Material conveying control system in automatic production line

Abstract

The invention discloses a material conveying control system in an automatic production line, which belongs to the technical field of material conveying and comprises a material resource acquisition module used for acquiring resource parameter information related to materials to be conveyed; the production line monitoring module is used for acquiring relevant parameter information related to conveying of the materials in the production line conveying process; the material conveying path selection module is used for analyzing according to the acquired resource parameter information and the associated parameter information so as to select an optimal material conveying path; the analysis control module is used for analyzing according to the monitored related parameter information and judging whether the materials are abnormal or not in the conveying process; and the execution module is used for giving a corresponding alarm response when judging that the material conveying is abnormal. According to the invention, comprehensive analysis can be carried out according to the related parameter information generated during material conveying to judge potential abnormity and known abnormity of the material in the conveying process, so that response adjustment can be carried out in time to ensure normal operation of a production line.

Description

Technical Field

[0001] The present invention belongs to the technical field of material conveying, and particularly relates to a material conveying control system in an automated production line. Background Art

[0002] With the continuous development of the manufacturing industry and the continuous progress of technology, automated production lines have become the core mode of modern industrial production. In many industries such as automobile manufacturing, electronic device production, food processing, and pharmaceutical manufacturing, automated production lines, with their efficient, accurate, and stable production capabilities, have greatly improved production efficiency, reduced labor costs, and improved product quality.

[0003] When transporting materials currently, mechanical conveying equipment such as belt conveyors and chain conveyors is mostly used. They usually convey materials at a fixed speed and along a fixed route, and cannot be flexibly adjusted according to the actual needs of the materials on the production line. Due to different conveying situations on different production lines, conveying along a fixed selected route is likely to cause material accumulation and affect the conveying efficiency. In addition, ordinary mechanical conveying equipment lacks real-time monitoring of the material state during the conveying process and can only be monitored manually. When problems such as material blockage and deviation occur, manual workers cannot detect them in time, which will affect the normal operation of the production line. Summary of the Invention

[0004] The purpose of the present invention is to provide a material conveying control system in an automated production line to solve the problems faced in the above background art.

[0005] The purpose of the present invention can be achieved by the following technical solutions:

[0006] A material conveying control system in an automated production line, the control system comprising:

[0007] A material resource acquisition module, which is used to acquire resource parameter information related to the material to be conveyed;

[0008] A production line monitoring module, which is used to acquire correlation parameter information related to the conveying during the conveying of materials on the production line;

[0009] A material conveying path selection module, which is used to analyze based on the acquired resource parameter information and correlation parameter information, so as to select the optimal conveying path for the material;

[0010] An analysis and control module, which is used to analyze based on the monitored correlation parameter information to judge whether an abnormality occurs during the conveying of the material;

[0011] An execution module, which performs corresponding alarm responses when it judges that the material conveying is abnormal.

[0012] Further, the resource parameter information includes the physical characteristic information of the material, the production requirement information of the material, and the environmental requirement information of the material, and the associated parameter information includes the acquired production line image information, the power consumption information of the production line conveying equipment, the temperature information of the production line conveying equipment, the fault information of the production line conveying equipment, and the production line conveying completion amount information.

[0013] Further, the working method of the material conveying path selection module is as follows:

[0014] According to the acquired resource parameter information of the material to be conveyed, through the formula obtain the status value Z of the material to be conveyed M , where m is the total number of resource items of the material to be conveyed obtained, M i is the parameter value obtained under the i-th resource item, ∈ i is the weight coefficient of the i-th resource item, and i ∈ [1, m];

[0015] At the same time, based on the neural network model training technology, when the material is transmitted, each production line is set with a corresponding status value matching interval [Z M x, Z M y];

[0016] Match the status value Z of the material to be conveyed M with the status value matching intervals [Z M x, Z M y] corresponding to each production line;

[0017] Screen out the production lines that meet the conveying requirements of the material to be conveyed, and record them as the set of candidate production lines. The screening requirements are: Z M ∈ [Z M x, Z M y];

[0018] At the same time, obtain the amount of material to be conveyed PL m , the estimated waiting time PL t and the operating condition value P of each production line in the set of candidate production lines, and through the formula

[0019] obtain the matching coefficient k of each production line;

[0020] According to the magnitude of the matching coefficient k, sort each production line in ascending order, and select the production line with the highest ranking as the best conveying path for the material;

[0021] where PL t0 is the preset waiting time reference value, L s0is the reference value of the conveying length of the preset production line, T s0 is the reference value of the conveying duration of the preset production line, L s is the conveying length of the production line, T s is the conveying duration of the production line, and α1 and α2 are proportionality coefficients.

[0022] Furthermore, the method for obtaining the operating condition value P is as follows:

[0023] Obtain the power consumption value P during the conveying of the production line within the Δt period P and the equipment temperature value P T , and formulate the curve function P of the power consumption value changing with time P (t), and the curve function P of the temperature value changing with time T (t);

[0024] Through the formula obtain the operating condition value P of the production line;

[0025] wherein, P n is the number of faults occurred in the production line within the Δt period, P qr is the task completion volume of the production line within the Δt period, P qr0 is the expected task completion volume within the Δt period, t a is the start time point of the Δt period, t b is the end time point of the Δt period, P P0 (t) is the standard curve function of the power consumption value changing with time formulated according to historical data, P T0 (t) is the standard curve function of the temperature value changing with time formulated according to historical data.

[0026] Furthermore, the working method of the analysis and control module is as follows:

[0027] Real-time capture the image information of the production line during the conveying of materials through a camera, process the image information, and use the edge detection algorithm to identify the contour of the material, and judge whether the contour of the material is within the set material conveying position interval:

[0028] When all the material contours fall within the set material conveying position interval, it is judged that the material conveying is normal;

[0029] Otherwise, it is judged that the material conveying is abnormal.

[0030] Furthermore, the working method of the analysis and control module also includes:

[0031] When it is judged that the material conveying is not abnormal, collect the distance value H between the contour center of the material within n consecutive frames and the center of the set material conveying position, and formulate the curve function H(x) of the distance value changing with the number of frames;

[0032] Obtain the offset value D through the formula ;

[0033] When D > D s , it is determined that there is a potential abnormality in the material transportation;

[0034] Among them, x1 is the first frame of image obtained, x n is the last frame of image obtained, H(x1) is the distance value of the first frame of image, H(x n ) is the distance value of the last frame of image, and D s is the preset offset judgment threshold.

[0035] Furthermore, the working method of the execution module is as follows:

[0036] When it is determined that there is a potential abnormality in the material transportation, a first-level alarm is generated, and at this time, the material transportation speed is adjusted;

[0037] When it is determined that the material transportation is abnormal and H x < H < H y , a second-level alarm is generated, and at this time, the material transportation speed is adjusted and the position of the material is adjusted simultaneously;

[0038] When it is determined that the material transportation is abnormal and H > H y , a third-level alarm is generated and the machine is immediately stopped;

[0039] Among them, H x and H y are two set distance offset judgment thresholds.

[0040] Advantages of the present invention:

[0041] The present invention first obtains the state value of the material to be transported according to the resource parameter information of the material to be transported, and finds out the production line that meets the material transportation according to the state value, so that the appropriate production line can be selected for transportation according to the actual needs of different materials, without the need for manual selection of the production line, which can ensure the transportation efficiency to a certain extent; at the same time, a comprehensive analysis is carried out according to the quantity of materials to be transported, the estimated waiting time and the operating condition value of each production line in the set of production lines to be selected, and the matching coefficient of each production line is obtained, so as to select the best production line for transportation, which can greatly improve the material transportation efficiency.

[0042] The present invention can carry out a comprehensive analysis according to the associated parameter information generated during the transportation of the material to judge the potential abnormalities and known abnormalities that occur during the transportation of the material, so as to make a timely response adjustment to ensure the normal operation of the production line.

[0043] Of course, it is not necessary for any product implementing the present invention to achieve all the above advantages simultaneously. Brief Description of the Drawings

[0044] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0045] Figure 1 It is a block diagram of the system modules of the present invention. Detailed 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 some, rather than all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the protection scope of the present invention.

[0047] In one embodiment, a material conveying control system in an automated production line is disclosed. As Figure 1 shown, the control system includes:[[]]

[0048] A material resource acquisition module, which is used to acquire resource parameter information related to the material to be conveyed. The resource parameter information includes the physical characteristic information of the material, the production requirement information of the material, and the environmental requirement information of the material.

[0049] A production line monitoring module, which is used to acquire associated parameter information related to the conveyance during the conveyance of the material on the production line. The associated parameter information includes the acquired production line image information, the power consumption information of the production line conveyance equipment, the temperature information of the production line conveyance equipment, the fault information of the production line conveyance equipment, and the production line conveyance completion information.

[0050] A material conveying path selection module, which is used to analyze based on the acquired resource parameter information and associated parameter information, so as to select the optimal material conveying path.

[0051] An analysis and control module, which is used to analyze based on the monitored associated parameter information to determine whether an abnormality occurs during the conveyance of the material.

[0052] An execution module, which performs corresponding alarm responses when it is determined that the material conveyance is abnormal.

[0053] Through the above technical solution, the present application first obtains the status value of the material to be transported according to the resource parameter information of the material to be transported. The resource parameter information includes the physical characteristic information of the material, such as the size, weight, shape, fragility, etc. of the material, while the production demand information of the material includes the material demand priority, the urgency of production, etc., and the environmental demand information of the material includes the temperature, humidity, and cleanliness requirements during the transportation of the material, etc. And according to the status value, the production line that meets the material transportation is found. In this way, the appropriate production line can be selected for transportation according to the actual needs of different materials, without the need for manual selection of the production line, which can ensure the transportation efficiency to a certain extent; at the same time, based on the comprehensive analysis of the amount of materials to be transported, the estimated waiting time, and the operating condition values of each production line in the set of candidate production lines, the matching coefficient of each production line is obtained, so as to select the best production line for transportation, which can greatly improve the material transportation efficiency; at the same time, according to the associated parameter information generated during the transportation of the material, such as the production line image information, the power consumption information of the production line transportation equipment, the temperature information of the production line transportation equipment, the fault information of the production line transportation equipment, and the production line completion amount information, etc., comprehensive analysis is carried out to judge the potential and known abnormalities that occur during the transportation of the material, so as to make a timely response adjustment to ensure the normal operation of the production line.

[0054] The working method of the material transportation path selection module is: according to the obtained resource parameter information of the material to be transported, through the formula obtain the status value Z of the material to be transported M , where m is the total number of resource items for obtaining the material to be transported, M i is the parameter value obtained under the i-th resource item, ∈ i is the weight coefficient of the i-th resource item, and i ∈ [1, m];

[0055] At the same time, based on the neural network model training technology, when the material is transported, each production line is set with a corresponding status value matching interval [Z M x, Z M y];

[0056] Match the status value Z of the material to be transported M with the corresponding status value matching interval [Z M x, Z M y] of each production line;

[0057] Select the production lines that meet the transportation of the material to be transported, denoted as the set of candidate production lines. The screening requirements are: Z M ∈ [Z M x, Z M y];

[0058] At the same time, obtain the amount of materials to be transported PL of each production line in the set of candidate production linesm and the estimated waiting time PL t and the operating condition value P. The matching coefficient k of each production line is obtained through the formula

[0059] ;

[0060] According to the magnitude of the matching coefficient k, each production line is sorted in ascending order, and the production line with the highest ranking is selected as the best material conveying path;

[0061] wherein, PL t0 is the preset waiting time reference value, L s0 is the preset production line conveying length reference value, T s0 is the preset production line conveying duration reference value, L s is the conveying length of the production line, T s is the conveying duration of the production line, and α1 and α2 are proportionality coefficients;

[0062] Through the above technical solution, this embodiment provides a method for the material conveying path selection module to select the best production line for conveying. First, the state value Z of the material to be conveyed is obtained through the formula ; wherein, m is the total number of resource items for obtaining the material to be conveyed, including items such as the volume, length, and priority level of the material, M M is the actual parameter value obtained under each resource item, ∈ i is the weight coefficient set for each resource item. At the same time, based on the neural network model training technology, when the material is being transported, each production line is set with a corresponding state value matching interval [Z i x, Z M y]; the state value Z of the material to be conveyed M is matched with the state value matching interval [Z M x, Z M y] corresponding to each production line. If Z M ∈ [Z M x, Z M y], then the production lines that meet the requirements for conveying the material to be conveyed are screened out and recorded as the set of candidate production lines; in this way, the production lines that match the material can be quickly found from many production lines, so that the appropriate production line can be selected for conveying according to the actual needs of different materials, ensuring the conveying efficiency. Then, the amount of material to be conveyed PL M of each production line in the set of candidate production lines is obtained, m the estimated waiting time PL t and the operating condition value P. Through the formula

[0063] Obtain the matching coefficient k for each production line; according to the magnitude of the matching coefficient k, sort each production line in ascending order, and select the production line with the earliest ranking as the best material conveying path. In the formula, PL t0 is the preset reference value of the waiting duration, L s0 is the preset reference value of the conveying length of the production line, T s0 is the preset reference value of the conveying duration of the production line. α1 and α2 are proportionality coefficients, which can be determined according to historical data combined with empirical data. It can be seen from the formula that when the operating condition value of the production line is better (when the operating condition value P is smaller), the amount of material to be conveyed PL m is less, the expected waiting duration PL t is shorter, the conveying length of the production line is shorter, and the conveying duration of the production line is shorter, indicating that the production line is more suitable for material conveying. Therefore, when the value of the matching coefficient k is smaller, it indicates that the production line has the best selectivity for material conveying. So, according to the magnitude of the matching coefficient k, sort each production line in ascending order, and select the production line with the earliest ranking as the best material conveying path to ensure the conveying efficiency of the material.

[0064] The method for obtaining the operating condition value P is as follows: Obtain the power consumption value P P and the equipment temperature value P T during the conveying of the production line within the Δt cycle, and formulate the curve function P P (t) of the power consumption value changing with time and the curve function P T (t) of the temperature value changing with time;

[0065] Through the formula obtain the operating condition value P of the production line;

[0066] Among them, P n is the number of faults occurring in the production line within the Δt cycle, P qr is the task completion amount of the production line within the Δt cycle, P qr0 is the expected task completion amount within the Δt cycle, t a is the start time point of the Δt cycle, t b is the end time point of the Δt cycle, P P0 (t) is the standard curve function of the power consumption value changing with time formulated according to historical data, P T0 (t) is the standard curve function of the temperature value changing with time formulated according to historical data.

[0067] The above technical solution provides a method for obtaining the operating status value. Generally speaking, when the power consumption of the production line is greater, the temperature of the production line equipment is higher, or the task completion situation is worse, it indicates that the operating status of the production line is poor and it is less suitable for material transportation. Therefore, a Δt period is determined according to experience, and the power consumption value P during the transportation of the production line within the Δt period is obtained. P and the equipment temperature value P T , and a curve function P of the power consumption value changing with time is determined. P (t), the curve function P of the temperature value changing with time T (t). Through the formula

[0068] the operating status value P of the production line is obtained. In the formula, P n is the number of faults occurring in the production line within the Δt period, P qr is the task completion volume of the production line within the Δt period, which can be obtained according to the real-time detection data of the production line, and P qr0 is the expected task completion volume within the Δt period, P P0 (t) is the standard curve function of the power consumption value changing with time determined according to historical data, P T0 (t) is the standard curve function of the temperature value changing with time determined according to historical data, both of which can be determined according to the historical transportation data of the production line; it can be seen from the formula that when the operating status value P of the production line is larger, it indicates that the operating status of the production line is worse, and the possibility of its priority option for material transportation is smaller. Therefore, by combining the power consumption situation, temperature change situation, task completion situation and fault situation of the production line equipment, the operating situation of the production line can be judged more accurately, so as to provide a judgment basis for selecting the optimal production line.

[0069] The working method of the analysis and control module is as follows: The image information of the production line during material transportation is captured in real time through a camera, and the image information is processed. The edge detection algorithm is used to identify the contour of the material, and it is judged whether the contour of the material is within the set material transportation position interval:

[0070] When all the material contours fall within the set material transportation position interval, it is judged that the material transportation is normal;

[0071] Otherwise, it is judged that the material transportation is abnormal.

[0072] When it is judged that the material transportation has not occurred abnormally, the distance value H between the contour center of the material within n consecutive frames and the set material transportation position center is collected, and a curve function H(x) of the distance value changing with the number of frames is determined;

[0073] Through the formula the offset value D is obtained;

[0074] When D > Ds If so, it is determined that there is a potential abnormality in the material transportation;

[0075] Among them, x1 is the first frame of image obtained, x n is the last frame of image obtained, H(x1) is the distance value of the first frame of image, H(x n ) is the distance value of the last frame of image, D s is the preset offset judgment threshold.

[0076] The above technical solution provides a specific method for the analysis and control module to judge whether an abnormality occurs during the transportation of materials. First, according to the transportation size of the production line and the transported materials, a material transportation position interval is set for the entire production line. Within this interval, the materials are transported normally; then, the image information of the production line during material transportation is captured in real time by a camera, and the image information is processed. The edge detection algorithm is used to identify the contour of the material, and it is judged whether the contour of the material is within the set material transportation position interval: when all the material contours fall within the set material transportation position interval, it indicates that the position of the material does not change abnormally during transportation, and it is judged that the material transportation is normal; otherwise, it is judged that the material transportation is abnormal, and an alarm response is made in a timely manner. When it is judged that the material transportation has not occurred abnormally, the distance value H between the contour center of the material within n consecutive frames and the set material transportation position center is collected, and the curve function H(x) of the distance value changing with the number of frames is drawn up. The offset value D is obtained through the formula The formula represents the change situation of the initial distance value and the end distance value within n frames of photos, and the formula represents the overall change situation within n frames of photos. Obviously, the larger the offset value D, the greater the potential offset abnormality of the material during transportation. Therefore, the obtained offset value D is compared with the offset judgment threshold D s preset according to experience. When D > D s If so, it is determined that there is a potential abnormality in the material transportation. In this way, the potential abnormalities and known abnormalities that occur during the transportation of materials on the production line can be comprehensively analyzed based on the associated parameter information generated during material transportation, so as to make a response adjustment in a timely manner to ensure the normal operation of the production line.

[0077] The working method of the execution module is: when it is determined that there is a potential abnormality in the material transportation, a first-level alarm is generated, and at this time, the material transportation speed is adjusted;

[0078] When it is determined that the material transportation is abnormal and H x < H < H y If so, a second-level alarm is generated, and at this time, the material transportation speed is adjusted and the position of the material is adjusted at the same time;

[0079] When it is determined that the material transportation is abnormal and H > Hy When this occurs, a third-level alarm is generated and the machine is immediately stopped;

[0080] where H x and H y are two set distance offset judgment thresholds.

[0081] The above technical solution provides a method for the execution module to respond to alarms. First, when it is determined that there is a potential abnormality in material transportation, it indicates that no abnormality has occurred at this time, but there is a potential transportation abnormality, so a first-level alarm is generated and the material transportation speed is slightly adjusted to avoid subsequent abnormalities; and when it is determined that the material transportation is abnormal and H x <H<H y where H x and H y are two set distance offset judgment thresholds determined based on the historical data of the production line combined with empirical data, it indicates that an offset has occurred at this time, but the offset is not large, so a second-level alarm is generated, and the material transportation speed is adjusted and the position of the material is adjusted at the same time to restore the operation of the production line; and when it is determined that the material transportation is abnormal and H > H y it indicates that the offset is serious at this time, so a third-level alarm is generated and the machine is immediately stopped for inspection and repair; in this way, the transportation efficiency of the entire production line is guaranteed.

[0082] It should be noted that for the convenience of analysis and calculation, the data parameters in the above formula are all dimensionless calculations after processing, and the dimensionless processing method is processed by the existing technology and will not be described in detail here.

[0083] The above content is only an example and explanation of the concept of the present invention. Those skilled in the art of this technology make various modifications or supplements to the described specific embodiments or use similar methods for substitution. As long as they do not deviate from the concept of the invention or exceed the scope defined by this claim book, they should all fall within the protection scope of the present invention.

Claims

1. A material conveying control system in an automated production line, characterized in that, The control system includes: A material resource acquisition module, which is used to acquire resource parameter information related to the material to be transported; A production line monitoring module, which is used to acquire correlation parameter information related to transportation during the transportation of materials on the production line; A material transportation path selection module, which is used to analyze based on the acquired resource parameter information and correlation parameter information, so as to select the best transportation path for the material; An analysis and control module, which is used to analyze based on the monitored correlation parameter information to judge whether an abnormality occurs during the transportation of the material; An execution module, which performs corresponding alarm responses when it is judged that the material transportation is abnormal.

2. The material conveying control system in an automated production line according to claim 1, characterized in that, The resource parameter information includes the physical characteristic information of the material, the production demand information of the material, and the environmental demand information of the material. The correlation parameter information includes the acquired production line image information, the power consumption information of the production line transportation equipment, the temperature information of the production line transportation equipment, the fault information of the production line transportation equipment, and the production line transportation completion information.

3. The material conveying control system in an automated production line according to claim 2, characterized in that, The working method of the material transportation path selection module is as follows: According to the obtained resource parameter information of the material to be transported, through the formula the state value Z of the material to be transported is obtained M , where m is the total number of resource items of the material to be transported obtained, M i is the parameter value obtained under the i-th resource item, ∈ i is the weight coefficient of the i-th resource item, and i ∈ [1, m]; Meanwhile, based on the neural network model training technology, during material transportation, a corresponding state value matching interval [Z M x, Z M y] is set for each production line; Match the status value Z of the material to be conveyed M with the status value matching intervals [Z M x, Z M y] corresponding to each production line; Select the production lines that meet the requirements for transporting the material to be transported, denoted as the set of candidate production lines. The screening requirements are: Z M ∈ [Z M x, Z M y]; Simultaneously obtain the material quantity to be conveyed PL of each production line in the set of candidate production lines m , the estimated waiting duration PL t and the operating condition value P. Through the formula Obtain the matching coefficient k for each production line; Sort each production line in ascending order according to the magnitude of the matching coefficient k, and select the production line with the highest ranking as the best transportation path for the material; Among them, PL t0 is a preset waiting duration reference value, L s0 is a preset production line conveying length reference value, T s0 is a preset production line conveying duration reference value, L s is the conveying length of the production line, T s is the conveying duration of the production line, and α1 and α2 are proportionality coefficients.

4. The material conveying control system in an automated production line according to claim 3, wherein, The method for obtaining the operating condition value P is as follows: Obtain the power consumption value P during the conveyance of the production line within the Δt period P and the device temperature value P T , and formulate the curve function P P (t) of the power consumption value varying with time, and the curve function P T (t) of the temperature value varying with time; Through the formula obtain the operating condition value P of the production line; Among them, P n is the number of production line failures during the Δt period, P qr is the task completion volume of the production line during the Δt period, P qr0 is the expected task completion volume during the Δt period, t a is the start time point of the Δt period, t b is the end time point of the Δt period, P P0 (t) is the standard curve function of the power consumption value changing with time formulated according to historical data, P T0 (t) is the standard curve function of the temperature value changing with time formulated according to historical data.

5. The material conveying control system in an automated production line according to claim 2, characterized in that, The working method of the analysis and control module is as follows: Real-time capture the image information of the production line when transporting materials through a camera, process the image information, use the edge detection algorithm to identify the contour of the material, and judge whether the contour of the material is within the set material transportation position interval: When all the material contours fall within the set material transportation position interval, it is judged that the material transportation is normal; Otherwise, it is judged that the material transportation is abnormal.

6. The material conveying control system in an automated production line according to claim 5, characterized in that, The working method of the analysis and control module also includes: When it is judged that no abnormality occurs in the material transportation, collect the distance value H between the contour center of the material and the set material transportation position center within n consecutive frames, and formulate a curve function H(x) of the distance value changing with the number of frames; Derive the offset value D through the formula ​ When D > D s it is determined that there is a potential abnormality in material transportation; Among them, x1 is the first frame of image obtained, and x n is the last frame of image obtained. H(x1) is the distance value of the first frame of image, and H(x n ) is the distance value of the last frame of image. D s is a preset offset judgment threshold value.

7. The material conveying control system in an automated production line according to claim 6, wherein The working method of the execution module is as follows: When it is judged that there is a potential abnormality in the material transportation, generate a first-level alarm, and at this time, adjust the material transportation speed; When it is determined that the material transportation is abnormal and H x <H<H y When this occurs, a secondary alarm is generated. At this time, the material transportation speed is adjusted and the position of the material is also adjusted; When it is determined that the material transportation is abnormal and H > H y a third-level alarm is generated and the machine is immediately stopped; Among them, H x and H y are two set distance offset judgment thresholds.

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