Embedded electronic grain counting machine control method and system

Abstract

The invention discloses an embedded electronic grain counting machine control method and an embedded electronic grain counting machine control system, relates to the technical field of grain counting machine control, and solves the technical problem that errors exist in grain counting work due to the fact that specific reasons caused by an abnormal working state are difficult to identify, adjust and control. The particle number difference value is calculated with the time period as the unit and compared with the preset difference value, the working state of the electronic particle counting machine can be rapidly and accurately judged, meanwhile, the mathematical model between the particle number and the conveying belt speed is established, speed adjustment is more scientific and reasonable, the particle counting efficiency and accuracy can be effectively improved, and the working efficiency of the electronic particle counting machine is improved. For problems caused by abnormity of an internal counting sensor, through detailed analysis of pulse signals, abnormity caused by particle adhesion or large particle identification is distinguished, then the adhesion condition is estimated and the number of adhered particles is determined in combination with the particle processing characteristics of a particle counting machine, and the particle counting accuracy is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of counting machine control, and specifically to an embedded-based electronic counting machine control method and system. Background Art

[0002] Electronic counting machines are widely used in industrial production for counting granular materials. Among them, optoelectronic induction counting machines convert changes in optical signals into electrical signals through optoelectronic sensors to count particles.

[0003] According to the patent application with the publication number CN118570712B, a multi-functional counting machine and a counting method are disclosed. The method includes: adjusting spectral configuration parameters and working parameters; obtaining a third image after adjusting the working parameters, based on the middle region and the termination region of the third image; performing morphological detection, spatio-temporal tracking, debris removal, dynamically counting the number of effective trajectories of tablets on each movement path, and calculating the counting end time and confidence level, and sending the counting end signal to the cylinder that controls the opening and closing of the material gate.

[0004] However, when the existing electronic counting machines are actually working, their working states may be affected by various factors, such as changes in conveyor belt speed, particle adhesion, sensor failures, etc., resulting in problems such as inaccurate counting or abnormal operation of the equipment. Therefore, it is necessary to solve these problems. Summary of the Invention

[0005] In view of the deficiencies of the prior art, the present invention provides an embedded-based electronic counting machine control method and system, which solves the problem of difficultly identifying the specific reasons for abnormal working states and performing adjustment control, resulting in errors in the counting work.

[0006] To achieve the above objectives, the present invention is realized through the following technical solutions: An embedded-based electronic counting machine control method, which specifically includes the following steps:

[0007] Obtain the conveyor belt speed, calculate the difference in the number of particles in adjacent cycles, compare it with the preset difference, and generate an abnormal analysis or normal monitoring signal;

[0008] Analyze the abnormal analysis signal, obtain the real-time image of the conveyor belt and analyze the particle conveying situation, and generate speed abnormal information or other abnormal information;

[0009] Analyze the speed abnormal information, determine the relationship between the number of particles and the conveyor belt speed, and conduct a particle counting experiment, establish a mathematical model between the number of particles and the conveying speed to obtain a relational expression, and analyze and generate speed adjustment information based on the number of particles in the work requirements as a standard;

[0010] Analyze other abnormal information, sort out historical data to determine the normal pulse shape interval, compare it with all pulse signals, screen out abnormal pulse signals, initially judge the abnormal reason according to the pulse width, and then combine the continuity of the pulse area to divide the abnormal pulse signals into normal count and abnormal count signals;

[0011] Analyze the abnormal calculation signals, refer to historical data to determine the normal single pulse area range, set area thresholds for different adhesion quantities in combination with common situations of particle adhesion, compare the pulse area corresponding to the abnormal count signals with the thresholds to determine the particle adhesion quantity, and generate quantity information.

[0012] As a further solution of the present invention, the specific method for generating abnormal analysis or normal monitoring signals is as follows:

[0013] Taking time t as the period, when the conveyor belt speed remains unchanged, obtain the particle quantities in adjacent periods, calculate the difference between the two to obtain the difference in period quantities;

[0014] Compare the difference in period quantities with the preset difference set by the operator. If the difference in period quantities > the preset difference, generate an abnormal analysis signal; if the difference in period quantities ≤ the preset difference, generate a normal monitoring signal.

[0015] As a further solution of the present invention, the specific method for analyzing the abnormal analysis signal is as follows:

[0016] For the abnormal analysis signal, collect the real-time image of the conveyor belt of the electronic counting machine, analyze the particle conveying situation. If there is any situation of particle accumulation, jumping or jamming in the image, it indicates that the conveyor belt speed is abnormal, and generate speed abnormal information; if the particle conveying in the image is normal, generate other abnormal information.

[0017] As a further solution of the present invention, the specific method for analyzing the speed abnormal information is as follows:

[0018] Obtain the conveyor belt speed v and the length L of the particle counting area, then the time for the particle to pass through the counting area is t = L / v. Obtain the accurate counted particles n0 corresponding to the unit time, then the number of particles detected in time t is N = t×n0, and determine the inverse relationship between the number of particles and the conveyor belt;

[0019] Conduct multiple particle counting experiments at different conveyor belt speeds v1, v2, …, v n while ensuring that conditions such as the particle distribution state and the counting area are consistent during the experiment. Obtain the particle numbers N1, N2, …, N n after time t1, draw the N-v curve according to the experimental data, and use the polynomial function N = a0 + a1v + a2v 2 +…+ a n v n, where a0, a1, …, a n are undetermined coefficients for fitting. The coefficients are determined by the least squares method, and the corresponding relational expression is finally obtained;

[0020] Obtain the number of particles required for the work demand. Taking this number as the standard, adjust the current conveyor belt speed according to the obtained relational expression to generate speed adjustment information.

[0021] As a further solution of the present invention, the specific method for analyzing and screening abnormal pulse signals from other abnormal information is as follows:

[0022] Obtain the difference in the number of cycles. At the same time, collect the pulse signals during the particle counting process, sequentially numbered as i and i = 1, 2, ..., j, where j is the total number of pulse signals. The photoelectric sensor converts the optical signal into an electrical signal, and the circuit processes the electrical signal and counts. Each time the light is blocked, a counting pulse is generated, and the counter counts the number of particles accordingly;

[0023] Obtain the pulse shape corresponding to each pulse signal, sort out the historical data, determine the normal pulse shape interval for single particle counting, compare the shape of each pulse signal i with the normal interval, screen out the abnormal pulse signals, and mark them as k and k = 1, 2, ..., p, where p is the total number of abnormal pulse signals.

[0024] As a further solution of the present invention, the specific method for classifying the abnormal pulse signals into normal counting and abnormal counting signals is as follows:

[0025] Obtain the pulse width of the abnormal pulse signal k, and initially judge the cause of the abnormality, which may be particle adhesion or large particle recognition. Analyze the continuity of the pulse area of the abnormal pulse signal k and classify it secondary;

[0026] If the pulse area profile is continuous, it is determined that the cause of the abnormality is large particle recognition, and a normal counting signal is generated. If the pulse area profile is discontinuous, it is determined that the cause of the abnormality is particle adhesion, and an abnormal counting signal is generated.

[0027] As a further solution of the present invention, the specific method for analyzing the abnormal calculation signal to generate quantity information is as follows:

[0028] Obtain all abnormal counting signals, select any group as the analysis object, obtain its pulse area, retrieve the historical data of the current particle recognition, collect the pulse area data of M normal single particles, calculate the mean and standard deviation of these data, and determine the normal single particle pulse area range as -2 , +2 ;

[0029] Based on the characteristics of the granule processing by the granule counter, estimate the granule adhesion situation, determine the area threshold for different adhesion quantities. When two granules adhere to each other, the area threshold is [1.8 ( -2 ), 1.8 ( +2 ); when three granules adhere to each other, the area threshold is [2.2 ( -2 ), 2.2 ( +2 );

[0030] Match the pulse area corresponding to the abnormal count signal with the above area threshold, determine the adhesion quantity corresponding to the abnormal count signal, and generate quantity information.

[0031] An embedded-based electronic granule counter control system includes:

[0032] Basic information acquisition unit, which is used to acquire the granule counter type and conveyor belt speed information of the electronic granule counter and transmit them to the counting recognition and analysis unit;

[0033] Counting recognition and analysis unit, which is used to acquire the granule quantity in adjacent time periods, calculate the difference to obtain the period quantity difference, and at the same time compare it with the preset value to generate an abnormal analysis signal or a normal monitoring signal;

[0034] For the abnormal analysis signal, determine the abnormal cause based on the real-time image of the conveyor belt of the electronic granule counter, and generate speed abnormal information or other abnormal information. At the same time, transmit the speed abnormal information to the transmission speed adjustment and analysis unit, and transmit the other abnormal information to the calculation adjustment and analysis unit;

[0035] Transmission speed adjustment and analysis unit, which is used to analyze the acquired speed abnormal information, establish a mathematical model between the granule quantity and the conveying speed, and obtain the corresponding relational expression. At the same time, determine the adjustment speed according to the granule quantity in the work requirement, generate speed adjustment information, and then transmit it to the control information output unit;

[0036] Calculation adjustment and analysis unit, which is used to analyze the acquired other abnormal information, label the pulse signals in the granule counting process, sort out the historical data to obtain the normal pulse shape interval, and at the same time match it with the pulse signal to obtain the abnormal pulse signal;

[0037] Next, obtain the pulse width to initially determine the cause of the abnormality, then combine with the continuity of the pulse area for judgment, perform secondary classification on the abnormal pulse signal to obtain a normal count signal and an abnormal count signal. For the abnormal count signal, determine the normal single-pulse area range according to historical data analysis, combine with the particle adhesion situation, determine the area threshold for different adhesion quantities, match the pulse area corresponding to the abnormal count signal with the area threshold to determine the adhesion quantity, generate quantity information, and at the same time transmit it to the control information output unit;

[0038] A control information output unit, which is used to display the obtained speed adjustment information and quantity information to the corresponding operator.

[0039] The present invention provides an embedded-based electronic counting machine control method and system. Compared with the prior art, it has the following beneficial effects:

[0040] By obtaining the basic information of the electronic counting machine, calculating the particle quantity difference in units of time periods, and comparing it with the preset difference, the present invention can quickly and accurately judge whether the working state of the electronic counting machine is normal. If an abnormality is found, it can further determine whether it is a speed abnormality or an internal counting sensor abnormality through the analysis of the real-time image of the conveyor belt, improving the accuracy and timeliness of fault diagnosis.

[0041] The present invention establishes a mathematical model between the particle quantity and the conveyor belt speed. First, deduce the inverse relationship between the two theoretically, and then obtain a more practical polynomial function relationship through multiple experiments and curve fitting methods. Adjust the conveyor belt speed based on the particle quantity in the working requirements, making the speed adjustment more scientific and reasonable, and effectively improving the counting efficiency and accuracy.

[0042] For the problems caused by the abnormality of the internal counting sensor, through the detailed analysis of the pulse signal, including steps such as obtaining the pulse shape, matching with the normal pulse shape interval, analyzing the pulse width and the continuity of the pulse area, the present invention can accurately screen out the abnormal pulse signal and distinguish whether it is caused by particle adhesion or large particle recognition, providing strong support for solving the problem of inaccurate counting.

[0043] For the abnormal count signal, by collecting the pulse area data of normal single particles, calculating the mean value and standard deviation to determine the normal range, and then combining with the characteristics of the counting machine for processing particles to estimate the adhesion situation and determine the area threshold, the present invention can accurately match the pulse area corresponding to the abnormal count signal with the threshold, thereby determining the number of adhered particles, improving the accuracy of particle counting, and ensuring the precise control of the particle quantity in the production process. Description of the Drawings

[0044] Figure 1 It is a flowchart of the method steps of the present invention;

[0045] Figure 2 This is the system principle block diagram of the present invention. Specific embodiments

[0046] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0047] Embodiment 1

[0048] Please refer to Figure 1 , this application provides an embedded-based control method for an electronic granule counter, and the method specifically includes the following steps:

[0049] S1. Obtain the basic information of the electronic granule counter, and the basic information includes the type of the electronic granule counter and the conveyor belt speed. The electronic granule counter in this application is a photoelectric induction granule counter, and takes the time t as a cycle to obtain the corresponding granule quantity within adjacent time cycles, and at the same time calculates the difference between the two to obtain the cycle quantity difference. And here the granule quantity is obtained under the condition of the same conveyor belt speed. Then compare the cycle quantity difference with a preset difference, and the specific value of the preset difference is set by the operator;

[0050] If the cycle quantity difference is greater than the preset difference, it indicates that the working state of the electronic granule counter is abnormal, and an abnormal analysis signal is generated. On the contrary, if the cycle granule difference is less than the preset difference, it indicates that the working state of the electronic granule counter is normal, and a normal monitoring signal is generated.

[0051] For example, when using a photoelectric induction type electronic granule counter for counting work, the operator sets the conveyor belt speed to 5 m / min, the time cycle t to 1 minute, and the preset difference to 10 granules. In two consecutive time cycles, the granule quantity obtained in the first cycle is 500 granules, and the granule quantity obtained in the second cycle is 520 granules. The calculated cycle quantity difference is 20 granules, which is greater than the preset difference of 10 granules. At this time, the system generates an abnormal analysis signal. After the operator checks the equipment, it is found that there is dust on the surface of the sensor, which affects the detection accuracy. After cleaning, the equipment resumes normal operation.

[0052] Next, process the obtained abnormal analysis signal, acquire the real-time image of the conveyor belt of the electronic grain counting machine, and analyze the conveying situation of the particles in the real-time image. If there is particle accumulation in the conveying situation, it indicates that the speed of the current conveyor belt is abnormal, and the conveying speed needs to be adjusted to generate speed abnormal information. On the contrary, if the conveying situation is normal, and here normal means there are no phenomena such as particle accumulation, jumping, or jamming, it indicates that there is an abnormality in the internal counting sensor, and other abnormal information is generated.

[0053] S2. Analyze the obtained speed abnormal information, establish a mathematical model between the number of particles and the conveying speed, and the specific establishment method is as follows:

[0054] Obtain the conveyor belt speed v and the length L of the particle counting area. Then the time for the particles to pass through the counting area is t = L / v. Obtain the accurate counted particles n0 per unit time. Then the number of particles detected within time t is N = t×n0. From this, it can be obtained that there is an inverse relationship between the number of particles N and the conveyor belt speed v.

[0055] Conduct multiple particle counting experiments at different conveyor belt speeds. During the experiment, ensure that conditions such as the distribution state of the particles and the counting area remain consistent to exclude the interference of other factors. Denote different conveyor belt speeds as v1, v2, …, v n , and at the same time obtain the number of particles N1, N2, …, N obtained by the particle counter after time t1 n , then draw the N-v curve based on the obtained experimental data, observe the shape and trend of the curve, and at the same time use the method of curve fitting to establish a polynomial function N = a0 + a1v + a2v 2 +…+ a n v n , where (a0, a1, …, a n are undetermined coefficients) for fitting, and determine the coefficients by the least squares method to finally obtain the corresponding relationship.

[0056] Next, obtain the number of particles in the work requirement and adjust the current conveyor belt speed based on it to generate speed adjustment information.

[0057] S3. Analyze the other obtained abnormal information to obtain the difference in the number of cycles. At the same time, obtain the pulse signals during the counting process of grains, label them as i, and i = 1, 2, …, j, where j represents the number of pulse signals. The photoelectric sensor converts the change in the optical signal into an electrical signal, processes and counts the electrical signal through a circuit. Each time the light is blocked, a counting pulse is generated, and the counter records the number of pulses, thereby realizing the counting of particles. Then, obtain the pulse shape corresponding to the pulse signal i, and sort out the historical data to obtain the normal pulse shape interval. Here, the normal pulse shape interval represents the pulse shape obtained by counting a single particle. At the same time, match it with the pulse shape corresponding to the pulse signal i, and screen out the abnormal pulse signals denoted as k, and k = 1, 2, …, p, where p represents the number of abnormal pulse signals;

[0058] First, calculate the difference in the number of particles in adjacent time periods, that is, the difference in the number of cycles. This step can help us initially judge whether there are abnormal fluctuations in the counting process of grains. At the same time, during the counting process of grains, the photoelectric sensor plays a key role. It accurately converts the change in the optical signal into an electrical signal. Each time a particle blocks the light, a counting pulse is generated. These pulse signals are sequentially labeled as i (i = 1, 2, …, j, where j represents the total number of pulse signals), and the counter records the number of pulses to achieve the counting of particles;

[0059] Next, obtain the pulse shape corresponding to each pulse signal i. To judge whether the pulse shape is normal, it is necessary to sort out the historical data to obtain the normal pulse shape interval. Here, the normal pulse shape interval refers to the range of pulse shapes obtained when counting a single particle. Then, match the pulse shape corresponding to each pulse signal i with the normal pulse shape interval. Through this matching and screening, it is possible to find out the pulse signals that do not conform to the normal range and mark them as abnormal pulse signals k (k = 1, 2, …, p, where p represents the number of abnormal pulse signals);

[0060] Next, obtain the pulse width of the abnormal pulse signal k, and preliminarily determine the abnormal cause corresponding to the abnormal pulse signal k according to the pulse width. Here, the abnormal causes include particle adhesion and large particle recognition. At the same time, judge the continuity of the pulse area corresponding to the abnormal pulse signal k, and perform secondary classification on the abnormal pulse signal k to obtain a normal count signal and an abnormal count signal. If the contour of the pulse area is continuous, the abnormal cause corresponds to large particle recognition, and a normal count signal is generated. If the contour of the pulse area is discontinuous, the abnormal cause corresponds to particle adhesion, and an abnormal count signal is generated. Specifically, when analyzing the particle area, under normal circumstances, for the recognition of large particles, the contour of the corresponding pulse area is a continuous whole, while for the case of particle adhesion, the corresponding pulse area is formed by splicing, so there will be discontinuous parts;

[0061] S4. Analyze the obtained abnormal count signals, obtain all the abnormal count signals, and at the same time take one group as the analysis object for analysis, obtain the pulse area of the analysis object, then obtain the historical data of the current particle recognition, collect the pulse area data of M normal single particles, and calculate the mean value of the M data and standard deviation , and then determine the normal single particle pulse area range according to the obtained mean value and standard deviation, denoted as -2 , +2 ;

[0062] Next, combine the characteristics of the particle counting machine for processing particles, estimate the possible situations of particle adhesion, and determine different area thresholds according to the estimated adhesion situations. For example, when two particles are adhered to each other, the area threshold obtained through analysis is [1.8 ( -2 ), 1.8 ( +2 )], when three particles are connected, the area threshold obtained through analysis is [2.2 ( -2 ), 2.2 ( +2 )]. At the same time, match the pulse area corresponding to the abnormal count signal with the area threshold, and determine the adhesion quantity corresponding to the abnormal count signal to generate quantity information;

[0063] And so on, analyze all the abnormal count signals to generate corresponding quantity information.

[0064] Embodiment 2

[0065] Please refer to Figure 2, this application provides an embedded electronic tablet counting machine control system, including: a basic information acquisition unit, a counting recognition and analysis unit, a transmission speed adjustment and analysis unit, a counting adjustment and analysis unit, and a control information output unit, and combined with Figure 2 It can be known that there is a one-way electrical connection between the above functional units.

[0066] The basic information acquisition unit is used to acquire the type of the tablet counting machine and the conveyor belt speed information of the electronic tablet counting machine, and transmit it to the counting recognition and analysis unit;

[0067] The counting recognition and analysis unit is used to acquire the number of particles in adjacent time periods, calculate the difference to obtain the difference in the number of periods, and at the same time compare it with a preset value to generate an abnormal analysis signal or a normal monitoring signal;

[0068] For the abnormal analysis signal, determine the abnormal reason based on the real-time image of the conveyor belt of the electronic tablet counting machine, and generate speed abnormal information or other abnormal information. At the same time, transmit the speed abnormal information to the transmission speed adjustment and analysis unit, and transmit the other abnormal information to the calculation adjustment and analysis unit. The specific analysis method is the same as the processing method of S1 in Embodiment 1;

[0069] The transmission speed adjustment and analysis unit is used to analyze the acquired speed abnormal information, establish a mathematical model between the number of particles and the conveying speed, and obtain the corresponding relational expression. At the same time, determine the adjustment speed according to the number of particles in the work requirement, generate speed adjustment information, and the specific processing method is the same as the processing process of S2 in Embodiment 1. Then transmit it to the control information output unit;

[0070] The calculation adjustment and analysis unit is used to analyze the acquired other abnormal information, label the pulse signals in the tablet counting process, and sort out the historical data to obtain the normal pulse shape interval. At the same time, match it with the pulse signal to obtain the abnormal pulse signal;

[0071] Then obtain the pulse width to initially determine the abnormal reason, and then judge in combination with the continuity of the pulse area. Classify the abnormal pulse signal twice to obtain a normal counting signal and an abnormal counting signal. The specific processing method is the same as the processing process of S3 in Embodiment 1. For the abnormal calculation signal, determine the normal single pulse area range according to the historical data analysis, and combine the particle adhesion situation to determine the area threshold for different adhesion numbers. Match the pulse area corresponding to the abnormal counting signal with the area threshold to determine the adhesion number, generate quantity information, and the specific processing method is the same as the processing process of S4 in Embodiment 1. At the same time, transmit it to the control information output unit;

[0072] The control information output unit is used to display the acquired speed adjustment information and quantity information to the corresponding operator.

[0073] For some data in the above formula, only their numerical values are taken for calculation, and the parameter units are not substituted for calculation. At the same time, the content not described in detail in this specification belongs to the prior art well-known to those skilled in the art.

[0074] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical method of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical method of the present invention.

Claims

1. An embedded-based control method for an electronic counting machine, characterized in that The method specifically includes the following steps: Obtain the conveyor belt speed, calculate the difference in the number of particles in adjacent cycles, compare it with a preset difference, and generate an abnormal analysis or normal monitoring signal; Analyze the abnormal analysis signal, obtain the real-time image of the conveyor belt and analyze the particle conveying situation, and generate speed abnormal information or other abnormal information; Analyze the speed abnormal information, determine the relationship between the number of particles and the conveyor belt speed, conduct a particle counting experiment, establish a mathematical model between the number of particles and the conveying speed to obtain a relational expression, and analyze and generate speed adjustment information based on the number of particles in the work requirement as a standard; Analyze other abnormal information, sort out historical data to determine the normal pulse shape interval, compare it with all pulse signals, screen out abnormal pulse signals, initially judge the abnormal reason according to the pulse width, and then combine the continuity of the pulse area to divide the abnormal pulse signals into normal counting and abnormal counting signals; Analyze the abnormal calculation signal, determine the normal single pulse area range with reference to historical data, set area thresholds for different adhesion numbers in combination with common situations of particle adhesion, compare the pulse area corresponding to the abnormal counting signal with the threshold value to determine the number of particle adhesions, and generate quantity information.

2. The control method of an embedded electronic tablet counting machine according to claim 1, wherein The specific method for generating the abnormal analysis or normal monitoring signal is as follows: Taking time t as a cycle, when the conveyor belt speed remains unchanged, obtain the number of particles in adjacent cycles, calculate the difference between the two to obtain the cycle number difference; Compare the cycle number difference with the preset difference set by the operator. If the cycle number difference > the preset difference, generate an abnormal analysis signal. If the cycle number difference ≤ the preset difference, generate a normal monitoring signal.

3. The control method of an embedded electronic pill counter according to claim 1, characterized in that The specific method for analyzing the abnormal analysis signal is as follows: For the abnormal analysis signal, collect the real-time image of the conveyor belt of the electronic tablet counting machine, analyze the particle conveying situation. If there is any situation of particle accumulation, jumping or jamming in the image, it indicates that the conveyor belt speed is abnormal and generate speed abnormal information. If the particle conveying in the image is normal, generate other abnormal information.

4. A control method for an embedded electronic tablet counting machine according to claim 1, characterized in that The specific method for analyzing the speed abnormal information is as follows: Obtain the conveyor belt speed v and the length L of the particle counting area. Then the time for the particle to pass through the counting area is t = L / v. Obtain the accurate counting particles n0 corresponding to the unit time. Then the number of particles detected in time t is N = t×n0, and determine the inverse relationship between the number of particles and the conveyor belt; Carry out multiple particle counting experiments at different conveyor belt speeds v1, v2, …, v n while ensuring that conditions such as the particle distribution state and the counting area are consistent during the experiment, and obtain the number of particles N1, N2, …, N n after time t1. Plot the N-v curve based on the experimental data, and use the polynomial function N = a0 + a1v + a2v 2 + … + a n v n , where a0, a1, …, a n are undetermined coefficients for fitting, determine the coefficients by the least squares method, and finally obtain the corresponding relationship; Obtain the number of particles required for the work requirement, and adjust the current conveyor belt speed according to the obtained relational expression with this number as the standard, and generate speed adjustment information.

5. A control method for an embedded electronic tablet counting machine according to claim 1, characterized in that, The specific method for analyzing other abnormal information and screening out abnormal pulse signals is as follows: Obtain the cycle number difference. At the same time, collect the pulse signals during the tablet counting process, sequentially numbered as i and i = 1, 2,..., j, where j is the total number of pulse signals. The photoelectric sensor converts the optical signal into an electrical signal, and the circuit processes the electrical signal and counts. Each time the light is blocked, a counting pulse is generated, and the counter counts the number of particles accordingly; Obtain the pulse shape corresponding to each pulse signal, sort out the historical data, determine the normal pulse shape interval for single particle counting, compare the shape of each pulse signal i with the normal interval, and screen out the abnormal pulse signals, marked as k and k = 1, 2,..., p, where p is the total number of abnormal pulse signals.

6. The control method of an embedded electronic tablet counting machine according to claim 1, wherein The specific method for classifying the abnormal pulse signals into normal count and abnormal count signals is as follows: Obtain the pulse width of the abnormal pulse signal k, and preliminarily judge the cause of the abnormality based on this. It may be particle adhesion or large particle recognition. Analyze the continuity of the pulse area of the abnormal pulse signal k and conduct secondary classification on it; If the pulse area profile is continuous, determine that the cause of the abnormality is large particle recognition and generate a normal count signal. If the pulse area profile is discontinuous, determine that the cause of the abnormality is particle adhesion and generate an abnormal count signal.

7. A control method for an embedded electronic tablet counting machine according to claim 1, characterized in that, The specific method for analyzing the abnormal calculation signal to generate quantity information is as follows: Obtain all abnormal count signals, select any group as the analysis object, obtain its pulse area, retrieve the historical data of current particle recognition, collect the pulse area data of M normal single particles, calculate the mean and standard deviation of these data, and determine that the pulse area range of normal single particles is -2 , +2 ; According to the characteristics of the granule processing by the granule counter, estimate the granule adhesion situation, determine the area threshold for different adhesion quantities. When two granules adhere to each other, the area threshold is [1.8 ( -2 ), 1.8 ( +2 )]. When three granules adhere to each other, the area threshold is [2.2 ( -2 ), 2.2 ( +2 )]; Match the pulse area corresponding to the abnormal count signal with the above area threshold to determine the adhesion quantity corresponding to this abnormal count signal and generate quantity information.

8. An embedded-based electronic tablet counting machine control system for implementing the embedded-based electronic tablet counting machine control method according to any one of claims 1-7, characterized in that, Including: A basic information acquisition unit, which is used to acquire the type of the counting machine and the conveyor belt speed information of the electronic counting machine and transmit them to the counting recognition and analysis unit; A counting recognition and analysis unit, which is used to acquire the number of particles in adjacent time periods, calculate the difference to obtain the difference in the number of periods, and at the same time compare it with a preset value to generate an abnormal analysis signal or a normal monitoring signal; For the abnormal analysis signal, determine the cause of the abnormality based on the real-time image of the conveyor belt of the electronic counting machine, and generate speed abnormality information or other abnormal information. At the same time, transmit the speed abnormality information to the transmission speed adjustment and analysis unit and transmit the other abnormal information to the calculation adjustment and analysis unit; A transmission speed adjustment and analysis unit, which is used to analyze the obtained speed abnormality information, establish a mathematical model between the number of particles and the conveying speed, and obtain the corresponding relationship. At the same time, determine the adjustment speed according to the number of particles in the work requirement, generate speed adjustment information, and then transmit it to the control information output unit; A calculation adjustment and analysis unit, which is used to analyze the obtained other abnormal information, label the pulse signals in the counting process, sort out the historical data to obtain the normal pulse shape interval, and at the same time match it with the pulse signal to obtain the abnormal pulse signal; Then obtain the pulse width to preliminarily determine the cause of the abnormality, and then judge in combination with the continuity of the pulse area. Conduct secondary classification on the abnormal pulse signal to obtain a normal count signal and an abnormal count signal. For the abnormal calculation signal, determine the normal single pulse area range according to historical data analysis, combine the particle adhesion situation, determine the area threshold for different adhesion quantities, and match the pulse area corresponding to the abnormal count signal with the area threshold to determine the adhesion quantity and generate quantity information. At the same time, transmit it to the control information output unit; A control information output unit, which is used to display the obtained speed adjustment information and quantity information to the corresponding operator.

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