A conveying device and method for intelligent production of beverages

Abstract

The present application provides a conveying device and method for intelligent beverage production, firstly collecting the vibration state information of each conveyor belt; then extracting the vibration feedback characteristics of each conveyor belt under the corresponding load state; determining the load offset of each conveyor belt during the guide roller traction process according to the resonance characteristics of each conveyor belt under the corresponding load state and the displacement fluctuation of the beverage cans on the beverage production line during the transportation process, and further determining the vibration suppression amount of each conveyor belt during the guide roller traction process; determining the guided conveying cost of each conveyor belt under the corresponding load state through all the vibration suppression amounts and the collision margin of the beverage cans on the beverage production line; and adaptively adjusting the hydraulic vibration buffer on each drive device based on all the guided conveying costs. The scheme of the present application can reduce the dynamic load changes borne by the conveyor belt during operation due to vibration, thereby improving the stability of the beverage cans during the transportation process.

Description

Technical Field

[0001] The present application relates to the technical field of conveying equipment, and more specifically, to a conveying equipment and method for intelligent beverage production. Background Art

[0002] The combination of food production and processing with intelligent manufacturing equipment is leading the transformation of beverage production. Intelligent manufacturing equipment uses automation and Internet of Things technology to achieve efficient monitoring and data analysis of beverage production lines, significantly improving production efficiency and product quality. In the intelligent production of beverages, conveying equipment plays a vital role. Modern conveying equipment is equipped with an intelligent control system that can adjust the transportation speed and path according to real-time data to ensure the coordinated operation of all aspects of production. At the same time, these devices monitor product status through sensors and visual recognition technology, identify and handle potential problems in a timely manner, and reduce human errors. With the continuous advancement of technology, the intelligent transformation of the food industry has greatly improved the safety and quality of beverage products.

[0003] In the prior art, the conveying control of intelligent beverage production is achieved by combining sensors and intelligent algorithms to monitor the running status of the conveyor belt in real time, and adjust the belt speed and direction according to the load, position, posture of the beverage cans on the conveyor belt and the vibration amplitude of the conveyor belt to reduce the impact of vibration on the can body. However, due to the vibration of the conveyor belt, the conveyor belt will be subjected to dynamic load changes during the traction process of the guide roller, that is, the load change on the conveyor belt is no longer constant, but fluctuates with the vibration change. Especially under high load and high speed conditions, the vibration will cause the belt body to produce periodic displacement and fluctuation. This dynamic load change will cause the center line of the belt body to deviate, resulting in the tipping, collision or blockage of the beverage can during the transportation process. Therefore, how to reduce the dynamic load changes that the conveyor belt is subjected to during operation caused by vibration, thereby improving the stability of the beverage can during the transportation process is a difficult problem faced by the industry. Summary of the invention

[0004] The present application provides a conveying device and method for intelligent beverage production, which can reduce the dynamic load changes on the conveyor belt caused by vibration during operation, thereby improving the stability of beverage cans during transportation.

[0005] In a first aspect, the present application provides a conveying and guiding method for intelligent production of beverages, which is used to control the conveying of beverage cans on a beverage production line, wherein the beverage cans are conveyed by a plurality of conveyor belts, each of which comprises a driving device, wherein a hydraulic vibration buffer is provided on the driving device, and comprises the following steps:

[0006] A vibration sensor is arranged on each conveyor belt to obtain vibration status information sent by each vibration sensor;

[0007] Extract the vibration feedback characteristics of each conveyor belt under the corresponding load state from all vibration state information;

[0008] Determine the load offset of each conveyor belt during the traction process of the guide roller according to the resonance characteristics of each conveyor belt under the corresponding load state and the displacement fluctuation of the beverage cans on the beverage production line during the conveying process, and determine the vibration suppression amount of each conveyor belt during the traction process of the guide roller according to all load offsets and the vibration feedback characteristics of each conveyor belt under the corresponding load state;

[0009] Determine the guiding and conveying cost of each conveyor belt under the corresponding load state by using all vibration suppression quantities and the collision margin of beverage cans on the beverage production line;

[0010] The hydraulic vibration dampers at the individual drives are adaptively adjusted based on all guided transport costs.

[0011] In some embodiments, extracting the vibration feedback characteristics of each conveyor belt under the corresponding load state from all vibration state information specifically includes:

[0012] According to different load states, each vibration state information is divided into a light load vibration state information set, a medium load vibration state information set and a heavy load vibration state information set;

[0013] Clustering the light-load vibration state information set, the medium-load vibration state information set, and the heavy-load vibration state information set respectively, thereby obtaining a plurality of light-load vibration state information clusters, a plurality of medium-load vibration state information clusters, and a plurality of heavy-load vibration state information clusters;

[0014] Determine the vibration feedback characteristics of each conveyor belt in the light load state according to the vibration gradient in each vibration state information and all light load vibration state information clusters;

[0015] Determine the vibration feedback characteristics of each conveyor belt under the medium load state through the vibration gradient in each vibration state information and all medium load vibration state information clusters;

[0016] The vibration feedback characteristics of each conveyor belt under the heavy load state are determined according to the vibration gradient in each vibration state information and all the heavy load vibration state information clusters.

[0017] In some embodiments, determining the load offset of each conveyor belt during the traction process of the guide roller according to the resonance characteristics of each conveyor belt under the corresponding load state and the displacement fluctuation of the beverage cans on the beverage production line during the conveying process specifically includes:

[0018] Obtain the resonance data of each conveyor belt at different key positions under corresponding load conditions;

[0019] Extract features from each resonance data to obtain the resonance features of each conveyor belt under different load conditions;

[0020] Determine the resonance balance amount during the conveying process according to the resonance characteristics of each conveyor belt under different load conditions;

[0021] Determine the load fluctuation of each conveyor belt based on a preset regression model and the displacement fluctuation of beverage cans on the beverage production line during the conveying process;

[0022] The load deviation of each conveyor belt during the traction process of the guide roller is determined according to the resonance balancing amount during the conveying process and the load fluctuation amount of each conveyor belt.

[0023] In some embodiments, determining the vibration suppression amount of each conveyor belt during the traction process of the guide roller according to all load offsets and the vibration feedback characteristics of each conveyor belt under the corresponding load state specifically includes:

[0024] Performing linear fitting on all vibration gradients in each vibration state information to obtain a vibration gradient curve;

[0025] Determining the vibration overshoot of each conveyor belt according to the vibration gradient curve and the vibration feedback characteristics of each conveyor belt under the corresponding load state;

[0026] The vibration suppression amount of each conveyor belt during the traction process of the guide roller is determined by the vibration overshoot amount of each conveyor belt and all load offsets.

[0027] In some embodiments, determining the guided conveying cost of each conveyor belt under a corresponding load state by using all vibration suppression amounts and the collision margin of beverage cans on the beverage production line specifically includes:

[0028] Obtain collision information of beverage cans on each conveyor belt under different load conditions;

[0029] Determine the collision margin of beverage cans on the beverage production line based on a preset sliding window and all collision information;

[0030] Determine the maximum guided collision factor and the minimum guided collision factor through the collision margin of beverage cans on the beverage production line;

[0031] The guiding and conveying cost of each conveyor belt under the corresponding load state is determined according to the maximum guiding collision factor, the minimum guiding collision factor and all vibration suppression amounts.

[0032] In some embodiments, adaptively adjusting the hydraulic vibration buffer on each drive device based on all guided transport costs specifically includes:

[0033] Determine the following adjustment coefficient according to all the guided transport costs;

[0034] The hydraulic vibration damper is controlled via the following control factor at the individual drive units.

[0035] In some embodiments, the vibration sensor is a piezoelectric vibration sensor.

[0036] In a second aspect, the present application provides a conveying device for intelligent production of beverages, the conveying device comprising a plurality of conveyor belts, each of which is provided with a vibration sensor, the conveyor belts each comprising a driving device, a hydraulic vibration buffer being provided on the driving device, the conveying device further comprising a conveying guide unit, the conveying guide unit comprising:

[0037] An acquisition module is used to acquire vibration state information sent by each vibration sensor;

[0038] A processing module, used for extracting vibration feedback characteristics of each conveyor belt under corresponding load state from all vibration state information;

[0039] The processing module is further used to determine the load offset of each conveyor belt during the traction process of the guide roller according to the resonance characteristics of each conveyor belt under the corresponding load state and the displacement fluctuation of the beverage cans on the beverage production line during the conveying process, and determine the vibration suppression amount of each conveyor belt during the traction process of the guide roller according to all the load offsets and the vibration feedback characteristics of each conveyor belt under the corresponding load state;

[0040] The processing module is further used to determine the guided conveying cost of each conveyor belt under the corresponding load state through all vibration suppression amounts and the collision margin of beverage cans on the beverage production line;

[0041] The execution module is used to adaptively adjust the hydraulic vibration damper on each drive device based on all guided conveying costs.

[0042] In a third aspect, the present application provides a computer device, comprising a memory and a processor, wherein the memory stores codes, and the processor is configured to obtain the codes and execute the above-mentioned conveying guidance method for intelligent beverage production.

[0043] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned conveying guidance method for intelligent beverage production is implemented.

[0044] The technical solution provided by the embodiments disclosed in this application has the following beneficial effects:

[0045] In the conveying equipment and method for intelligent production of beverages provided by the present application, first, a vibration sensor is set on each conveyor belt to obtain the vibration state information sent by each vibration sensor; the vibration feedback characteristics of each conveyor belt under the corresponding load state are extracted from all the vibration state information; the load offset of each conveyor belt during the guide roller traction process is determined according to the resonance characteristics of each conveyor belt under the corresponding load state and the displacement fluctuation of the beverage cans on the beverage production line during the transportation process, and the vibration suppression amount of each conveyor belt during the guide roller traction process is determined according to all the load offsets and the vibration feedback characteristics of each conveyor belt under the corresponding load state; the guided conveying cost of each conveyor belt under the corresponding load state is determined by all the vibration suppression amounts and the collision margin of the beverage cans on the beverage production line; and the hydraulic vibration buffer on each drive device is adaptively adjusted based on all the guided conveying costs.

[0046] It can be seen that in the present application, the guided conveying cost of each conveyor belt under the corresponding load state can be determined by all the vibration suppression amounts and the collision margin of the beverage cans on the beverage production line; wherein, firstly, based on the preset regression model, the parameter amount of the dynamic load change fluctuation that each conveyor belt bears during the transmission process is extracted from the displacement fluctuation of the beverage cans on the beverage production line during the transportation process, and then the load offset of each conveyor belt during the guide roller traction process is determined by the resonance characteristics of each conveyor belt under the corresponding load state and the load fluctuation amount of each conveyor belt, wherein the load offset represents the parameter of the lateral deviation of the load center of gravity on the conveyor belt due to the influence of the dynamic load change under the traction of the guide roller, and further all the vibration gradients in each vibration state information are linearly fitted to obtain the vibration gradient curve, and the vibration gradient curve and the vibration feedback characteristics of the conveyor belt under different load states are used to obtain the vibration overshoot used to measure the actual vibration amplitude of the conveyor belt exceeding the steady-state vibration amplitude during the transportation process, wherein the vibration overshoot can reflect the excessive response of the conveyor belt to dynamic load changes. degree, and then all load offsets are quantified according to the vibration overshoot to obtain the vibration suppression amount of each conveyor belt during the traction process of the guide roller. By adjusting the vibration suppression amount, the vibration of the conveyor belt can be kept within a controllable range, thereby reducing the negative impact; secondly, the collision margin of the beverage cans on the beverage production line is extracted from the collision information of the beverage cans on each conveyor belt under different load conditions, wherein the collision margin can reflect the possibility of collision of the beverage cans on the beverage production line during transportation; then, all vibration suppression amounts are feature extracted through the collision margin of the beverage cans on the beverage production line to obtain the guided transportation cost of each conveyor belt under the corresponding load state, wherein the guided transportation cost represents the cost of the guided adjustment required to ensure the stable transportation of the beverage cans when the conveyor belt faces dynamic load changes; finally, based on all the guided transportation costs, the hydraulic vibration buffers on each drive device are adaptively adjusted; in summary, the scheme of the present application can reduce the dynamic load changes that the conveyor belt is subjected to during operation due to vibration, thereby improving the stability of the beverage cans during transportation. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 is an exemplary flow chart of a conveying guidance method for intelligent beverage production according to some embodiments of the present application;

[0048] Figure 2 is a schematic diagram of a flow chart for determining a vibration suppression amount in some embodiments of the present application;

[0049] Figure 3 is a schematic diagram of a process for determining a guided transport cost in some embodiments of the present application;

[0050] Figure 4is a schematic structural diagram of a conveying guide unit according to some embodiments of the present application;

[0051] Figure 5 It is a structural schematic diagram of a computer device for implementing a conveying guidance method for intelligent beverage production according to some embodiments of the present application. DETAILED DESCRIPTION

[0052] In order to better understand the technical solution of the present application, the technical solution of the present application will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0053] refer to Figure 1 , which is an exemplary flow chart of a method for guiding the delivery of beverages for intelligent production according to some embodiments of the present application. The method 100 for guiding the delivery of beverages for intelligent production mainly includes the following steps:

[0054] In step 101, a vibration sensor is provided on each conveyor belt to obtain vibration state information sent by each vibration sensor.

[0055] The vibration sensor in the present application is a piezoelectric vibration sensor or other types of vibration sensors, which are not specifically limited here. In specific implementation, the vibration state information of each conveyor belt during the transmission process can be obtained from the vibration sensors on each conveyor belt.

[0056] It should also be noted that the vibration state information described in the present application is an ordered sequence consisting of multiple vibration amplitudes that change over time, wherein the range of time changes in the vibration state information is within the last hour after the start of delivery, and the time interval between each vibration amplitude is seconds. In other embodiments, the range of time changes can also be set to other intervals, which are not limited here.

[0057] It should be noted that, in the present application, each conveyor belt corresponds to a vibration state information.

[0058] In step 102, the vibration feedback characteristics of each conveyor belt under the corresponding load state are extracted from all vibration state information.

[0059] In some embodiments, extracting the vibration feedback characteristics of each conveyor belt under the corresponding load state from all vibration state information can be achieved by using the following steps:

[0060] According to different load states, each vibration state information is divided into a light load vibration state information set, a medium load vibration state information set and a heavy load vibration state information set;

[0061] Clustering the light-load vibration state information set, the medium-load vibration state information set, and the heavy-load vibration state information set respectively, thereby obtaining a plurality of light-load vibration state information clusters, a plurality of medium-load vibration state information clusters, and a plurality of heavy-load vibration state information clusters;

[0062] Determine the vibration feedback characteristics of each conveyor belt in the light load state according to the vibration gradient in each vibration state information and all light load vibration state information clusters;

[0063] Determine the vibration feedback characteristics of each conveyor belt under the medium load state through the vibration gradient in each vibration state information and all medium load vibration state information clusters;

[0064] The vibration feedback characteristics of each conveyor belt under the heavy load state are determined according to the vibration gradient in each vibration state information and all the heavy load vibration state information clusters.

[0065] It should be noted that in the present application, the load state includes three states: light load, medium load and heavy load. Among them, light load means that the total weight of all beverage cans on the conveyor belt is less than 30% of the maximum design bearing capacity of the equipment, medium load means that the total weight of all beverage cans on the conveyor belt is between 30% and 70% of the maximum design bearing capacity of the equipment, and heavy load means that the total weight of all beverage cans on the conveyor belt is more than 70% of the maximum design bearing capacity of the equipment.

[0066] In specific implementation, the light load vibration state information set, the medium load vibration state information set and the heavy load vibration state information set are clustered respectively, and then a plurality of light load vibration state information clusters, a plurality of medium load vibration state information clusters and a plurality of heavy load vibration state information clusters are obtained. The following method can be adopted, namely: taking the maximum vibration amplitude in each vibration state information as the standard, using the DBSCAN clustering algorithm to cluster the vibration state information in the light load vibration state information set, the medium load vibration state information set and the heavy load vibration state information set respectively, so as to obtain a plurality of light load vibration state information clusters, a plurality of medium load vibration state information clusters and a plurality of heavy load vibration state information clusters. In other embodiments, other methods can also be adopted for implementation, which will not be repeated here.

[0067] It should be noted that the vibration gradient in the vibration state information in the present application can be calculated using the difference method for the vibration amplitude in the vibration state information. In addition, there are multiple vibration gradients in each vibration state information.

[0068] In specific implementation, the vibration feedback characteristics of each conveyor belt in the light load state are determined according to the vibration gradients in each vibration state information and all the light load vibration state information clusters. The following method is adopted, namely: first, a negative exponential function with the natural logarithm e as the base is calculated for all vibration gradients in each vibration state information in the light load vibration state information cluster, and the result obtained after calculating the negative exponential function with the natural logarithm e as the base is used as the light load vibration gradient coefficient of each vibration state information. Then, a light load vibration state information cluster is selected as the selected light load vibration state information cluster, the light load vibration gradient coefficient of each vibration state information in the selected light load vibration state information cluster is multiplied by the value of the cluster center of the selected light load vibration state information cluster, and the multiplied value is used as the vibration feedback characteristics of the conveyor belt corresponding to each vibration state information in the selected light load vibration state information cluster in the light load state, and the vibration feedback characteristics of the conveyor belt corresponding to each vibration state information in the remaining light load vibration state information clusters in the light load state are continuously determined. In other embodiments, other methods may also be adopted for implementation, which will not be repeated here.

[0069] In specific implementation, the vibration feedback characteristics of each conveyor belt under the medium load state are determined by the vibration gradients in each vibration state information and all the medium load vibration state information clusters. The following method is adopted, namely: first, a negative exponential function with the natural logarithm e as the base is calculated for all vibration gradients in each vibration state information in the medium load vibration state information cluster, and the negative exponential function with the natural logarithm e as the base is calculated as the medium load vibration gradient coefficient of each vibration state information. Then, a medium load vibration state information cluster is selected as the selected medium load vibration state information cluster, the medium load vibration gradient coefficient of each vibration state information in the selected medium load vibration state information cluster is multiplied by the value of the cluster center of the selected medium load vibration state information cluster, and the multiplied value is used as the vibration feedback characteristics of the conveyor belt corresponding to each vibration state information in the selected medium load vibration state information cluster under the medium load state, and the vibration feedback characteristics of the conveyor belt corresponding to each vibration state information in the remaining light load vibration state information cluster under the medium load state are continuously determined. Other methods can also be adopted in other embodiments, which are not limited here.

[0070] In specific implementation, the vibration feedback characteristics of each conveyor belt under the heavy load state are determined according to the vibration gradients in each vibration state information and all the heavy load vibration state information clusters. The following method is adopted, namely: first, a negative exponential function with the natural logarithm e as the base is calculated for all vibration gradients in each vibration state information in the heavy load vibration state information cluster, and the result obtained after calculating the negative exponential function with the natural logarithm e as the base is used as the heavy load vibration gradient coefficient of each vibration state information. Then, a heavy load vibration state information cluster is selected as the selected heavy load vibration state information cluster, the heavy load vibration gradient coefficient of each vibration state information in the selected heavy load vibration state information cluster is multiplied by the value of the cluster center of the selected heavy load vibration state information cluster, and the multiplied value is used as the vibration feedback characteristics of the conveyor belt corresponding to each vibration state information in the selected heavy load vibration state information cluster under the heavy load state, and the vibration feedback characteristics of the conveyor belt corresponding to each vibration state information in the remaining heavy load vibration state information clusters under the heavy load state are continuously determined. In other embodiments, other methods can also be adopted for implementation, which will not be repeated here.

[0071] It should be noted that the vibration feedback characteristics described in the present application represent abnormal feedback characteristics when the conveyor belt vibrates unbalanced under different load conditions.

[0072] In step 103, the load offset of each conveyor belt during the guide roller traction process is determined based on the resonance characteristics of each conveyor belt under the corresponding load state and the displacement fluctuation of the beverage cans on the beverage production line during the conveying process, and the vibration suppression amount of each conveyor belt during the guide roller traction process is determined based on all load offsets and the vibration feedback characteristics of each conveyor belt under the corresponding load state.

[0073] In some embodiments, the load offset of each conveyor belt during the traction process of the guide roller can be determined according to the resonance characteristics of each conveyor belt under the corresponding load state and the displacement fluctuation of the beverage cans on the beverage production line during the conveying process. The following steps can be used, namely:

[0074] Obtain the resonance data of each conveyor belt at different key positions under corresponding load conditions;

[0075] Extract features from each resonance data to obtain the resonance features of each conveyor belt under different load conditions;

[0076] Determine the resonance balance amount during the conveying process according to the resonance characteristics of each conveyor belt under different load conditions;

[0077] Determine the load fluctuation of each conveyor belt based on a preset regression model and the displacement fluctuation of beverage cans on the beverage production line during the conveying process;

[0078] The load deviation of each conveyor belt during the traction process of the guide roller is determined according to the resonance balancing amount during the conveying process and the load fluctuation amount of each conveyor belt.

[0079] It should be noted that the key positions of the conveyor belt in the present application are the tensioning device and the guide roller, wherein the tensioning device is located at both ends of the conveyor belt, close to the driving wheel, and the guide roller is located along the edge of the conveyor belt. There are multiple tensioning devices and multiple guide rollers in the present application.

[0080] In addition, it should be noted that the resonance data described in the present application is composed of vibration frequency data and vibration amplitude data, wherein the vibration frequency data is composed of a plurality of vibration frequency values ​​forming an ordered sequence that varies with time, and the time interval between each vibration frequency value is seconds, and the vibration amplitude data is composed of a plurality of vibration amplitudes forming an ordered sequence that varies with time, and the time interval between each vibration amplitude is seconds, and the resonance data can be obtained by vibration sensors arranged at various key positions of the conveyor belt, and at the same time, each resonance data corresponds to a conveyor belt, and each conveyor belt corresponds to a load state, that is, each resonance data corresponds to a load state.

[0081] In specific implementation, feature extraction is performed on each resonance data to obtain the resonance characteristics of each conveyor belt under different load conditions. The following method can be used, namely: select one resonance data as the selected resonance data, first, use filtering technology (such as a low-pass filter, which is not limited here) to remove the noise in the selected resonance data, and use the data obtained after the noise is removed as filtered resonance data, wherein the filtered resonance data are composed of filtered resonance frequency data and filtered resonance amplitude data. Secondly, use wavelet transform to process the filtered resonance frequency data to obtain wavelet coefficients, and further perform standard deviation and kurtosis on the filtered resonance amplitude data, and then divide the kurtosis by the standard deviation, so as to multiply the value obtained by the division by the wavelet coefficient, and use the multiplied value as the resonance characteristic of the conveyor belt corresponding to the selected resonance data under the corresponding load state, and continue to determine the resonance characteristics of the conveyor belt corresponding to the remaining resonance data under the corresponding load state. In other embodiments, other methods can also be used for implementation, which are not limited here.

[0082] It should be noted that the resonance characteristics described in the present application represent characteristic parameters of the conveyor belt under corresponding load conditions when the equipment on the beverage production line resonates. The resonance characteristics can be used to monitor excessive vibration and resonance of the conveyor belt during actual operation.

[0083] In specific implementation, the resonance balance amount in the conveying process can be determined according to the resonance characteristics of each conveyor belt under different load conditions. That is, the average of the resonance characteristics under different load conditions is obtained, and the obtained average is used as the resonance balance amount of the conveyor belt. In other embodiments, other methods can also be used to implement it, which will not be repeated here.

[0084] It should be noted that the resonance balance amount described in the present application represents the parameter amount that affects the overall stability of the conveyor belt when the equipment on the beverage production line resonates.

[0085] It should also be noted that in the present application, the displacement fluctuation of the beverage cans on the beverage production line during the conveying process represents the total change in displacement of the beverage cans on the beverage production line due to the vibration during the conveying process, which can be obtained through the displacement sensors installed on the guide rollers at the edges of each conveyor belt, and the sum of all monitored displacement values ​​of the beverage cans is taken as the displacement fluctuation of the beverage cans on the beverage production line during the conveying process.

[0086] In addition, it should be noted that the preset regression model can use the ridge regression algorithm to establish a model of the relationship between the historical vibration frequency, historical vibration amplitude of the conveyor belt under different load conditions and the historical displacement fluctuations of the beverage cans in the transportation process on the beverage production line. In other embodiments, other algorithms can also be used, which are not limited here.

[0087] In specific implementation, the load fluctuation amount of each conveyor belt is determined based on a preset regression model and the displacement fluctuation of beverage cans on the beverage production line during the transportation process. This can be achieved in the following manner, namely: the vibration frequency and vibration amplitude of each conveyor belt are obtained, and the vibration frequency and vibration amplitude of each conveyor belt are input into the preset regression model to obtain the predicted displacement fluctuation of beverage cans on the beverage production line during the transportation process, and then the displacement fluctuation is subtracted from the predicted displacement fluctuation, and the subtracted value is divided by the total load on each conveyor belt (which can be obtained by setting a weighing sensor on the conveyor belt), and the divided value is used as the load fluctuation amount of each conveyor belt. Other methods can also be used in other embodiments, which are not limited here.

[0088] It should be noted that the load fluctuation in the present application is a parameter that evaluates the dynamic load fluctuation that the conveyor belt bears during the transmission process. If the load fluctuation is too large, it indicates that the conveyor belt exhibits great instability when facing dynamic loads, which will cause shaking or displacement of beverage cans on the conveyor belt.

[0089] In specific implementation, the load offset of each conveyor belt during the guide roller traction process is determined based on the resonance balance amount in the conveying process and the load fluctuation amount of each conveyor belt. This can be achieved in the following manner, namely: first, the load fluctuation amount of each conveyor belt is normalized to the minimum-maximum value, and then the normalized values ​​are divided by the resonance balance amount, and the divided values ​​are used as the load offset of each conveyor belt during the guide roller traction process. Other methods can also be used in other embodiments, which are not limited here.

[0090] It should be noted that the load offset in the present application refers to the parameter of the lateral deviation of the load center of gravity on the conveyor belt due to the influence of dynamic load changes when the conveyor belt is pulled by the guide roller.

[0091] In some embodiments, reference Figure 2 As shown, this figure is a schematic diagram of the process of determining the vibration suppression amount in some embodiments of the present application. In this embodiment, the vibration suppression amount of each conveyor belt during the traction process of the guide roller is determined according to all load offsets and the vibration feedback characteristics of each conveyor belt under the corresponding load state, which can be achieved by the following steps:

[0092] First, in step 1031, linear fitting is performed on all vibration gradients in each vibration state information to obtain a vibration gradient curve;

[0093] Next, in step 1032, the vibration overshoot of each conveyor belt is determined according to the vibration gradient curve and the vibration feedback characteristics of each conveyor belt under the corresponding load state;

[0094] Then, in step 1033, the vibration suppression amount of each conveyor belt during the traction process of the guide roller is determined by the vibration overshoot amount of each conveyor belt and all load offsets.

[0095] In specific implementation, linear fitting is performed on all vibration gradients in each vibration state information to obtain a vibration gradient curve, which can be achieved in the following manner, namely: all vibration gradients are selected from each vibration state information, all vibration gradients are sorted in ascending order, and then the least squares support vector machine algorithm in the prior art is used to fit the sequence obtained after the ascending order, and the fitted sequence is used as the vibration gradient curve. In other embodiments, other fitting algorithms can also be used, which are not limited here.

[0096] It should be noted that in the present application, each value on the vibration gradient curve is used as a vibration gradient fitting value, wherein each vibration gradient fitting value corresponds to a vibration gradient.

[0097] In specific implementation, the vibration overshoot of each conveyor belt can be determined according to the vibration gradient curve and the vibration feedback characteristics of each conveyor belt under the corresponding load state. That is, first, the absolute value is taken after subtracting the corresponding vibration gradient from the vibration gradient fitting value on the vibration gradient curve, and then all the values ​​obtained after taking the absolute values ​​are summed, and the summed value is used as the fitting residual, and then, the fitting residuals are multiplied by the vibration feedback characteristics of each conveyor belt under the corresponding load state, and the multiplied value is used as the vibration overshoot of each conveyor belt. In other embodiments, other methods can also be used for implementation, which will not be repeated here.

[0098] It should be noted that the vibration overshoot described in the present application represents a parameter quantity in which the actual vibration amplitude exceeds the steady-state vibration amplitude, and the vibration overshoot reflects the degree of over-reaction of the conveyor belt when facing dynamic load changes.

[0099] In specific implementation, the vibration suppression amount of each conveyor belt during the guide roller traction process is determined by the vibration overshoot of each conveyor belt and all load offsets. This can be achieved in the following manner, namely: first, a negative exponential function with the natural logarithm e as the base is calculated for all load offsets, and then all values ​​obtained after calculating the negative exponential function with the natural logarithm e as the base are summed, and the summed value is used as the load offset adjustment coefficient, and then, the vibration overshoot of each conveyor belt is divided by the sum of 1 and the load offset adjustment coefficient, and the value obtained by division is used as the vibration suppression amount of each conveyor belt during the guide roller traction process. Other methods can also be used in other embodiments, which are not limited here.

[0100] It should be noted that the vibration suppression amount in the present application refers to the adjustment amount of the conveyor belt to offset the vibration caused by dynamic load changes during the traction process of the guide roller. By adjusting the vibration suppression amount, the vibration of the conveyor belt can be kept within a controllable range, thereby reducing negative impacts.

[0101] In step 104, the guided conveying cost of each conveyor belt under the corresponding load state is determined by all vibration suppression amounts and the collision margin of beverage cans on the beverage production line.

[0102] In some embodiments, reference Figure 3 As shown, this figure is a schematic diagram of the process of determining the guided conveying cost in some embodiments of the present application. In this embodiment, the guided conveying cost of each conveyor belt under the corresponding load state is determined by all vibration suppression amounts and the collision margin of beverage cans on the beverage production line, which can be achieved by the following steps:

[0103] First, in step 1041, collision information of beverage cans on each conveyor belt under different load conditions is obtained;

[0104] Secondly, in step 1042, the collision margin of the beverage cans on the beverage production line is determined according to the preset sliding window and all the collision information;

[0105] Then, in step 1043, the maximum guide collision factor and the minimum guide collision factor are determined by the collision margin of the beverage cans on the beverage production line;

[0106] Finally, in step 1044, the guided conveying cost of each conveyor belt under the corresponding load state is determined according to the maximum guided collision factor, the minimum guided collision factor and all vibration suppression amounts.

[0107] In specific implementation, the force is detected by embedding multiple force sensors on the surface of each conveyor belt, and the set of multiple force values ​​detected is used as the collision information of the beverage cans on the corresponding conveyor belt during the conveying process. At the same time, the load state of each conveyor belt is detected, and each conveyor belt is marked according to different load states, so as to obtain the collision information of the beverage cans on each conveyor belt under different load states.

[0108] It should be noted that the detection principle of the force sensor described in the present application is that when a collision occurs between beverage cans on a conveyor belt, the force generated by the collision will be transmitted to the force sensor through the surface of the conveyor belt, thereby obtaining information about the collision. In addition, it should be noted that each conveyor belt corresponds to a load state, and each collision information corresponds to a conveyor belt.

[0109] It should be noted that the sliding window described in the present application represents a sequence for processing collision information, which can be set using a fixed-length sequence, wherein the fixed length can be set using a value obtained by taking the square root of the total number of force values ​​in the collision information and rounding it down.

[0110] In specific implementation, the collision margin of beverage cans on the beverage production line is determined according to a preset sliding window and all collision information. The following method is used, namely: select a collision information as the selected collision information, first, sort all the force values ​​in the selected collision information in ascending order, and use the sequence obtained after the ascending order as the collision sequence, and secondly, align the sliding window with the first force value in the collision sequence, select the maximum force value and the minimum force value from the force values ​​covered by the sliding window, subtract the minimum force value from the maximum force value, and use the subtracted value as the collision strength of the first force value, move the sliding window, align the sliding window with the second force value in the collision sequence, and then The maximum force value and the minimum force value are selected from the force values ​​covered by the sliding window, and the minimum force value is subtracted from the maximum force value, and the subtracted value is used as the collision force of the second force value, and so on, until the sliding window is aligned with the last force value in the collision sequence, all the collision forces are summed up, and the summed value is used as the local collision margin of the beverage cans on the conveyor belt corresponding to the selected collision information, and the local collision margin of the beverage cans on the conveyor belt corresponding to the remaining collision information is continued to be determined. Finally, all the local collision margins are summed up, and the summed value is used as the collision margin of the beverage cans on the beverage production line. In other embodiments, other methods can also be used to achieve this, which is not limited here.

[0111] It should be noted that the collision margin described in the present application indicates the possibility of collision of beverage cans during transportation on a beverage production line. The larger the collision margin, the higher the possibility of collision of beverage cans during transportation, and vice versa.

[0112] In specific implementation, the maximum guide collision factor and the minimum guide collision factor can be determined by the collision margin of beverage cans on the beverage production line. This can be achieved in the following manner, namely: the largest local collision margin and the smallest local collision margin are selected from all local collision margins, the smallest local collision margin is divided by the difference between the largest local collision margin and the smallest local collision margin, and the value obtained by the division is used as the minimum guide collision factor, and then the largest local collision margin is divided by the difference between the largest local collision margin and the smallest local collision margin, and the value obtained by the division is used as the maximum guide collision factor. Other methods can also be used in other embodiments, which will not be repeated here.

[0113] It should be noted that in the present application, the maximum guide collision factor represents the maximum collision risk value that the beverage cans on the conveyor belt can withstand during the traction and guiding process of the guide rollers, and the minimum guide collision factor reflects the minimum collision risk value that the beverage cans on the conveyor belt can withstand during the traction and guiding process of the guide rollers. The maximum guide collision factor and the minimum guide collision factor can be used to identify the carrying capacity of the conveyor belt under the most extreme load.

[0114] In specific implementation, the guided conveying cost of each conveyor belt under the corresponding load state is determined according to the maximum guided collision factor, the minimum guided collision factor and all vibration suppression amounts. The following method is adopted, namely: a vibration suppression amount is selected as the selected vibration suppression amount, the selected vibration suppression amount is multiplied by the maximum guided collision factor, and the multiplied value is used as the transitional guided conveying amount, 1 is added to the minimum guided collision factor, and the added value is multiplied by the selected vibration suppression amount, the multiplied value is further added to the transitional guided conveying amount, and the multiplied value is used as the guided conveying cost of the conveyor belt corresponding to the selected vibration suppression amount under its corresponding load state, and the guided conveying cost of the conveyor belt corresponding to the remaining vibration suppression amounts under its corresponding load state is further determined. Other methods can also be adopted in other embodiments, which are not limited here.

[0115] It should be noted that the guided conveying cost described in the present application refers to the cost of guiding adjustment required for the conveyor belt to ensure stable transportation of beverage cans when facing dynamic load changes.

[0116] In step 105 , the hydraulic vibration dampers on the individual drive devices are adaptively adjusted based on all guided transport costs.

[0117] In some embodiments, adaptive adjustment of the hydraulic vibration buffer on each drive device based on all guided conveying costs can be achieved by the following steps:

[0118] Determine the following adjustment coefficient according to all the guided transport costs;

[0119] The hydraulic vibration damper is controlled via the following control factor at the individual drive units.

[0120] It should be noted that by adjusting the following adjustment coefficient, the response of the hydraulic vibration buffer to dynamic load changes can be improved, so that it can more accurately follow the actual load changes of the system, reduce the overshoot of vibration and displacement, and improve the stability of the system. As a preferred embodiment, the following adjustment coefficient can be determined based on all the guided conveying costs. The following method can be used, namely: calculating the mean of all the guided conveying costs, and using the obtained mean as the following adjustment coefficient. In other embodiments, other methods can also be used, which are not limited here.

[0121] In specific implementation, the following method can be used to guide and adjust the upper hydraulic vibration buffer on each drive device through the following adjustment coefficient, that is: the following adjustment coefficient is used as the adjustment coefficient of the valve oil flow in the hydraulic vibration buffer on each drive device, and then the oil flow is automatically adjusted to improve the vibration suppression ability of the hydraulic vibration buffer adjusted by the damping coefficient, thereby suppressing the vibration frequency of the conveyor belt at the selected guide rotating device. Other methods can also be used in other embodiments, which will not be repeated here.

[0122] In addition, in another aspect of the present application, in some embodiments, the present application provides a conveying device for intelligent production of beverages, the conveying device includes a plurality of conveyor belts, each of which is provided with a vibration sensor, the conveyor belts each include a driving device, a hydraulic vibration buffer is provided on the driving device, the conveying device also includes a conveying guide unit, reference Figure 4 , which is a schematic diagram of the structure of a conveying guide unit according to some embodiments of the present application, the conveying guide unit 400 includes: an acquisition module 401, a processing module 402 and an execution module 403, which are described as follows:

[0123] Acquisition module 401, in this application, acquisition module 401 is mainly used to acquire vibration state information sent by each vibration sensor;

[0124] Processing module 402, in the present application, the processing module 402 is used to extract the vibration feedback characteristics of each conveyor belt under the corresponding load state from all vibration state information;

[0125] It should be noted that the processing module 402 in the present application is also used to determine the load offset of each conveyor belt during the traction process of the guide roller according to the resonance characteristics of each conveyor belt under the corresponding load state and the displacement fluctuation of the beverage cans on the beverage production line during the transportation process, and determine the vibration suppression amount of each conveyor belt during the traction process of the guide roller according to all load offsets and the vibration feedback characteristics of each conveyor belt under the corresponding load state;

[0126] In addition, the processing module 402 in the present application is also used to determine the guided conveying cost of each conveyor belt under the corresponding load state through all vibration suppression amounts and the collision margin of beverage cans on the beverage production line;

[0127] The execution module 403 in the present application is mainly used to adaptively adjust the hydraulic vibration buffers on each driving device based on all the guided conveying costs.

[0128] In addition, the present application also provides a computer device, which includes a memory and a processor, wherein the memory stores codes, and the processor is configured to obtain the codes and execute the above-mentioned conveying guidance method for intelligent beverage production.

[0129] In some embodiments, reference Figure 5 , which is a schematic diagram of the structure of a computer device for implementing a conveying guidance method for beverage intelligent production according to some embodiments of the present application. The conveying guidance method for beverage intelligent production in the above embodiments can be Figure 5 The computer device 500 shown in the figure is implemented, and the computer device 500 includes at least one processor 501, a communication bus 502, a memory 503 and at least one communication interface 504.

[0130] The processor 501 may be a general-purpose central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more processors for controlling the execution of the conveying guidance method for intelligent beverage production in the present application.

[0131] The communication bus 502 may be used to transmit information between the above-mentioned components.

[0132] The memory 503 may be a read only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, or an electrically erasable programmable read only memory (EEPROM), a compact disc read only memory (CD ROM) or other optical disc storage, an optical disc storage (including a compressed optical disc, a laser disc, an optical disc, a digital versatile disc, a Blu-ray disc, etc.), a magnetic disk or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of an instruction or data structure and can be accessed by a computer, but is not limited thereto. The memory 503 may exist independently and be connected to the processor 501 via the communication bus 502. The memory 503 may also be integrated with the processor 501.

[0133] The memory 503 is used to store the program code for executing the solution of the present application, and the execution is controlled by the processor 501. The processor 501 is used to execute the program code stored in the memory 503. The program code may include one or more software modules. The method described in the above method embodiment can be implemented by the processor 501 and one or more software modules in the program code in the memory 503.

[0134] The communication interface 504 uses any transceiver or other device for communicating with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area networks (WLAN), etc.

[0135] In a specific implementation, as an embodiment, a computer device may include multiple processors, each of which may be a single-core (single CPU) processor or a multi-core (multi CPU) processor. The processor here may refer to one or more devices, circuits, and / or processing cores for processing data (such as computer program instructions).

[0136] The above-mentioned computer device may be a general-purpose computer device or a special-purpose computer device. In a specific implementation, the computer device may be a desktop computer, a portable computer, a network server, a personal digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device or an embedded device. The embodiment of the present application does not limit the type of computer device.

[0137] In addition, the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the above-mentioned conveying and guiding method for intelligent beverage production.

[0138] In summary, in the conveying equipment and method for intelligent beverage production disclosed in the embodiment of the present application, firstly, a vibration sensor is set on each conveyor belt to obtain the vibration state information sent by each vibration sensor; the vibration feedback characteristics of each conveyor belt under the corresponding load state are extracted from all the vibration state information; the load offset of each conveyor belt during the guide roller traction process is determined according to the resonance characteristics of each conveyor belt under the corresponding load state and the displacement fluctuation of the beverage cans on the beverage production line during the transportation process, and the vibration suppression amount of each conveyor belt during the guide roller traction process is determined according to all the load offsets and the vibration feedback characteristics of each conveyor belt under the corresponding load state; the guided conveying cost of each conveyor belt under the corresponding load state is determined by all the vibration suppression amounts and the collision margin of the beverage cans on the beverage production line; the hydraulic vibration buffer on each drive device is adaptively adjusted based on all the guided conveying costs. The scheme of the present application can reduce the dynamic load changes that the conveyor belt bears during operation due to vibration, thereby improving the stability of the beverage cans during the transportation process.

[0139] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0140] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A conveying and guiding method for intelligent beverage production, used for controlling the conveying of beverage cans on a beverage production line, wherein the beverage cans are conveyed by a plurality of conveyor belts, each of which comprises a driving device, and a hydraulic vibration buffer is arranged on the driving device, characterized in that: The method comprises the following steps: A vibration sensor is arranged on each conveyor belt to obtain vibration status information sent by each vibration sensor; Extract the vibration feedback characteristics of each conveyor belt under the corresponding load state from all vibration state information; Determine the load offset of each conveyor belt during the traction process of the guide roller according to the resonance characteristics of each conveyor belt under the corresponding load state and the displacement fluctuation of the beverage cans on the beverage production line during the conveying process, and determine the vibration suppression amount of each conveyor belt during the traction process of the guide roller according to all load offsets and the vibration feedback characteristics of each conveyor belt under the corresponding load state; Determine the guiding and conveying cost of each conveyor belt under the corresponding load state by using all vibration suppression quantities and the collision margin of beverage cans on the beverage production line; Adaptive adjustment of the hydraulic vibration dampers on each drive unit based on all guided transport costs; Among them, the vibration feedback characteristics of each conveyor belt under the corresponding load state are extracted from all vibration state information, specifically including: According to different load states, each vibration state information is divided into a light load vibration state information set, a medium load vibration state information set and a heavy load vibration state information set; Clustering the light-load vibration state information set, the medium-load vibration state information set, and the heavy-load vibration state information set respectively, thereby obtaining a plurality of light-load vibration state information clusters, a plurality of medium-load vibration state information clusters, and a plurality of heavy-load vibration state information clusters; Determine the vibration feedback characteristics of each conveyor belt in the light load state according to the vibration gradient in each vibration state information and all light load vibration state information clusters; Determine the vibration feedback characteristics of each conveyor belt under the medium load state through the vibration gradient in each vibration state information and all medium load vibration state information clusters; Determine the vibration feedback characteristics of each conveyor belt under the heavy load state according to the vibration gradient in each vibration state information and all the heavy load vibration state information clusters; The vibration feedback characteristics represent abnormal feedback characteristics when the conveyor belt vibrates unbalanced under different load conditions.

2. The method according to claim 1, characterized in that Determining the load offset of each conveyor belt during the traction process of the guide roller according to the resonance characteristics of each conveyor belt under the corresponding load state and the displacement fluctuation of the beverage cans on the beverage production line during the conveying process specifically includes: Obtain the resonance data of each conveyor belt at different key positions under corresponding load conditions; Extract features from each resonance data to obtain the resonance features of each conveyor belt under different load conditions; Determine the resonance balance amount during the conveying process according to the resonance characteristics of each conveyor belt under different load conditions; Determine the load fluctuation of each conveyor belt based on a preset regression model and the displacement fluctuation of beverage cans on the beverage production line during the conveying process; The load deviation of each conveyor belt during the traction process of the guide roller is determined according to the resonance balancing amount during the conveying process and the load fluctuation amount of each conveyor belt.

3. The method according to claim 1, characterized in that Determining the vibration suppression amount of each conveyor belt during the traction process of the guide roller according to all load offsets and the vibration feedback characteristics of each conveyor belt under the corresponding load state specifically includes: Performing linear fitting on all vibration gradients in each vibration state information to obtain a vibration gradient curve; Determining the vibration overshoot of each conveyor belt according to the vibration gradient curve and the vibration feedback characteristics of each conveyor belt under the corresponding load state; The vibration suppression amount of each conveyor belt during the traction process of the guide roller is determined by the vibration overshoot amount of each conveyor belt and all load offsets.

4. The method according to claim 1, characterized in that The guiding and conveying costs of each conveyor belt under the corresponding load state are determined by all vibration suppression amounts and the collision margin of beverage cans on the beverage production line, including: Obtain collision information of beverage cans on each conveyor belt under different load conditions; Determine the collision margin of beverage cans on the beverage production line based on a preset sliding window and all collision information; Determine the maximum guided collision factor and the minimum guided collision factor through the collision margin of beverage cans on the beverage production line; The guiding and conveying cost of each conveyor belt under the corresponding load state is determined according to the maximum guiding collision factor, the minimum guiding collision factor and all vibration suppression amounts.

5. The method according to claim 1, characterized in that Adaptive adjustment of the hydraulic vibration dampers on each drive unit based on all guided transport costs specifically includes: Determine the following adjustment coefficient according to all the guided transport costs; The hydraulic vibration damper is controlled via the following control factor at the individual drive units.

6. The method according to claim 1, characterized in that The vibration sensor is a piezoelectric vibration sensor.

7. A conveying device for intelligent beverage production, the conveying device adopts the method described in any one of claims 1 to 6 for conveying and guiding, the conveying device comprises a plurality of conveyor belts, each of which comprises a driving device, characterized in that: A vibration sensor is arranged on each conveyor belt, a hydraulic vibration buffer is arranged on the driving device, and the conveying equipment also includes a conveying guide unit, and the conveying guide unit includes: An acquisition module is used to acquire vibration state information sent by each vibration sensor; A processing module, used for extracting vibration feedback characteristics of each conveyor belt under corresponding load state from all vibration state information; The processing module is further used to determine the load offset of each conveyor belt during the traction process of the guide roller according to the resonance characteristics of each conveyor belt under the corresponding load state and the displacement fluctuation of the beverage cans on the beverage production line during the conveying process, and determine the vibration suppression amount of each conveyor belt during the traction process of the guide roller according to all the load offsets and the vibration feedback characteristics of each conveyor belt under the corresponding load state; The processing module is further used to determine the guided conveying cost of each conveyor belt under the corresponding load state through all vibration suppression amounts and the collision margin of beverage cans on the beverage production line; The execution module is used to adaptively adjust the hydraulic vibration damper on each drive device based on all guided conveying costs.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the conveying guidance method for intelligent beverage production according to any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the conveying and guiding method for intelligent beverage production according to any one of claims 1 to 6 is implemented.

Images