A device cleanliness determination method and apparatus, electronic device, and storage medium

Abstract

The application discloses a device cleanliness determination method and device, electronic equipment and storage medium, wherein the method comprises: determining a to-be-adjusted model corresponding to a to-be-detected device, and obtaining at least one group of to-be-used parameters associated with the to-be-adjusted model; performing parameter adjustment on the to-be-adjusted model based on the at least one group of to-be-used parameters to obtain a to-be-used model; determining a to-be-used cleanliness corresponding to the to-be-detected device based on the to-be-used model; determining a to-be-used weight corresponding to the to-be-used cleanliness, and determining a target cleanliness of the to-be-detected device based on the to-be-used cleanliness and the to-be-used weight. The problem that the device cleanliness of the to-be-detected device cannot be accurately determined, resulting in excessive or untimely cleaning, is solved, and the effect of accurately determining the device cleanliness of the to-be-detected device and determining whether the to-be-detected device needs to be cleaned is achieved.

Description

Technical Field

[0001] This invention relates to the field of tobacco equipment processing technology, and in particular to a method, apparatus, electronic device, and storage medium for determining the cleanliness of equipment. Background Technology

[0002] Due to the complexity of the online laser drilling process and the small area of ​​dust accumulation on the components of the laser drilling equipment, it is impossible to directly observe the cleanliness of the laser drilling equipment.

[0003] Currently, the cleaning frequency and time for laser drilling equipment are usually determined based on manual experience. However, this method cannot accurately determine the cleanliness of the laser drilling equipment. Therefore, there may be problems such as untimely cleaning or excessive cleaning, which wastes manpower.

[0004] To address the aforementioned issues, it is necessary to improve the method for determining equipment cleanliness so that laser equipment can be cleaned accordingly based on its cleanliness level. Summary of the Invention

[0005] This invention provides a method, apparatus, electronic device, and storage medium for determining the cleanliness of equipment, in order to solve the problem of being unable to accurately determine the cleanliness of the equipment to be tested, resulting in excessive cleaning or untimely cleaning.

[0006] In a first aspect, embodiments of the present invention provide a method for determining the cleanliness of equipment, comprising:

[0007] A model to be adjusted corresponding to the device under test is determined, and at least one set of parameters to be used associated with the device under test is obtained; wherein, the at least one set of parameters to be used includes device running time, number of holes, pulse width, and cigarette paper thickness processed based on the device under test;

[0008] Based on the at least one set of parameters to be used, the parameters of the device to be tested are adjusted to obtain the model to be used;

[0009] Based on the model to be used, determine the cleanliness level to be used corresponding to the equipment to be tested;

[0010] Determine the weight to be used corresponding to the cleanliness level to be used, and determine the target cleanliness level of the device to be tested based on the cleanliness level to be used and the weight to be used.

[0011] Secondly, embodiments of the present invention also provide a device for determining equipment cleanliness, comprising:

[0012] The parameter acquisition module is used to determine the adjustment model corresponding to the device under test and acquire at least one set of parameters to be used associated with the device under test; wherein, the at least one set of parameters to be used includes device running time, number of holes, pulse width and cigarette paper thickness processed based on the device under test;

[0013] The model to be used determination module is used to adjust the parameters of the device to be tested based on the at least one set of parameters to be used, so as to obtain the model to be used;

[0014] The cleanliness determination module is used to determine the cleanliness level to be used corresponding to the device to be tested based on the model to be used.

[0015] The target cleanliness determination module is used to determine the weight to be used corresponding to the cleanliness to be used, and to determine the target cleanliness of the device to be tested based on the cleanliness to be used and the weight to be used.

[0016] Thirdly, embodiments of the present invention also provide an electronic device, comprising:

[0017] At least one processor; and

[0018] A memory communicatively connected to the at least one processor; wherein,

[0019] The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the equipment cleanliness determination method according to any embodiment of the present invention.

[0020] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing computer instructions, which are used to cause a processor to execute the equipment cleanliness determination method described in any embodiment of the present invention.

[0021] The technical solution of this embodiment involves determining an adjustment model corresponding to the device under test and obtaining at least one set of parameters to be used associated with the adjustment model. The device under test is simulated using simulation software to obtain an adjustment model corresponding to the device under test. Based on the parameters to be used corresponding to the device under test, at least one set of parameters to be used corresponding to the adjustment model is determined. A linear regression algorithm is used to determine the reference cleanliness corresponding to each set of parameters to be used. The adjustment model is then adjusted based on the at least one set of parameters to be used to obtain a model to be used. Based on each set of parameters to be used and the corresponding reference cleanliness, the parameter information corresponding to the adjustment model can be determined. The adjustment model is then adjusted based on the parameter information to obtain the model to be used. Based on the model to be used, the cleanliness to be used corresponding to the device under test is determined. The current parameters to be used corresponding to the device under test and the cleanliness of the device corresponding to the current parameters to be used are also determined, thus obtaining the cleanliness to be used corresponding to the model to be used. A weight corresponding to the desired cleanliness level is determined, and based on the desired cleanliness level and the weight, a target cleanliness level for the device under test is determined. The weight corresponding to the desired cleanliness level is determined according to the influence of the cleaning air pressure parameter. The target cleanliness level is obtained by multiplying the desired cleanliness level and the weight, thus characterizing the degree of dust accumulation on the surface of the device under test. This method solves the problem of inaccurately determining the cleanliness level of the device under test, leading to excessive cleaning or untimely cleaning. It achieves the effect of accurately determining the cleanliness level of the device under test and determining whether cleaning is necessary based on the cleanliness level.

[0022] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 This is a flowchart of a method for determining equipment cleanliness according to Embodiment 1 of the present invention;

[0025] Figure 2 This is a flowchart of a method for determining equipment cleanliness according to Embodiment 2 of the present invention;

[0026] Figure 3 This is a schematic diagram of an image of the dust accumulation area of ​​the device under test, as provided in Embodiment 2 of the present invention;

[0027] Figure 4 This is a schematic diagram of a binary image corresponding to an image of a ash accumulation area provided in Embodiment 2 of the present invention;

[0028] Figure 5 This is a schematic diagram illustrating the mapping relationship between the parameters to be used and the reference cleanliness level according to Embodiment 2 of the present invention;

[0029] Figure 6 This is a curve showing the relationship between equipment cleanliness and cleaning air pressure parameters according to Embodiment 2 of the present invention;

[0030] Figure 7 This is a schematic diagram of a device for determining the cleanliness of equipment according to Embodiment 3 of the present invention;

[0031] Figure 8 This is a schematic diagram of the structure of an electronic device that implements the equipment cleanliness determination method of the present invention. Detailed Implementation

[0032] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0033] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in sequences other than those illustrated or described herein.

[0034] Example 1

[0035] Figure 1The present invention provides a flowchart of a method for determining the cleanliness of equipment in Embodiment 1. This embodiment is applicable to situations where the cleanliness of a laser drilling device for a cigarette machine is detected, and the need for cleaning of the laser drilling device for the cigarette machine is determined based on the cleanliness. This method can be executed by an equipment cleanliness determination device, which can be implemented in hardware and / or software. The equipment cleanliness determination device can be configured in a computing device capable of executing the equipment cleanliness determination method.

[0036] like Figure 1 As shown, the method includes:

[0037] S110. Determine the adjustment model corresponding to the device under test, and obtain at least one set of parameters to be used associated with the device under test.

[0038] In this technical solution, the device to be tested can be a laser drilling device for cigarette machines. During the online drilling process of cigarette sticks, dust generated by laser ablation adheres to the surface of the focusing lens, producing a thermal effect that reduces focusing efficiency and damages the lens coating. Simultaneously, dust adheres to the laser exit of the jet nozzle, obstructing the laser beam and reducing cleanliness. These effects reduce ventilation stability and product quality stability, shorten the maintenance cycle and lifespan of the focusing lens equipment, and impact production efficiency. To improve the production efficiency and drilling accuracy of the laser drilling device, a model can be created to obtain an adjustable model. At least one set of parameters to be used includes the device's operating time, number of holes drilled, pulse width, and the thickness of the cigarette paper processed by the device.

[0039] Specifically, a three-dimensional model corresponding to the device under test is constructed to obtain the model to be adjusted, and at least one set of parameters to be used related to the device under test are obtained. The model to be adjusted is then adjusted based on each set of parameters to obtain the model to be used corresponding to the device under test.

[0040] For example, each set of parameters includes information such as equipment running time, number of holes punched, pulse width, and the thickness of the cigarette paper processed by the equipment under test. Based on each parameter, the corresponding equipment cleanliness can be obtained, and the need for cleaning of the equipment under test can be determined according to the equipment cleanliness. Here, equipment cleanliness can be understood as the dust accumulation on the surface of the equipment under test. The higher the dust accumulation, the lower the equipment cleanliness, and vice versa. It can be understood that the lower the equipment cleanliness, the greater the need for cleaning equipment. In other words, as the equipment cleanliness decreases, the equipment under test needs to be cleaned in a timely manner.

[0041] Optionally, determine the adjustment model corresponding to the device under test and obtain at least one set of parameters to be used associated with the device under test, including: performing simulation on the device under test based on simulation software to obtain the adjustment model corresponding to the device under test; and determining at least one set of parameters to be used corresponding to the device under test based on the equipment parameters and process parameters of the device under test.

[0042] The simulation software can be understood as 3D simulation software used to model the equipment under test. By simulating the equipment using this software, a corresponding adjustable model can be obtained. For example, when simulating the equipment using the simulation software, the simulation can be based on the spatial area where dust is generated or flows. That is, the cleanliness of the surface of the equipment may differ at different times. Therefore, the influencing factors of the area where the equipment is located at the current moment can be simulated. In other words, the simulated equipment is correlated with the amount of dust and dirt in the area where the equipment is located at the current moment. Equipment parameters can be understood as parameters corresponding to the equipment under test, such as the model number. Process parameters can be understood as the process parameters of the equipment under test when perforating cigarettes, such as the cigarette brand, cigarette paper thickness, cigarette ventilation, number of perforations, and laser pulse width. In other words, the process parameters match the process parameters of the cigarettes processed by the equipment under test.

[0043] Specifically, based on the actual spatial positions and connection relationships of each structural component of the equipment under test, the three-dimensional spatial structure of dust generation and flow between the components is determined. This spatial structure is then discretized into a mesh, and numerical simulation is performed to obtain an adjustable model corresponding to the equipment under test. Simultaneously, at least one set of parameters corresponding to the equipment under test, including equipment parameters and process parameters, are acquired. Based on these parameters, the adjustable model corresponding to the equipment under test is adjusted, and the adjusted model is used as the model to be used.

[0044] S120. Adjust the parameters of the model to be adjusted based on at least one set of parameters to be used, and obtain the model to be used.

[0045] In this technical solution, each set of parameters to be used corresponds to a certain level of equipment cleanliness. In order to enable the model to be adjusted to better simulate the operation of the equipment to be tested, and to obtain a level of equipment cleanliness that is closer to that of the equipment to be tested based on the model to be adjusted, the parameters of the model to be adjusted can be adjusted based on each set of parameters to be used and the corresponding level of equipment cleanliness to obtain the model to be used.

[0046] Optionally, the device to be tested is adjusted based on at least one set of parameters to be used to obtain a model to be used, including: processing each set of parameters to be used based on a linear regression algorithm to obtain a reference cleanliness corresponding to each set of parameters to be used; adjusting the model to be adjusted based on each set of parameters to be used and the corresponding reference cleanliness to obtain a model to be used.

[0047] The reference cleanliness level can be understood as the cleanliness level corresponding to the device under test, calculated based on each set of parameters to be used. In other words, the cleanliness level varies depending on the different sets of parameters. Multiple reference cleanliness levels can be obtained by calculating based on multiple sets of parameters. By adjusting the parameters of the model to be adjusted according to the correspondence between each set of parameters and the corresponding reference cleanliness level, the model to be used can be obtained.

[0048] Specifically, after obtaining the parameters to be used in each group, the parameters to be used in each group are processed based on the linear regression algorithm to obtain the corresponding reference cleanliness. Based on the parameters to be used in each group and the corresponding reference cleanliness, the parameters of the model to be adjusted are adjusted to obtain the model to be used.

[0049] For example, based on at least one set of parameters to be used corresponding to the device under test, a linear regression algorithm can be used to calculate the reference cleanliness of each set of parameters, and a corresponding cleanliness reference table can be established to record each set of parameters and its corresponding reference cleanliness. The model to be used can then be adjusted based on the parameters and their corresponding reference cleanliness in this cleanliness reference table to obtain the model to be used.

[0050] Optionally, based on each set of parameters to be used and the corresponding reference cleanliness, the parameters of the model to be adjusted are adjusted to obtain the model to be used, including: determining the cleanliness fitting equation corresponding to the model to be adjusted; determining each fitting parameter to be determined in the cleanliness fitting equation based on each set of parameters to be used and the corresponding reference cleanliness; and adjusting the parameters of the model to be adjusted based on each fitting parameter to be determined to obtain the model to be used.

[0051] The cleanliness fitting equation can be understood as an equation that fits and calculates various reference cleanliness levels. It includes at least one fitting parameter to be determined. This parameter can be understood as an unknown parameter in the cleanliness fitting equation. By substituting each set of parameters to be used and the corresponding reference cleanliness levels into the cleanliness fitting equation, the undetermined fitting parameter can be obtained.

[0052] Specifically, after obtaining each set of parameters to be used and the corresponding reference cleanliness, these parameters and reference cleanliness are substituted into the cleanliness fitting equation to solve for the undetermined fitting parameters. Furthermore, these undetermined fitting parameters can be used as adjustment parameters for the model to be adjusted. Based on these parameters, the model to be adjusted is obtained, leading to the model to be used.

[0053] S130. Based on the model to be used, determine the cleanliness level to be used corresponding to the equipment to be tested.

[0054] Here, the cleanliness to be used can be understood as the cleanliness obtained by simulating the equipment to be tested based on the model to be used.

[0055] It is understandable that the parameters of the model to be used are quite similar to those of the device to be tested. Therefore, the device to be tested can be simulated based on the model to obtain the cleanliness level corresponding to the device. For example, a set of parameters to be used corresponding to the device to be tested can be input, and the cleanliness level of the device obtained based on the model to be used is the cleanliness level to be used.

[0056] It should be noted that the cleanliness of the equipment under test is related not only to the parameters to be used, but also to the cleaning air pressure during cleaning. Therefore, the cleanliness obtained at this stage is not the final cleanliness of the equipment under test. The specific method for determining the cleanliness of the equipment will be explained in detail in subsequent steps.

[0057] Optionally, based on the model to be used, the cleanliness level to be used corresponding to the device to be tested is determined, including: obtaining the current parameters to be used corresponding to the device to be tested; and calculating the cleanliness level of the current parameters to be used based on the model to be used, thereby obtaining the cleanliness level to be used corresponding to the device to be tested.

[0058] Here, the currently used parameter can be understood as any set of parameters to be used. Only one set of parameters to be used is used as an example of the currently used parameter.

[0059] Specifically, the current parameters to be used are input into the model to be used, and the current parameters to be used are calculated based on the model to obtain the cleanliness level to be used corresponding to the current parameters to be used.

[0060] S140. Determine the weight to be used corresponding to the cleanliness level to be used, and determine the target cleanliness level of the equipment to be tested based on the cleanliness level to be used and the weight to be used.

[0061] The "weight to be used" characterizes the influence of the cleaning air pressure parameter during the cleaning of the equipment under test on the cleanliness level of the equipment under test. The higher the influence, the larger the weight to be used; conversely, the lower the influence, the smaller the weight to be used. The target cleanliness level can be understood as the final cleanliness level of the equipment under test, obtained from simulation based on the model to be used.

[0062] In practical applications, the equipment under test is cleaned by a cleaning module during operation to maintain its cleanliness. Therefore, the impact of cleaning air pressure parameters on the cleanliness of the equipment must be considered, and the weight for use must be determined based on the degree of influence of cleaning air pressure parameters on the cleanliness level to be achieved. It should be noted that the cleaning module cannot completely remove dust from the surface of the equipment under test; that is, the target cleanliness level for the equipment under test needs to be determined jointly based on the cleanliness level to be achieved and the weight for use.

[0063] Optionally, determine the weight to be used corresponding to the cleanliness level to be used, and determine the target cleanliness level of the device to be tested based on the cleanliness level to be used and the weight to be used, including: determining the weight to be used corresponding to the cleanliness level to be used according to the target mapping curve; multiplying the cleanliness level to be used by the corresponding weight to be used to obtain the target cleanliness level corresponding to the target device to be tested.

[0064] The target mapping curve can be used to characterize the correspondence between equipment cleanliness and the weight to be used. The target mapping curve includes at least one equipment cleanliness level and the corresponding weight to be used for each equipment cleanliness level.

[0065] Specifically, based on the pre-constructed target mapping curve, the cleaning air pressure parameters corresponding to the cleanliness level of each device can be determined. After obtaining the cleanliness level to be used, the weight to be used corresponding to that cleanliness level can be determined. Furthermore, multiplying the cleanliness level to be used by the weight to be used yields the target cleanliness level corresponding to the device to be tested.

[0066] Optionally, after determining the weight corresponding to the cleanliness level to be used, and determining the target cleanliness level of the device to be tested based on the cleanliness level to be used and the weight, the method further includes: generating a corresponding early warning when the target cleanliness level is less than a preset cleanliness threshold; and sending the early warning to the target client so that the target user can perform corresponding cleaning procedures on the device to be tested according to the early warning.

[0067] The preset cleanliness threshold can be understood as a pre-set upper limit for cleanliness. A higher pre-use cleanliness level indicates a cleaner surface and less dust, while a lower pre-use cleanliness level indicates a cleaner surface and more dust. The warning message is a notification indicating that the cleanliness of the device under test is low. The target client can be the monitoring platform corresponding to the device under test or a mobile device carried by the target user. The target user can be the maintenance and cleaning personnel of the device under test.

[0068] Specifically, when the target cleanliness level is lower than the preset cleanliness threshold, it indicates that there is enough dust on the surface of the device under test, requiring further cleaning. At this point, a warning message corresponding to the device under test is generated and sent to the relevant client, reminding the target user to promptly perform the necessary cleaning.

[0069] The advantage of this setup is that, based on this technical solution, the cleanliness of the equipment under test can be accurately detected. When the cleanliness of the equipment is high, there is no need to clean the equipment under test, which can save manpower. When the cleanliness of the equipment is low, it can promptly remind the target user to clean it. This ensures that the cleanliness of the equipment under test is always within a good cleanliness range, thereby maintaining the working efficiency of the equipment under test.

[0070] The technical solution of this embodiment involves determining an adjustment model corresponding to the device under test and obtaining at least one set of parameters to be used associated with the adjustment model. The device under test is simulated using simulation software to obtain an adjustment model corresponding to the device under test. Based on the parameters to be used corresponding to the device under test, at least one set of parameters to be used corresponding to the adjustment model is determined. A linear regression algorithm is used to determine the reference cleanliness corresponding to each set of parameters to be used. The adjustment model is then adjusted based on the at least one set of parameters to be used to obtain a model to be used. Based on each set of parameters to be used and the corresponding reference cleanliness, the parameter information corresponding to the adjustment model can be determined. The adjustment model is then adjusted based on the parameter information to obtain the model to be used. Based on the model to be used, the cleanliness to be used corresponding to the device under test is determined. The current parameters to be used corresponding to the device under test and the cleanliness of the device corresponding to the current parameters to be used are also determined, thus obtaining the cleanliness to be used corresponding to the model to be used. A weight corresponding to the desired cleanliness level is determined, and based on the desired cleanliness level and the weight, a target cleanliness level for the device under test is determined. The weight corresponding to the desired cleanliness level is determined according to the influence of the cleaning air pressure parameter. The target cleanliness level is obtained by multiplying the desired cleanliness level and the weight, thus characterizing the degree of dust accumulation on the surface of the device under test. This method solves the problem of inaccurately determining the cleanliness level of the device under test, leading to excessive cleaning or untimely cleaning. It achieves the effect of accurately determining the cleanliness level of the device under test and determining whether cleaning is necessary based on the cleanliness level.

[0071] Example 2

[0072] In a specific example, taking a cigarette machine laser drilling device as the device to be tested, to determine the cleanliness of the device, an adjustment model corresponding to the device can be pre-established, and at least one set of parameters to be used corresponding to the device can be obtained as the parameters to be used corresponding to the adjustment model. In practical applications, such as... Figure 2 As shown, when constructing the adjustment model corresponding to the device to be tested, data collection and analysis can be performed in advance: collect various basic data, including but not limited to production machine parameters, cigarette product brand parameters and their process production standard parameters; analyze the influencing factors such as laser drilling component configuration, cleaning air pressure, cigarette paper material characteristics, lens material and drilling laser power, to initially obtain the main influencing factors affecting lens cleanliness, and abstract the mathematical model and its boundary conditions; when using the data, carefully analyze and verify the data, carefully verify any problems found, and eliminate possible errors and omissions.

[0073] Specifically, the equipment parameters and process parameters corresponding to the equipment to be tested need to be determined. For example, determining the equipment parameters could involve: determining the number of cigarettes that can be produced per unit time based on the cigarette machine model; the cigarette machine model is a significant factor affecting the cleanliness of the laser perforation equipment for cigarette machines. It is understandable that cigarette machines come in various models, which can be categorized as high-speed, medium-speed, and low-speed machines based on the number of cigarettes they can produce per unit time; different production efficiencies result in different numbers of cigarettes produced per unit time, different numbers of perforations in the laser perforation equipment, and significantly different amounts of dust generated. Simultaneously, it is necessary to determine the process parameters, such as the brand of all cigarette products, and obtain the standard process parameters and their tolerance ranges, including cigarette paper thickness, cigarette ventilation, and number of perforations. Analyzing each influencing factor, the main factors affecting the cleanliness of the lens are preliminarily identified, and a mathematical model (i.e., the model to be adjusted) and its boundary conditions are abstracted. For example, the equipment parameter to be tested is determined to be the cigarette machine model ZJ17, and the determined process parameter is a cigarette production rate of 1000 cigarettes / minute.

[0074] In addition, the process parameters corresponding to the equipment under test also include pulse width. For example, the pulse width distribution can be determined based on the ventilation and number of holes of the cigarette product brand. The laser used for laser drilling is a pulsed laser, which emits discontinuous laser light. It performs instantaneous drilling at high power density through the peak power of the pulsed laser beam. Because the laser beam output by the laser is focused by a lens, the light intensity distribution is Gaussian, and the distribution of laser energy is non-uniform, showing a distribution that is high in the middle and low around the edges. In laser drilling, the longer the drilling pulse time and the larger the standard deviation of the Gaussian distribution of laser energy, the more white edges there are around the laser-drilled holes, resulting in the generation of more dust. The pulse width distribution range of common laser drilling equipment is 30-200μs. At the same time, it also includes the cleaning air pressure parameters corresponding to the equipment under test, such as determining the range of compressed gas pressure for purging laser drilling equipment: In actual production, the equipment is equipped with clean air to disperse these dust particles, and the range of compressed gas used in actual production is 0-1.0MPa.

[0075] In practical applications, the reference cleanliness level of the equipment under test can be determined experimentally. Specifically, a preliminary experiment was conducted to build a cleanliness prediction model for the laser perforation equipment in cigarette machines. The preliminary experiment was carried out to obtain basic experimental data related to the prediction model. Cleanliness measurements of the laser perforation equipment were performed for different paper thicknesses, different perforation numbers, and different pulse widths. The measurement method was as follows: during machine operation, the machine was stopped every 30 minutes, the laser perforation equipment was removed, and the cleanliness of its contact surfaces was measured. After measurement, the laser perforation components were reinstalled in the unit, and cigarette production was resumed. The machine was stopped again after 30 minutes for the next measurement, until the total measurement time reached 180 minutes. The cleanliness measurement experimental values ​​are shown in Table 1.

[0076] Table 1. Experimental values ​​for cleanliness measurement

[0077]

[0078] As shown in the table above, each set of parameters to be used includes paper thickness, number of holes, pulse width, and equipment running time. By processing each set of parameters to be used using a linear regression algorithm, the cleanliness level (i.e., reference cleanliness level) corresponding to each set of parameters to be used can be obtained.

[0079] As a preferred embodiment, the cleanliness measurement area can first be defined: the main dust accumulation areas of the laser drilling equipment are analyzed and identified to delineate the cleanliness measurement area. Images of the main dust accumulation areas (cleanliness measurement areas) of the laser drilling equipment are acquired, see [link to relevant documentation]. Figure 3 Furthermore, by selecting an appropriate threshold, the acquired image is subjected to grayscale conversion or binarization conversion, see [link to relevant documentation]. Figure 4 By statistically analyzing the grayscale values ​​or 0 / 1 values ​​of each pixel, the ratio of clean (non-dusty) surface area to the total surface area is calculated to obtain the cleanliness parameter; statistical analysis shows that... Figure 5 The cleanliness level of the equipment to be tested is 0.48.

[0080] Furthermore, the model to be used corresponding to the equipment to be tested is determined based on the Rayleigh method. The specific construction method can be determined according to the following formula (i.e., the cleanliness fitting equation):

[0081] η1=1-kα x β y γ z t u

[0082] Where η1 represents the reference cleanliness, α represents the paper thickness, γ represents the number of holes, β represents the laser pulse width, t represents the running time, and k, x, y, z, and u represent the fitting parameters to be determined for the model to be adjusted.

[0083] By calculating the parameters to be used in each group using the linear regression algorithm, the fitting parameters to be determined for the model to be adjusted can be obtained, that is, the constants k, x, y, z, u of the model equation are obtained, as shown in Table 2:

[0084] Table 2 Calculated values ​​of constants in the model equations

[0085]

[0086] Understandably, after obtaining the fitting parameters corresponding to the model to be adjusted, the model to be adjusted is tuned based on these parameters to obtain the model to be used. Based on the model to be used, by inputting the current parameters to be used, the cleanliness level to be used corresponding to the current parameters can be obtained.

[0087] It should be noted that when determining the cleanliness of the equipment to be tested, the influence of the cleaning air pressure parameter on the equipment to be tested should also be considered, so as to determine the weight of each cleanliness level to be used based on the degree of influence.

[0088] Specifically, the deposition status of soot particles under different cleaning air pressures was calculated and converted into the surface cleanliness of the laser drilling equipment, resulting in the relationship curve between the cleaning air pressure parameter and the cleanliness (i.e., the target mapping curve). See [link to relevant documentation]. Figure 6 The weights to be used can be determined based on the following formula:

[0089]

[0090] Furthermore, based on the required cleanliness level and the required weight, the target cleanliness level corresponding to the equipment to be tested can be obtained. Specifically, the target cleanliness level can be determined according to the following formula:

[0091] η = η1·η2

[0092] Where η represents the target cleanliness, η1 represents the cleanliness to be used, and η2 represents the weight to be used.

[0093] For example, if k = 7.96 × 10⁶, x = 2.53, y = 0.134, z = 0.139, and u = 1.30, then the target cleanliness level is:

[0094]

[0095] Where η represents the target cleanliness, α represents the paper thickness, β represents the number of holes, γ represents the laser pulse width, t represents the running time, and p represents the cleaning air pressure parameter.

[0096] After obtaining the target cleanliness level, it is determined whether the target cleanliness level is less than the preset cleanliness threshold. If so, an early warning prompt corresponding to the device to be tested is generated and sent to the target client so that the target user can clean the device to be tested in a timely manner according to the early warning prompt.

[0097] The technical solution of this embodiment involves determining an adjustment model corresponding to the device under test and obtaining at least one set of parameters to be used associated with the adjustment model. The device under test is simulated using simulation software to obtain an adjustment model corresponding to the device under test. Based on the parameters to be used corresponding to the device under test, at least one set of parameters to be used corresponding to the adjustment model is determined. A linear regression algorithm is used to determine the reference cleanliness corresponding to each set of parameters to be used. The adjustment model is then adjusted based on the at least one set of parameters to be used to obtain a model to be used. Based on each set of parameters to be used and the corresponding reference cleanliness, the parameter information corresponding to the adjustment model can be determined. The adjustment model is then adjusted based on the parameter information to obtain the model to be used. Based on the model to be used, the cleanliness to be used corresponding to the device under test is determined. The current parameters to be used corresponding to the device under test and the cleanliness of the device corresponding to the current parameters to be used are also determined, thus obtaining the cleanliness to be used corresponding to the model to be used. A weight corresponding to the desired cleanliness level is determined, and based on the desired cleanliness level and the weight, a target cleanliness level for the device under test is determined. The weight corresponding to the desired cleanliness level is determined according to the influence of the cleaning air pressure parameter. The target cleanliness level is obtained by multiplying the desired cleanliness level and the weight, thus characterizing the degree of dust accumulation on the surface of the device under test. This method solves the problem of inaccurately determining the cleanliness level of the device under test, leading to excessive cleaning or untimely cleaning. It achieves the effect of accurately determining the cleanliness level of the device under test and determining whether cleaning is necessary based on the cleanliness level.

[0098] Example 3

[0099] Figure 7 This is a schematic diagram of a device for determining the cleanliness of equipment provided in Embodiment 3 of the present invention. Figure 7 As shown, the device includes: a parameter acquisition module 210, a model determination module 220, a cleanliness determination module 230, and a target cleanliness determination module 240.

[0100] The parameter acquisition module 210 is used to determine the adjustment model corresponding to the device under test and acquire at least one set of parameters to be used associated with the device under test; wherein the at least one set of parameters to be used includes the device running time, number of holes, pulse width and the thickness of the cigarette paper processed based on the device under test.

[0101] The model to be used determination module 220 is used to adjust the parameters of the model to be adjusted based on at least one set of parameters to be used, so as to obtain the model to be used.

[0102] The cleanliness determination module 230 is used to determine the cleanliness level to be tested corresponding to the equipment to be tested based on the model to be used.

[0103] The target cleanliness determination module 240 is used to determine the weight to be used corresponding to the cleanliness to be used, and to determine the target cleanliness of the equipment to be tested based on the cleanliness to be used and the weight to be used.

[0104] The technical solution of this embodiment involves determining an adjustment model corresponding to the device under test and obtaining at least one set of parameters to be used associated with the adjustment model. The device under test is simulated using simulation software to obtain an adjustment model corresponding to the device under test. Based on the parameters to be used corresponding to the device under test, at least one set of parameters to be used corresponding to the adjustment model is determined. A linear regression algorithm is used to determine the reference cleanliness corresponding to each set of parameters to be used. The adjustment model is then adjusted based on the at least one set of parameters to be used to obtain a model to be used. Based on each set of parameters to be used and the corresponding reference cleanliness, the parameter information corresponding to the adjustment model can be determined. The adjustment model is then adjusted based on the parameter information to obtain the model to be used. Based on the model to be used, the cleanliness to be used corresponding to the device under test is determined. The current parameters to be used corresponding to the device under test and the cleanliness of the device corresponding to the current parameters to be used are also determined, thus obtaining the cleanliness to be used corresponding to the model to be used. A weight corresponding to the desired cleanliness level is determined, and based on the desired cleanliness level and the weight, a target cleanliness level for the device under test is determined. The weight corresponding to the desired cleanliness level is determined according to the influence of the cleaning air pressure parameter. The target cleanliness level is obtained by multiplying the desired cleanliness level and the weight, thus characterizing the degree of dust accumulation on the surface of the device under test. This method solves the problem of inaccurately determining the cleanliness level of the device under test, leading to excessive cleaning or untimely cleaning. It achieves the effect of accurately determining the cleanliness level of the device under test and determining whether cleaning is necessary based on the cleanliness level.

[0105] Optionally, the parameter acquisition module includes: a model determination unit, used to simulate the device to be tested based on simulation software to obtain a model to be adjusted corresponding to the device to be tested;

[0106] The parameter determination unit is used to determine at least one set of parameters to be used corresponding to the equipment to be tested, based on the equipment parameters and process parameters of the equipment to be tested; wherein the process parameters are matched with the process parameters of the cigarettes processed by the equipment to be tested.

[0107] Optionally, the model determination module includes: a reference cleanliness determination unit, which is used to process each group of parameters to be used based on a linear regression algorithm to obtain the reference cleanliness corresponding to each group of parameters to be used;

[0108] The model to be used determination unit is used to adjust the parameters of the model to be adjusted based on each set of parameters to be used and the corresponding reference cleanliness, so as to obtain the model to be used.

[0109] Optionally, the model determination unit includes: a cleanliness fitting equation determination subunit, used to determine the cleanliness fitting equation corresponding to the model to be adjusted; wherein the cleanliness fitting equation includes at least one fitting parameter to be determined;

[0110] The sub-unit for determining fitting parameters is used to determine each fitting parameter to be determined in the cleanliness fitting equation based on each group of parameters to be used and the corresponding reference cleanliness.

[0111] The model to be used determines the sub-units, which are used to adjust the parameters of the model to be adjusted based on each fitting parameter to be determined, so as to obtain the model to be used.

[0112] Optionally, the cleanliness determination module includes: a current usage parameter determination unit, used to acquire the current usage parameters corresponding to the device to be tested;

[0113] The cleanliness determination unit is used to calculate the cleanliness based on the current cleanliness parameters of the device to be tested, based on the cleanliness model.

[0114] Optionally, the target cleanliness determination module includes: a weight determination unit, used to determine the weight to be used corresponding to the cleanliness to be used based on the target mapping curve; wherein, the target mapping curve includes at least one equipment cleanliness and the weight to be used corresponding to each equipment cleanliness.

[0115] The target cleanliness determination unit is used to multiply the cleanliness to be used by the corresponding weight to obtain the target cleanliness corresponding to the target detection equipment.

[0116] Optionally, the equipment cleanliness determination device further includes: an early warning generation module, used to generate a corresponding early warning when the target cleanliness is less than a preset cleanliness threshold after determining the weight to be used corresponding to the cleanliness to be used, and determining the target cleanliness of the equipment to be tested based on the cleanliness to be used and the weight to be used.

[0117] The warning notification sending module is used to send warning notifications to the target client so that the target user can perform corresponding cleaning procedures on the equipment to be tested according to the warning notification.

[0118] The equipment cleanliness determination device provided in the embodiments of the present invention can execute the equipment cleanliness determination method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of executing the method.

[0119] Example 4

[0120] Figure 8 A schematic diagram of the structure of an electronic device 10 according to 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 may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0121] like Figure 8 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0122] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0123] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of 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 suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as equipment cleanliness determination methods.

[0124] In some embodiments, the device cleanliness determination method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the device cleanliness determination method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the device cleanliness determination method by any other suitable means (e.g., by means of firmware).

[0125] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0126] Computer programs used to implement the equipment cleanliness determination method of the present invention 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, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs can be executed entirely on the machine, partially on the machine, as a standalone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0127] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0128] To provide interaction with a user, the systems and techniques described herein 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 pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; 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 sound input, voice input, or tactile input).

[0129] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0130] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0131] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0132] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for determining the cleanliness of equipment, characterized in that, include: A model to be adjusted corresponding to the device under test is determined, and at least one set of parameters to be used associated with the device under test is obtained; wherein, the at least one set of parameters to be used includes device running time, number of holes, pulse width, and cigarette paper thickness processed based on the device under test; Based on the at least one set of parameters to be used, the model to be adjusted is adjusted to obtain the model to be used; Based on the model to be used, determine the cleanliness level to be used corresponding to the equipment to be tested; A weight corresponding to the cleanliness level to be used is determined, and a target cleanliness level of the device to be tested is determined based on the cleanliness level to be used and the weight; wherein, the weight is used to characterize the degree of influence of the cleaning air pressure parameter when cleaning the device to be tested on the cleanliness level to be used. The step of determining the adjustment model corresponding to the device under test and obtaining at least one set of parameters to be used associated with the device under test includes: simulating the device under test using simulation software to obtain the adjustment model corresponding to the device under test; determining at least one set of parameters to be used corresponding to the device under test based on the device parameters and process parameters of the device under test; wherein the process parameters match the process parameters of the cigarettes processed by the device under test. The step of adjusting the parameters of the model to be adjusted based on the at least one set of parameters to be used to obtain the model to be used includes: processing each set of parameters to be used based on a linear regression algorithm to obtain a reference cleanliness corresponding to each set of parameters to be used; and adjusting the parameters of the model to be adjusted based on each set of parameters to be used and the corresponding reference cleanliness to obtain the model to be used. The step of determining the weight to be used corresponding to the cleanliness level to be used, and determining the target cleanliness level of the device to be tested based on the cleanliness level to be used and the weight to be used, includes: determining the weight to be used corresponding to the cleanliness level to be used according to the target mapping curve; wherein the target mapping curve includes at least one device cleanliness level and the weight to be used corresponding to each device cleanliness level; multiplying the cleanliness level to be used by the corresponding weight to be used to obtain the target cleanliness level corresponding to the device to be tested.

2. The method according to claim 1, characterized in that, The step of adjusting the parameters of the model to be adjusted based on each set of parameters to be used and the corresponding reference cleanliness to obtain the model to be used includes: Determine the cleanliness fitting equation corresponding to the model to be adjusted; wherein the cleanliness fitting equation includes at least one fitting parameter to be determined; Based on the parameters to be used in each group and the corresponding reference cleanliness, determine each fitting parameter to be determined in the cleanliness fitting equation; Based on the fitting parameters to be determined, the parameters of the model to be adjusted are adjusted to obtain the model to be used.

3. The method according to claim 1, characterized in that, The step of determining the required cleanliness level for the device to be tested based on the model to be used includes: Obtain the current parameters to be used corresponding to the device under test; Based on the model to be used, the cleanliness of the current parameters to be used is calculated to obtain the cleanliness of the device to be tested.

4. The method according to claim 1, characterized in that, After determining the weight to be used corresponding to the cleanliness level to be used, and determining the target cleanliness level of the device to be tested based on the cleanliness level to be used and the weight to be used, the method further includes: When the target cleanliness level is less than a preset cleanliness threshold, a corresponding early warning message is generated; The warning message is sent to the target client so that the target user can perform corresponding cleaning procedures on the device under test according to the warning message.

5. A device for determining the cleanliness of equipment, characterized in that, include: The parameter acquisition module is used to determine the adjustment model corresponding to the device under test and acquire at least one set of parameters to be used associated with the device under test; wherein, the at least one set of parameters to be used includes device running time, number of holes, pulse width and cigarette paper thickness processed based on the device under test; The model to be used determination module is used to adjust the parameters of the device to be tested based on the at least one set of parameters to be used, so as to obtain the model to be used; The cleanliness determination module is used to determine the cleanliness level to be used corresponding to the device to be tested based on the model to be used. The target cleanliness determination module is used to determine the weight to be used corresponding to the cleanliness to be used, and to determine the target cleanliness of the device to be tested based on the cleanliness to be used and the weight to be used; wherein, the weight to be used is used to characterize the degree of influence of the cleaning air pressure parameter when cleaning the device to be tested on the cleanliness to be used; The parameter acquisition module includes: a model determination unit, used to simulate the device to be tested based on simulation software to obtain a model to be adjusted corresponding to the device to be tested; and a parameter determination unit, used to determine at least one set of parameters to be used corresponding to the device to be tested based on the device parameters and process parameters of the device to be tested; wherein the process parameters match the process parameters of the cigarettes processed by the device to be tested. The module for determining the model to be used includes: a reference cleanliness determination unit, used to process each group of parameters to be used based on a linear regression algorithm to obtain a reference cleanliness corresponding to each group of parameters to be used; and a model to be used determination unit, used to adjust the parameters of the model to be adjusted based on each group of parameters to be used and the corresponding reference cleanliness to obtain the model to be used. The target cleanliness determination module includes: a weight determination unit, used to determine the weight to be used corresponding to the cleanliness to be used based on the target mapping curve; wherein the target mapping curve includes at least one equipment cleanliness and the weight to be used corresponding to each equipment cleanliness; the target cleanliness determination unit is used to multiply the cleanliness to be used by the corresponding weight to be used to obtain the target cleanliness corresponding to the equipment to be tested.

6. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that is executed by the at least one processor to enable the at least one processor to perform the equipment cleanliness determination method according to any one of claims 1-4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed by a processor, implement the equipment cleanliness determination method according to any one of claims 1-4.

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