distribution parameter and the pellet mass, calculate the pellet number distribution parameter. The pellet mass distribution parameter includes the number of injected pellets per unit area and per unit time in each of the annular regions;

[0018] Based on the pellet number distribution parameter, construct a training sample set;

[0019] Use the training sample set to perform fitting calculation on a preset fitting polynomial to obtain the fitting error corresponding to the fitting polynomial, and optimize the fitting polynomial in the direction of minimizing the fitting error to obtain the fitting function.

[0020] In one or more embodiments, the step of calculating the pellet coverage parameter per unit area of the surface to be processed based on the fitting function, the moving shot peening trajectory and the moving shot peening rate includes:

[0021] Based on the moving shot peening trajectory and the moving shot peening rate, determine the sweeping information per unit area. The sweeping information includes the equivalent sweeping area and the sweeping time of the unit area in fixed-point shot peening;

[0022] Determine the pellet coverage parameter per unit area based on the fitting function and the swept information per unit area.

[0023] In one or more embodiments, the moving shot peening trajectory includes at least one unidirectional shot peening trajectory, and the step of determining the swept information per unit area based on the moving shot peening trajectory and the moving shot peening rate includes:

[0024] Based on the unidirectional shot peening trajectory, determine the perpendicular distance between the unit area and the unidirectional shot peening trajectory;

[0025] Based on the perpendicular distance, obtain the equivalent swept area;

[0026] Based on the moving shot peening rate, calculate the swept time for each unit area within the equivalent swept area.

[0027] In one or more embodiments, the step of determining the pellet coverage parameter per unit area based on the fitting function and the swept information per unit area includes:

[0028] Obtain a distance parameter, where the distance parameter includes the distance between each unit area in the equivalent swept area and the shot peening point of the fixed-point shot peening;

[0029] Based on the fitting function, the swept time, and the distance parameter, calculate the number of pellets covered per unit, where the number of pellets covered per unit includes the number of pellets covering each unit area in the equivalent swept area during the fixed-point shot peening;

[0030] Based on the number of pellets covered per unit, determine the pellet coverage parameter per unit area.

[0031] To achieve the above object, another technical solution adopted by this application is:

[0032] Provide a pellet distribution prediction device, including:

[0033] A first calculation module, configured to calculate a pellet mass distribution parameter based on preset radial pellet mass distribution information, where the pellet mass distribution parameter includes the number of distributed pellets per unit area and per unit time in several annular regions and a central circular region on the surface to be processed, and the several annular regions and the central circular region are divided by a plurality of concentric circles with radii arranged in an arithmetic progression;

[0034] A construction module, configured to construct a fitting function based on the pellet mass distribution parameter, where the fitting function represents the number of shot pellets per unit area and per unit time at any radial position;

[0035] A second calculation module calculates the pellet coverage parameter per unit area of the surface to be processed based on the fitting function, the moving shot peening trajectory, and the moving shot peening rate.

[0036] To achieve the above object, another technical solution adopted by this application is:

[0037] Provide an electronic device, including:

[0038] At least one processor; and

[0039] A memory, the memory stores instructions, when the instructions are executed by the at least one processor, the at least one processor is caused to execute the pellet distribution prediction method as described in any of the above embodiments.

[0040] To achieve the above object, another technical solution adopted by this application is:

[0041] Provide a machine-readable storage medium storing executable instructions, the instructions when executed cause the machine to execute the pellet distribution prediction method as described in any of the above embodiments.

[0042] Different from the prior art, the beneficial effects of this application are:

[0043] The pellet radial distribution measurement device of this application can measure the pellet radial mass distribution law of fixed-point shot peening under given parameters, thereby helping to predict the pellet distribution during the moving shot peening process based on this radial mass distribution law, and helping to optimize the moving shot peening process to ensure uniform coverage of pellets;

[0044] This application can establish a fitting function based on the pellet radial mass distribution law of fixed-point shot peening measured by the pellet radial distribution measurement device, calculate the number of ejected pellets at any radial position of the fixed-point shot peening, and based on this number of ejected pellets, predict the pellet coverage parameter per unit area at any position of the surface to be processed during the moving shot peening process, thereby helping to optimize the moving shot peening process to ensure uniform coverage of pellets, which is of great significance for improving the fatigue strength of workpieces. Description of the Drawings

[0045] Figure 1 It is a schematic structural diagram of an embodiment of the pellet radial distribution measurement device of this application;

[0046] Figure 2 It is a schematic internal structural diagram of an embodiment of the pellet radial distribution measurement device of this application;

[0047] Figure 3 It is a schematic working state structural diagram of an embodiment of the pellet radial distribution measurement device of this application;

[0048] Figure 4It is a schematic flow chart of an embodiment of the pellet distribution prediction method of the present application;

[0049] Figure 5 It is Figure 4 a schematic flow chart of an embodiment corresponding to step S300 in

[0050] Figure 6 It is Figure 4 a schematic flow chart of an embodiment corresponding to step S400 in

[0051] Figure 7 It is Figure 6 a schematic flow chart of an embodiment corresponding to step S401 in

[0052] Figure 8 It is a schematic diagram of the mobile shot peening process of the present application;

[0053] Figure 9 It is Figure 6 a schematic flow chart of an embodiment corresponding to step S402 in

[0054] Figure 10 It is a structural block diagram of an embodiment of the pellet distribution prediction device of the present application;

[0055] Figure 11 It is a hardware structure diagram of an embodiment of the electronic device of the present application. Specific Embodiments

[0056] The present application will be described in detail below in conjunction with the embodiments shown in the accompanying drawings. However, these embodiments do not limit the present application, and any structural, method, or functional transformation made by those of ordinary skill in the art based on these embodiments is included in the protection scope of the present application.

[0057] As described in the background art, when shot peening the surface of a workpiece, the coverage of pellets is an important index for evaluating the shot peening effect, which is crucial for ensuring the surface strengthening quality and the service life of the workpiece. During the mobile shot peening process, the shot peening head is constantly moving, and at the same time, the distribution of pellets is uneven, which is very likely to cause non-uniform coverage of pellets during the shot peening strengthening process, that is, some areas are over-saturated covered and some areas are under-saturated covered, thereby affecting the strengthening quality and service life of the workpiece surface.

[0058] To solve the above problems, the applicant has developed a pellet radial distribution measuring device, a pellet distribution prediction method and device, wherein the pellet radial distribution measuring device can measure the distribution of pellets in the radial range during the fixed-point shot peening process, so as to obtain the pellet mass distribution in different radial regions under the fixed-point shot peening with specific parameters.

[0059] The pellet distribution prediction method can predict the pellet coverage parameter at any position on the surface to be processed of the workpiece during the mobile shot peening process based on the pellet mass distribution in different radial regions obtained by the measuring device, thereby contributing to the subsequent optimization of the mobile shot peening process to ensure uniform pellet coverage.

[0060] Specifically, please refer to Figure 1 and Figure 2 , Figure 1 which is a schematic structural diagram of an embodiment of the pellet radial distribution measuring device of the present application, Figure 2 and

[0061] which is a schematic internal structure diagram of an embodiment of the pellet radial distribution measuring device of the present application.

[0062] The receiving member 10 has a receiving surface 100. The receiving surface 100 is divided by a plurality of concentric circles 101 into a plurality of annular regions 102 and a central circular region 103 arranged in sequence from the inside to the outside. The radii of the plurality of concentric circles 101 are arranged in an arithmetic progression. The central circular region 103 and each annular region 102 are provided with receiving grooves 104. The receiving grooves 104 extend towards the inside of the receiving member in a direction perpendicular to the receiving surface 100.

[0063] The difference in radius between adjacent concentric circles 101 is greater than the pellets, so that the pellets can be sprayed into the inside of the receiving groove

[0064] The shot peening member 20 is arranged on one side of the receiving surface 100 of the receiving member 10. The shot peening member 20 is used to spray pellets towards the receiving surface 100 in a direction perpendicular to the receiving surface 100.

[0065] The detecting member 30 is arranged at the bottom of the receiving groove 104. The detecting member 30 is used to detect the mass of the pellets sprayed into the inside of the receiving groove 104.

[0066] Please refer to Figure 3 , Figure 3 which is a schematic structural diagram of the working state of an embodiment of the pellet radial distribution measuring device of the present application.

[0067] It can be understood that when the pellets are sprayed towards the receiving surface 100 by the shot peening member, the pellets sprayed towards a specific radial region will enter the corresponding receiving groove 104 in that region. By detecting the mass of the pellets entering the inside of the receiving groove 104, the pellet coverage mass in that radial region can be obtained.

[0068] It should be noted that in order to ensure the accuracy and perfection of the measurement, it is necessary to ensure that the size of the receiving surface 100 is larger than the coverage range of the shot peening.

[0069] In this embodiment, the detection member 30 can be a mass acquisition sensor. By acquiring the mass of the pellets carried in each receiving groove 103, the mass signal m in each receiving groove 104 can be directly obtained. i , where i is the number of the receiving groove 104.

[0070] In other embodiments, the detection member 30 can also be a pressure sensor or the like, and the effects of this embodiment can be achieved.

[0071] By taking the ratio of the mass signal to time and area, the shot peening mass per unit time and unit area can be further obtained.

[0072] To facilitate the acquisition of the time signal and the feedback signal of the detection member 30, a data acquisition unit 40 is further installed on the side of the receiving member 10 in this embodiment. The data acquisition unit 40 is respectively signal-connected to the shot peening member 20 and the detection member 30 to acquire the spraying duration of the shot peening member 20 and the feedback signal of the detection member 30.

[0073] The data acquisition unit 40 can be a signal processing module such as a single-chip microcomputer, and it can be connected to the shot peening member 20 and the detection member 30 through a wireless network or any other means to acquire relevant signals.

[0074] After obtaining the mass signal in the radial region and the time signal of the shot peening member 20 during the fixed-point shot peening process, the pellet coverage parameter at any position on the surface to be processed of the workpiece for the moving shot peening can be predicted.

[0075] It can be understood that the shot peening height h and the shot peening flow rate M of this measuring device should be the same as those of the moving shot peening to be predicted to ensure the accuracy and applicability of the data.

[0076] Specifically, please refer to Figure 4 , Figure 4 which is a schematic flowchart of an embodiment of the pellet distribution prediction method of this application.

[0077] The pellet distribution prediction method includes:

[0078] S100. Calculate the pellet mass distribution parameter based on the preset radial distribution information of the pellet mass.

[0079] First, obtain the pellet mass signal m in any annular region and the central circular region during the fixed-point shot peening measured by the above measuring device i , that is, the preset radial distribution information of the pellet mass.

[0080] Take the ratio of the pellet mass signal m i to the time t of the fixed-point shot peening, and the pellet mass distributed in the annular region and the central circular region per unit time can be obtained:

[0081] Furthermore, according to the areas of the annular region and the central circular region, the mass distribution of pellets per unit time and per unit area in the annular region and the central circular region can be obtained. Among them, the area S of the annular region i = π * (r i 2 - r i-1 2 ), where i is the number of the annular region.

[0082] In an application scenario, the radius of the central circular region can be set to dr, and the radius difference between adjacent concentric circles can be set to dr, and then r i = i * dr can be further obtained, so as to calculate m i dtds , and the pellet mass distribution parameters can be obtained.

[0083] It can be understood that in other application scenarios, the radius of the central circular region does not have to be the same as the radius difference between adjacent concentric circles, and the effects of this embodiment can be achieved.

[0084] S200. Based on the pellet mass distribution parameters, construct a fitting function.

[0085] After knowing the pellet mass distribution in each annular region and the central circular region, a correlation function between the radial distance and the pellet distribution can be constructed, so as to further obtain the pellet distribution at any radial position.

[0086] Specifically, the fitting process can be carried out by constructing a neural network model through machine learning, or by using fitting methods such as polynomial fitting, and the effects of this embodiment can be solved.

[0087] Taking polynomial fitting as an example below, the fitting process will be introduced in detail. Please refer to Figure 5 , Figure 5 is Figure 4 a schematic flow chart of an embodiment corresponding to step S200 in

[0088] The method for constructing the fitting function includes:

[0089] S201. Based on the pellet mass distribution parameters and the pellet mass, calculate the pellet number distribution parameters.

[0090] First, convert the mass distribution of pellets into the number distribution of pellets. According to the average diameter d w of the ejected pellets and the density ρ w , the average mass of the pellets can be obtained

[0091] By taking the ratio of the pellet mass distribution parameter to the average mass of the pellets, the number of pellets distributed in the annular region and the central circular region per unit time and per unit area can be obtained:

[0092]

[0093] S202. Construct a training sample set based on the pellet number distribution parameter.

[0094] Based on the obtained pellet number distribution parameter above, the number of pellets distributed per unit time and per unit area in all annular regions and the central circular region can be calculated. Assuming the maximum value of i is n, n groups of data can be obtained as the training sample set.

[0095] S203. Use the training sample set to perform fitting calculations on a preset fitting polynomial, obtain the fitting error corresponding to the fitting polynomial, and optimize the fitting polynomial in the direction of minimizing the fitting error to obtain a fitting function.

[0096] First, construct a fitting polynomial:

[0097]

[0098] Among them, A0…Am are fitting coefficients. Substitute the radius values of the n groups of data in the training sample set into the above fitting polynomial to obtain n polynomials:

[0099] N' = A0 + A1r + … + A i r i + … + A m r m

[0100] In an application scenario, the outer ring diameter of each annular region and the central circular region can be used as the radius value of the region and substituted into the above fitting polynomial; in other application scenarios, the radius value at the center position of each annular region and the central circular region can also be used as the radius value of the region, and the effects of this embodiment can be achieved in both cases.

[0101] Calculate the sum of the squares of the errors between the actually distributed number of pellets N of the n groups of data in the training sample set and the above polynomial N' to obtain a loss function:

[0102]

[0103] Take the partial derivatives of the above formula with respect to n + 1 fitting coefficients respectively, and set the partial derivatives to 0 to obtain n + 1 equations. Based on the n + 1 equations, calculate the optimal selection values of the fitting coefficients, and finally calculate the fitting function.

[0104] S300. Calculate the pellet coverage parameter per unit area of the surface to be processed based on the fitting function, the moving shot peening trajectory, and the moving shot peening rate.

[0105] Based on the fitting function obtained in the above steps, the number of pellets distributed per unit time and per unit area at any radial position on the surface to be processed during fixed-point shot peening can be predicted.

[0106] The process of moving shot peening can be regarded as a set of processes of multiple fixed-point shot peenings. Therefore, based on the above fitting function and the parameters of moving shot peening, the pellet coverage parameter per unit area on the surface to be processed during moving shot peening can be further predicted. Specifically, please refer to Figure 6 , Figure 6 which Figure 4 is a schematic flowchart of an embodiment corresponding to step S400 in

[0107] S301. Determine the sweeping information per unit area based on the moving shot peening trajectory and the moving shot peening rate.

[0108] Specifically, the sweeping information includes the equivalent sweeping area and the sweeping time of the unit area during fixed-point shot peening.

[0109] During the sweeping process of the pellet spraying area, the pellet coverage area at any position in the covered area of the surface to be processed can be equivalent to the total number of pellets distributed in a partial sweeping area in the pellet spraying area at a certain moment. This partial sweeping area is the equivalent sweeping area, and the sweeping time can be obtained based on the moving shot peening rate.

[0110] Please refer to Figure 7 , Figure 7 which Figure 6 is a schematic flowchart of an embodiment corresponding to step S401 in

[0111] The steps for determining the sweeping information include:

[0112] S3011. Determine the perpendicular distance between the unit area and the unidirectional shot peening trajectory based on the unidirectional shot peening trajectory.

[0113] S3012. Obtain the equivalent sweeping area based on the perpendicular distance;

[0114] Please refer to Figure 8 , Figure 8It is a schematic diagram of the mobile shot peening process of this application. In an application scenario, taking the unidirectional shot peening trajectory along the x direction as an example, the number of shot particles covering a unit area at any position A with an arbitrary ordinate y in the covered area of the surface to be processed can be equivalent to the number of shot particles in all areas with the same ordinate y as the unit area at position A in the shot particle ejection area at a certain moment. All these areas with the same ordinate y are the equivalent swept areas of the unit area A.

[0115] Specifically, the unit area at any position A can be recognized as a square grid with a side length of lr. At the same time, this equivalent swept area can be recognized as a rectangular area composed of k square grids with a side length of lr. The value of k can be determined according to the chord length L when the ordinate in the shot particle ejection area is y, that is, k = L / lr, and the value is rounded up.

[0116] The ordinate of the unidirectional shot peening trajectory along the x direction can be recognized as 0. At this time where R is the radius of the shot particle ejection area, which can be obtained based on the fitting function.

[0117] It can be understood that in other application scenarios, when the unidirectional shot peening trajectory is not set along the x direction, the corresponding equivalent swept area with the same vertical distance can also be obtained based on the vertical distance between this unit area and the unidirectional shot peening trajectory, and the effects of this embodiment can be achieved.

[0118] S3013 Calculate the sweeping time of each unit area in the equivalent swept area based on the mobile shot peening rate.

[0119] Taking the above unidirectional shot peening trajectory along the x direction as an example, based on the side length lr of the unit area and the mobile shot peening rate v, the sweeping time of each square grid can be calculated

[0120] S302 Determine the shot particle coverage parameters of the unit area based on the fitting function and the sweeping information of the unit area.

[0121] When the equivalent swept area and the sweeping time of the unit area on the surface to be processed in the fixed-point shot peening are determined, the shot particle coverage parameters of the unit area can be calculated based on the fitting function.

[0122] Specifically, please refer to Figure 9 , Figure 9 is Figure 6 a schematic flowchart of an embodiment corresponding to step S402 in

[0123] S3021 Obtain the distance parameter.

[0124] First, obtain the distance parameter r including the distance between each unit area in the equivalent swept area and the shot peening point of the fixed-point shot peening j .

[0125] In an application scenario, the distance between the center of any square grid and the injection center can be used as the distance parameter r j , in other application scenarios, the distance between other positions of the square grid and the injection center can also be used as the distance parameter, and the effects of this embodiment can be achieved in both cases.

[0126] As Figure 8 shown, according to the cosine theorem, it can be calculated where l rj is the total length l of the j grids rj = j × l r , cosθ is the cosine of the chord angle θ at the ordinate y, which can be expressed as

[0127] S3022. Calculate the number of pellets covered per unit based on the fitting function, sweep time, and distance parameter.

[0128] After obtaining the distance coefficient r between any square grid and the injection center j and the corresponding sweep time t of the square grid z , substituting the above data into the fitting function, the number of pellets covered in each square grid, that is, the number of pellets covered per unit, can be obtained:

[0129] N j = f N (r j ) * l r 2 * t z

[0130] where j is the number of the square grid, and l r 2 is the grid area.

[0131] S3023. Determine the pellet coverage parameter per unit area based on the number of pellets covered per unit.

[0132] By summing up the number of pellets covered per unit of all square grids, the pellet coverage parameter per unit area can be obtained:

[0133]

[0134] It can be understood that the above embodiments only introduce the calculation process of the pellet coverage parameter per unit area by taking the unidirectional shot peening trajectory as an example. In other embodiments, when there are multiple unidirectional shot peening trajectories, the pellet coverage parameter per unit area of each unidirectional shot peening trajectory can be calculated one by one and then superimposed; in some special working conditions, when the moving shot peening trajectory includes a curved shot peening trajectory, discrete points evenly distributed can also be taken on the curved shot peening trajectory, and each discrete point is used as the spraying point of fixed-point shot peening. The moving shot peening process can be discretized into multiple fixed-point shot peening processes, and the pellet coverage parameter per unit area can be calculated respectively and then superimposed, all of which can achieve the effects of this embodiment.

[0135] The present application also provides a pellet distribution prediction device. Please refer to Figure 10 , Figure 10 which is a structural block diagram of an embodiment of the pellet distribution prediction device of the present application.

[0136] The prediction device includes a first calculation module 21, a construction module 22, and a second calculation module 23.

[0137] Among them, the first calculation module 21 is used to calculate the pellet mass distribution parameter based on the radial distribution information of the pellet mass; the construction module 22 is used to construct a fitting function based on the pellet mass distribution parameter, and the fitting function represents the number of sprayed pellets per unit area and per unit time at any radial position; the second calculation module 23 calculates the pellet coverage parameter per unit area of the surface to be processed based on the fitting function, the moving shot peening trajectory, and the moving shot peening rate.

[0138] As described above with reference to Figures 3 to 9 , the pellet distribution prediction method according to the embodiments of this specification has been described. The details mentioned in the above description of the method embodiments also apply to the pellet distribution prediction device of the embodiments of this specification. The above pellet distribution prediction device can be implemented by hardware, or can be implemented by software or a combination of hardware and software.

[0139] Please refer to Figure 11 , Figure 11 which is a hardware structure diagram of an embodiment of the electronic device of the present application. As Figure 11 shown, the electronic device 30 may include at least one processor 31, a memory 32 (such as a non-volatile memory), a memory 33, and a communication interface 34, and at least one processor 31, the memory 32, the memory 33, and the communication interface 34 are connected together via a bus 35. At least one processor 31 executes at least one computer-readable instruction stored or encoded in the memory 32.

[0140] It should be understood that the computer-executable instructions stored in the memory 32, when executed, cause at least one processor 31 to perform the above in the various embodiments of this specification in combination withFigures 3 - 9 The various operations and functions described.

[0141] In the embodiments of this specification, the electronic device 30 may include, but is not limited to: personal computers, server computers, workstations, desktop computers, laptop computers, notebook computers, mobile electronic devices, smart phones, tablet computers, cellular phones, personal digital assistants (PDAs), handheld devices, messaging devices, wearable electronic devices, consumer electronic devices, and so on.

[0142] According to one embodiment, there is provided a program product such as a machine-readable medium. The machine-readable medium may have instructions (i.e., the elements implemented in software as described above), which when executed by a machine, cause the machine to perform the various operations and functions described above in the respective embodiments of this specification in combination with Figures 3 - 9 the various operations and functions described. Specifically, a system or device equipped with a readable storage medium may be provided, on which software program code for implementing the functions of any one of the above embodiments is stored, and cause a computer or processor of the system or device to read and execute the instructions stored in the readable storage medium.

[0143] In this case, the program code read from the readable medium itself can implement the functions of any one of the above embodiments, so the machine-readable code and the readable storage medium storing the machine-readable code constitute a part of this specification.

[0144] Examples of the readable storage medium include floppy disks, hard disks, magneto-optical disks, optical disks (such as CD-ROM, CD-R, CD-RW, DVD-ROM, DVD-RAM, DVD-RW, DVD-RW), magnetic tapes, non-volatile memory cards, and ROMs. Optionally, the program code can be downloaded from a server computer or a cloud via a communication network.

[0145] Those skilled in the art should understand that the various embodiments disclosed above can be variously deformed and modified without departing from the essence of the invention. Therefore, the protection scope of this specification should be defined by the appended claims.

[0146] It should be noted that not all steps and units in the above-mentioned various processes and system structure diagrams are necessary, and some steps or units can be ignored according to actual needs. The execution order of the steps is not fixed and can be determined as needed. The device structures described in the above embodiments can be physical structures or logical structures, that is, some units may be implemented by the same physical entity, or some units may be implemented separately by multiple physical entities, or some components in multiple independent devices may be jointly implemented.

[0147] In the above embodiments, the hardware units or modules can be implemented mechanically or electrically. For example, a hardware unit, module, or processor can include permanent dedicated circuits or logic (such as a dedicated processor, FPGA, or ASIC) to perform the corresponding operations. The hardware unit or processor can also include programmable logic or circuits (such as a general-purpose processor or other programmable processor), which can be temporarily configured by software to perform the corresponding operations. The specific implementation method (mechanical, or dedicated permanent circuits, or temporarily configured circuits) can be determined based on cost and time considerations.

[0148] The foregoing description of the disclosure is provided to enable any ordinary person skilled in the art to implement or use the disclosure. Various modifications to the disclosure will be apparent to those of ordinary skill in the art, and the general principles corresponding to the present disclosure can also be applied to other variations without departing from the scope of protection of the disclosure. Therefore, the disclosure is not limited to the examples and designs described herein, but is consistent with the broadest scope that conforms to the principles and novel features disclosed herein.

Claims

1. A method for predicting pellet distribution, characterized in that, Including: Based on the preset radial distribution information of pellet quality, calculate the pellet quality distribution parameters. The pellet quality distribution parameters include the number of pellets distributed per unit time and per unit area in several annular regions and the central circular region of the surface to be processed. The several annular regions and the central circular region are obtained by dividing with multiple concentric circles whose radii are arranged in an arithmetic progression; Based on the pellet quality distribution parameters, construct a fitting function, where the fitting function represents the number of sprayed pellets per unit area and per unit time at any radial position; Based on the fitting function, the moving shot peening trajectory, and the moving shot peening rate, calculate the pellet coverage parameter per unit area of the surface to be processed; The step of calculating the pellet coverage parameter per unit area of the surface to be processed based on the fitting function, the moving shot peening trajectory, and the moving shot peening rate includes: Based on the moving shot peening trajectory and the moving shot peening rate, determine the sweeping information per unit area. The sweeping information includes the equivalent sweeping area and the sweeping time of the unit area in fixed-point shot peening; Based on the fitting function and the sweeping information per unit area, determine the pellet coverage parameter per unit area; The moving shot peening trajectory includes at least one one-way shot peening trajectory. The step of determining the sweeping information per unit area based on the moving shot peening trajectory and the moving shot peening rate includes: Based on the one-way shot peening trajectory, determine the perpendicular distance between the unit area and the one-way shot peening trajectory; Based on the perpendicular distance, obtain the equivalent sweeping area; Based on the moving shot peening rate, calculate the sweeping time of each unit area within the equivalent sweeping area; The step of determining the pellet coverage parameter per unit area based on the fitting function and the sweeping information per unit area includes: Obtain distance parameters, where the distance parameters include the distance between each unit area in the equivalent sweeping area and the shot peening point of the fixed-point shot peening; Based on the fitting function, the sweeping time, and the distance parameters, calculate the unit pellet coverage quantity, where the unit pellet coverage quantity includes the number of pellets covering each unit area in the equivalent sweeping area in the fixed-point shot peening; Based on the unit pellet coverage quantity, determine the pellet coverage parameter per unit area.

2. The pellet distribution prediction method according to claim 1, wherein The step of constructing a fitting function based on the pellet quality distribution parameters includes: Based on the pellet quality distribution parameters and the pellet quality, calculate the pellet number distribution parameters. The pellet number distribution parameters include the number of sprayed pellets per unit area and per unit time in each of the annular regions; Based on the pellet number distribution parameters, construct a training sample set; Use the training sample set to perform fitting calculation on a preset fitting polynomial to obtain the fitting error corresponding to the fitting polynomial, and optimize the fitting polynomial in the direction of minimizing the fitting error to obtain the fitting function.

3. A pellet distribution prediction device, characterized in that, Including: A first calculation module, configured to calculate pellet mass distribution parameters based on preset radial pellet mass distribution information, where the pellet mass distribution parameters include the number of distributed pellets per unit time and per unit area in a plurality of annular regions and a central circular region of the surface to be processed, and the plurality of annular regions and the central circular region are obtained by dividing with a plurality of concentric circles whose radii are arranged in an arithmetic progression; A construction module, configured to construct a fitting function based on the pellet mass distribution parameters, where the fitting function represents the number of sprayed pellets per unit area and per unit time at any radial position; A second calculation module, configured to calculate the pellet coverage parameter per unit area of the surface to be processed based on the fitting function, the moving shot peening trajectory, and the moving shot peening rate; Wherein, the calculating the pellet coverage parameter per unit area of the surface to be processed based on the fitting function, the moving shot peening trajectory, and the moving shot peening rate includes: Determining the sweeping information per unit area based on the moving shot peening trajectory and the moving shot peening rate, where the sweeping information includes the equivalent sweeping region and the sweeping time of the unit area in the fixed-point shot peening; Determining the pellet coverage parameter per unit area based on the fitting function and the sweeping information per unit area; The moving shot peening trajectory includes at least one one-way shot peening trajectory, and the step of determining the sweeping information per unit area based on the moving shot peening trajectory and the moving shot peening rate includes: Determining the perpendicular distance between the unit area and the one-way shot peening trajectory based on the one-way shot peening trajectory; Obtaining the equivalent sweeping region based on the perpendicular distance; Calculating the sweeping time of each unit area in the equivalent sweeping region based on the moving shot peening rate; The step of determining the pellet coverage parameter per unit area based on the fitting function and the sweeping information per unit area includes: Obtaining a distance parameter, where the distance parameter includes the distance between each unit area in the equivalent sweeping region and the shot peening point of the fixed-point shot peening; Calculating the number of pellets per unit coverage based on the fitting function, the sweeping time, and the distance parameter, where the number of pellets per unit coverage includes the number of pellets covering each unit area in the equivalent sweeping region in the fixed-point shot peening; Determining the pellet coverage parameter per unit area based on the number of pellets per unit coverage.

4. An electronic device, characterized in that, Comprising: At least one processor; And A memory storing instructions that, when executed by the at least one processor, cause the at least one processor to execute the pellet distribution prediction method according to any one of claims 1 to 2.

5. A machine-readable storage medium, characterized in that, Stored with executable instructions that, when executed, cause the machine to execute the pellet distribution prediction method according to any one of claims 1 to 2.

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