An intelligent monitoring system and monitoring method for a probiotic tablet packaging production device

Abstract

The present application provides an intelligent monitoring system and a monitoring method for a probiotic tablet packaging production device, which monitors the surface temperature of the sealing area of each packaging production device; further determines the temperature fluctuation of the sealing area of each packaging production device, further extracts the temperature confidence interval of the sealing area of each packaging production device, performs drift compensation on the temperature confidence interval of the sealing area of each packaging production device according to all the temperature fluctuations, obtains the temperature drift relationship of the sealing area of each packaging production device, and determines the abnormal confidence value of the temperature in the sealing area of each packaging production device during the probiotic tablet packaging process through all the temperature drift relationships and all the temperature change states; generates a cooling instruction for the sealing area of each packaging production device through all the abnormal confidence values, and sends all the cooling adjustment instructions to the monitoring center of the packaging production device. The present application can achieve precise control and adjustment of the temperature of the sealing area of multiple packaging production devices, thereby improving the survival rate of probiotics.

Description

Technical Field

[0001] This application relates to the technical field of program control. More specifically, this application relates to an intelligent monitoring system and monitoring method for probiotic tablet packaging production equipment. Background Art

[0002] In the monitoring of probiotic tablet packaging production equipment, program control technology realizes the automated and intelligent management of the production process by integrating systems such as programmable logic controllers, data acquisition and monitoring control systems, and human-machine interfaces. The programmable logic controller precisely adjusts the pressure, packaging speed, temperature, and humidity of the tablet press according to the set process parameters to ensure that each production link meets the standards. The data acquisition and monitoring control system is responsible for real-time monitoring of production data, collecting the operating status of the equipment, and performing data analysis to ensure the stable operation of the equipment and timely adjustment of production parameters. The human-machine interface provides an intuitive interface for operators to facilitate real-time monitoring of the production process, adjustment, or troubleshooting. In addition, program control technology also has an automatic alarm function. Once a device failure or parameter abnormality occurs, the system will automatically issue an alarm to ensure that production is not affected, thereby improving production efficiency, ensuring the quality stability of probiotic products, and reducing manual intervention.

[0003] In the prior art, the cooling monitoring of traditional packaging production equipment mainly relies on the local temperature control of a single device. Traditional methods usually set independent temperature sensors on each device. When the temperature of the sealing area of the device reaches the preset threshold, the cooling system of the device starts to cool down. The operation of these cooling systems is often isolated, that is, the temperature adjustment of each device only targets itself without considering the coordinated operation with other devices, resulting in a low overall temperature management efficiency of the system. Therefore, how to achieve precise control and adjustment of the temperature of the sealing areas of multiple packaging production devices to improve the survival rate of probiotics has become a difficult problem faced by the industry. Summary of the Invention

[0004] This application provides an intelligent monitoring system and monitoring method for probiotic tablet packaging production equipment, which can achieve precise control and adjustment of the temperature of the sealing areas of multiple packaging production devices, thereby improving the survival rate of probiotics.

[0005] In the first aspect, this application provides an intelligent monitoring method for probiotic tablet packaging production equipment. The intelligent monitoring method includes the following steps:

[0006] Monitor the surface temperature of the sealing areas of each packaging production device on the probiotic tablet production line;

[0007] Determine the temperature fluctuations of the sealing areas of each packaging production device on the probiotic tablet production line, and extract the temperature confidence region of the sealing area of each packaging production device from the surface temperatures of the sealing areas of all packaging production devices;

[0008] Perform drift compensation on the temperature confidence region of the sealing area of each packaging production device according to all temperature fluctuations, and obtain the temperature drift relationship of the sealing area of each packaging production device during the probiotic tablet pressing and packaging process;

[0009] Obtain the temperature change state of the sealing area of each packaging production device, and determine the abnormal confidence value of the temperature in the sealing area of each packaging production device during the probiotic tablet pressing and packaging process through all the temperature drift relationships and all the temperature change states;

[0010] Generate cooling instructions for the sealing area of each packaging production device through all the abnormal confidence values, and send all the cooling adjustment instructions to the monitoring center of the packaging production device.

[0011] In this embodiment, determining the temperature fluctuations of the sealing areas of each packaging production device on the probiotic tablet production line specifically includes:

[0012] Based on the probiotic tablet production process specifications, set the reference temperature of the sealing area of each packaging production device;

[0013] Calculate the fluctuation range of the surface temperature of the sealing area of each packaging production device through the reference temperature of the sealing area of each packaging production device, and obtain the temperature fluctuations of the sealing areas of each packaging production device on the probiotic tablet production line.

[0014] In this embodiment, extracting the temperature confidence region of the sealing area of each packaging production device from the surface temperatures of the sealing areas of all packaging production devices specifically includes:

[0015] Obtain the historical surface temperature data of the sealing area of each packaging production device;

[0016] Extract the temperature trend of the sealing area of each packaging production device from the historical surface temperature data of the sealing area of each packaging production device based on a pre-trained machine learning model;

[0017] Determine the temperature confidence region of each packaging production device according to the temperature trend of the sealing area of each packaging production device and the surface temperature of the sealing area of each packaging production device.

[0018] In this embodiment, performing drift compensation on the temperature confidence region of the sealing area of each packaging production device according to all temperature fluctuations, and obtaining the temperature drift relationship of the sealing area of each packaging production device during the probiotic tablet pressing and packaging process specifically includes:

[0019] Determine the temperature drift amount of the sealing area of each packaging production device through the temperature confidence region of the sealing area of each packaging production device;

[0020] All temperature drifts are compensated to obtain the temperature drift compensation coefficient of the sealing area of ​​each packaging production equipment during the probiotic tablet packaging process;

[0021] The temperature drift relationship of the sealing area of ​​each packaging production equipment during the probiotic tablet packaging process is determined according to the temperature drift compensation coefficient of the sealing area of ​​each packaging production equipment.

[0022] In this embodiment, the abnormal confidence value of the temperature in the sealing area of ​​each packaging production equipment during the probiotic tablet packaging process is determined by all temperature drift relationships and all temperature change states, specifically including:

[0023] Make abnormal judgments on all temperature change states and obtain the abnormal temperature value of the sealing area of ​​each packaging production equipment during the probiotic tablet packaging process;

[0024] The abnormal confidence value of the temperature in the sealing area of ​​each packaging production equipment during the probiotic tablet packaging process is determined based on all temperature abnormal values ​​and all temperature drift relationships.

[0025] In this embodiment, generating a temperature reduction instruction for the sealing area of ​​each packaging production equipment through all abnormal confidence values ​​specifically includes:

[0026] Determine the temperature reduction range of the sealing area of ​​each packaging production equipment based on all abnormal confidence values;

[0027] The temperature reduction instruction of the sealing area of ​​each packaging production equipment is determined by the temperature reduction amplitude of the sealing area of ​​each packaging production equipment and the temperature fluctuation of the sealing area of ​​each packaging production equipment.

[0028] In this embodiment, the packaging production equipment is an automated mechanical equipment for producing packaged probiotic tablets.

[0029] In this embodiment, the sealing area of ​​the packaging production equipment is a key area used for sealing and packaging probiotic tablets during the probiotic tablet packaging production process.

[0030] In this embodiment, an infrared sensor is used to collect the surface temperature of the sealing area of ​​the packaging production equipment.

[0031] In a second aspect, the present application provides an intelligent monitoring system for probiotic tablet packaging production equipment, which is used to perform an intelligent monitoring method for probiotic tablet packaging production equipment. The intelligent monitoring system for probiotic tablet packaging production equipment includes:

[0032] Temperature monitoring module, used to monitor the surface temperature of the sealing area of ​​each packaging production equipment on the probiotic tableting production line;

[0033] The temperature credible domain determination module is used to determine the temperature fluctuation of the sealing area of ​​each packaging production equipment on the probiotic tableting production line, and extract the temperature credible domain of each packaging production equipment sealing area from the surface temperature of all packaging production equipment sealing areas;

[0034] The temperature drift compensation module is used to compensate the temperature trust region of the sealing area of ​​each packaging production equipment according to all temperature fluctuations, and obtain the temperature drift relationship of the sealing area of ​​each packaging production equipment during the probiotic tablet packaging process;

[0035] The temperature abnormality confidence value determination module is used to obtain the temperature change state of the sealing area of ​​each packaging production equipment, and determine the abnormality confidence value of the temperature of the sealing area of ​​each packaging production equipment during the probiotic tablet packaging process through all temperature drift relationships and all temperature change states;

[0036] The instruction sending module is used to generate a cooling instruction for the sealing area of ​​each packaging production equipment through all abnormal confidence values, and send all the cooling adjustment instructions to the monitoring center of the packaging production equipment.

[0037] The technical solution provided by the embodiments disclosed in this application has the following beneficial effects:

[0038] Monitor the surface temperature of the sealing area of ​​each packaging production equipment on the probiotic tableting production line, determine the temperature fluctuation of the sealing area of ​​each packaging production equipment on the probiotic tableting production line, extract the temperature credible domain of the sealing area of ​​each packaging production equipment from the surface temperature of the sealing area of ​​all packaging production equipment, perform drift compensation on the temperature credible domain of the sealing area of ​​each packaging production equipment according to all temperature fluctuations, obtain the temperature drift relationship of the sealing area of ​​each packaging production equipment during the probiotic tableting packaging process, obtain the temperature change state of the sealing area of ​​each packaging production equipment, determine the abnormal confidence value of the temperature of the sealing area of ​​each packaging production equipment during the probiotic tableting packaging process through all temperature drift relationships and all temperature change states, generate cooling instructions for the sealing areas of each packaging production equipment through all abnormal confidence values, and send all cooling adjustment instructions to the monitoring center of the packaging production equipment.

[0039] It can be seen that the present application determines the abnormal confidence value of the temperature of the sealing area of ​​each packaging production equipment during the probiotic tablet packaging process through all temperature drift relationships and all temperature change states, and generates cooling instructions for the sealing areas of each packaging production equipment through all abnormal confidence values; first, the solution can accurately obtain temperature data and judge the temperature fluctuation of each sealing area by real-time monitoring of the surface temperature of the sealing area of ​​each packaging production equipment; next, the technical solution can identify and define the temperature range of each sealing area by extracting the respective temperature trust domains from the temperature data of all sealing areas. In a further step, by drift compensation for all temperature fluctuation data, the temperature drift relationship of each sealing area during the probiotic tablet packaging process can be effectively identified. This compensation not only corrects the temperature error caused by the equipment or external environment, but also ensures that each sealing area The sealing area can be maintained in the optimal operating temperature range throughout the entire packaging process, which is crucial to ensuring the activity of probiotics and the quality of packaging, because probiotics are extremely sensitive to temperature, and too high or too low temperatures may affect their effectiveness and quality; in addition, by further obtaining the temperature change status of the sealing area of ​​each packaging production equipment and analyzing these changes in combination with the temperature drift relationship, the temperature abnormality confidence value of each sealing area is calculated. This process realizes early warning and precise control of temperature abnormalities, avoids the negative impact of excessive temperature fluctuations on the probiotic tablet packaging process, and generates specific cooling instructions through comprehensive analysis of all abnormal confidence values, and sends real-time adjustment information to the monitoring center of the packaging production equipment; in summary, the technical solution effectively realizes the precise management of the temperature of the sealing areas of multiple packaging production equipment through multiple precise control and adjustment steps. The precise calculation and automated control of each step not only improves the temperature control accuracy during the probiotic tablet packaging process and reduces the impact of temperature fluctuations on product quality, but also improves the overall stability of the production line, ensures the quality and activity of probiotic products, and enhances the controllability and intelligence of the packaging process, thereby optimizing the packaging production process, reducing the need for manual intervention, and improving production efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0041] Figure 1 It is a flow chart of the intelligent monitoring method of probiotic tablet packaging production equipment provided by the present application;

[0042] Figure 2is an exemplary flow chart for determining temperature fluctuations according to the present application;

[0043] Figure 3 is an exemplary flow chart for determining a temperature drift relationship according to the present application;

[0044] Figure 4 It is a module structure diagram of the intelligent monitoring system for probiotic tablet packaging production equipment provided by this application. DETAILED DESCRIPTION

[0045] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0046] The embodiment of the present application provides an intelligent monitoring system and monitoring method for probiotic tableting packaging production equipment, the core of which is to monitor the surface temperature of the sealing area of ​​each packaging production equipment on the probiotic tableting production line; determine the temperature fluctuation of the sealing area of ​​each packaging production equipment on the probiotic tableting production line, and extract the temperature credible domain of the sealing area of ​​each packaging production equipment from the surface temperature of the sealing area of ​​all packaging production equipment; drift compensation is performed on the temperature credible domain of the sealing area of ​​each packaging production equipment according to all temperature fluctuations, and the temperature drift relationship of the sealing area of ​​each packaging production equipment during the probiotic tableting packaging process is obtained; the temperature change state of the sealing area of ​​each packaging production equipment is obtained, and the abnormal confidence value of the temperature of the sealing area of ​​each packaging production equipment during the probiotic tableting packaging process is determined through all temperature drift relationships and all temperature change states; and cooling instructions for the sealing areas of each packaging production equipment are generated through all abnormal confidence values, and all cooling adjustment instructions are sent to the monitoring center of the packaging production equipment. The present application can realize the precise control and adjustment of the temperature of the sealing areas of multiple packaging production equipment, thereby improving the survival rate of probiotics.

[0047] Embodiment 1,

[0048] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods. Figure 1 As shown in the figure, this figure is an exemplary flow chart of an intelligent monitoring method for probiotic tablet packaging production equipment according to this embodiment of the present application, and the intelligent monitoring method includes the following steps:

[0049] In step S1, the surface temperature of the sealing area of ​​each packaging production equipment on the probiotic tableting production line is monitored.

[0050] In specific implementation, infrared sensors can be installed on each packaging production equipment of the probiotic tableting production line, and the surface temperature of the sealing area of ​​each packaging production equipment can be collected by the infrared sensors.

[0051] In step S2, the temperature fluctuation of the sealing area of ​​each packaging production equipment on the probiotic tableting production line is determined, and the temperature credible region of each packaging production equipment sealing area is extracted from the surface temperature of the sealing area of ​​all packaging production equipment.

[0052] In this embodiment, reference Figure 2 As shown in FIG. 1 , this figure is an exemplary flow chart for determining temperature fluctuations in an embodiment of the present application. In this embodiment, determining the temperature fluctuations in the sealing area of ​​each packaging production equipment on the probiotic tableting production line can be achieved by using the following steps:

[0053] In step S21, based on the probiotic tableting production process specification, the reference temperature of the sealing area of ​​each packaging production equipment is set;

[0054] In step S22, the fluctuation range of the surface temperature of the sealing area of ​​each packaging production equipment is calculated according to the reference temperature of the sealing area of ​​each packaging production equipment, so as to obtain the temperature fluctuation of the sealing area of ​​each packaging production equipment on the probiotic tableting production line.

[0055] In the specific implementation, first, according to the production process specifications of probiotic tablets, the reference temperature of the sealing area of ​​each packaging production equipment is set. This reference temperature can be set by referring to historical data, production process requirements and equipment design parameters to ensure that it meets the standard operating temperature of the packaging equipment during the production process. Secondly, the surface temperature of the sealing area of ​​each packaging production equipment is collected in real time by infrared sensors; next, the temperature fluctuation range of the sealing area of ​​each device is calculated based on the reference temperature and the real-time collected surface temperature. This can be achieved by calculating the standard deviation of the temperature, the difference between the maximum and minimum values, etc., to ensure that the degree of temperature change can be fully reflected. For example, the temperature fluctuation range of each device is calculated using the standard deviation algorithm. A larger standard deviation indicates a larger fluctuation range, while a smaller standard deviation indicates a smaller temperature change; in addition, the real-time temperature data can be smoothed with the help of a sliding window algorithm to reduce the impact of random fluctuations in a short period of time and obtain a more stable and accurate fluctuation range.

[0056] It should be noted that in this application, by comparing the temperature fluctuations calculated with the set reference temperature, the temperature fluctuations in the sealing area of ​​each packaging production equipment can be monitored in real time to ensure that it is always within the allowable fluctuation range and to ensure temperature stability during the production process.

[0057] In this embodiment, extracting the temperature credible domain of each sealing area of ​​packaging production equipment from the surface temperatures of the sealing areas of all packaging production equipment can be achieved by using the following steps:

[0058] Obtain historical surface temperature data of the sealing area of ​​each packaging production equipment;

[0059] The temperature trend of the sealing area of ​​each packaging production equipment is extracted from the historical surface temperature data of the sealing area of ​​each packaging production equipment based on the pre-trained machine learning model;

[0060] The temperature credible region of the sealing area of ​​each packaging production equipment is determined according to the temperature trend of the sealing area of ​​each packaging production equipment and the surface temperature of the sealing area of ​​each packaging production equipment.

[0061] In the specific implementation, first, obtain the historical surface temperature data of the sealing area of ​​each packaging production equipment, which provides the basis for subsequent analysis; the data needs to ensure that the time range is long enough to reflect the long-term temperature fluctuation pattern and ensure its accuracy and representativeness; secondly, based on the historical surface temperature data, use pre-trained machine learning models (such as LSTM or SVR) to extract the temperature trend of the sealing area of ​​each packaging production equipment. LSTM can capture the time series dependency in the temperature data and learn the law of temperature change over time, while SVR can establish the trend of temperature change through the regression model. Through the training of these models , the temperature trend of each sealing area can be obtained, which represents the expected temperature change pattern under normal working conditions; then, for each sealing area of ​​packaging production equipment, the temperature trend can be predicted in time series by combining the ARIMA model, and its confidence interval can be calculated to determine the credible range of temperature change. The temperature trend can be combined with the surface temperature by using regression analysis (such as multivariate linear regression or SVR), and the credible interval can be further adjusted. The Bayesian inference method is used to update the credible interval according to the historical surface temperature data and the real-time surface temperature, so that the credible interval obtained is used as the temperature credible domain of the sealing area of ​​the packaging production equipment.

[0062] It should be noted that the temperature trust domain in this application refers to the temperature fluctuation range of the sealing area of ​​each packaging production equipment under normal working conditions. Usually, this range is expressed as an upper and lower limit interval. When the current measured temperature exceeds the trust domain, it can be regarded as an abnormality, indicating that the equipment may have a fault or is not working properly.

[0063] In step S3, drift compensation is performed on the temperature credible region of the sealing area of ​​each packaging production equipment according to all temperature fluctuations, so as to obtain the temperature drift relationship of the sealing area of ​​each packaging production equipment during the probiotic tablet packaging process.

[0064] In this embodiment, in this embodiment, reference Figure 3As shown in FIG. 1 , this figure is an exemplary flow chart for determining the temperature drift relationship in an embodiment of the present application. In this embodiment, the temperature credible region of the sealing area of ​​each packaging production equipment is drift compensated according to all temperature fluctuations, and the temperature drift relationship of the sealing area of ​​each packaging production equipment during the probiotic tablet packaging process can be obtained by the following steps:

[0065] In step S31, the temperature drift of each sealing area of ​​the packaging production equipment is determined through the temperature trustworthy region of the sealing area of ​​each packaging production equipment;

[0066] In step S32, a temperature drift compensation coefficient of the sealing area of ​​each packaging production equipment during the probiotic tablet packaging process is determined according to all temperature fluctuations and all temperature drift amounts;

[0067] In step S33, the temperature drift relationship of the sealing area of ​​each packaging production equipment during the probiotic tablet packaging process is determined by the temperature drift compensation coefficient of the sealing area of ​​each packaging production equipment.

[0068] In specific implementation, firstly, the temperature drift refers to the degree of deviation between the actual temperature of the sealing area and its credible domain, which can be achieved by calculating the difference between the surface temperature of the sealing area of ​​the packaging production equipment at each moment and the upper and lower limits of the temperature credible domain. For areas with large temperature fluctuations, the temperature drift can be estimated by calculating the average value or maximum deviation value of the fluctuation; secondly, all temperature fluctuations and all temperature drifts are analyzed by statistical methods such as weighted average method or Kalman filtering, so as to obtain the temperature drift compensation coefficient of the sealing area of ​​each packaging production equipment during the probiotic tablet packaging process. The role of the temperature drift compensation coefficient is to reduce the impact of temperature fluctuations on the actual production process, thereby ensuring the stability of temperature changes; then, the historical surface temperature data of the sealing area of ​​each packaging production equipment is obtained, and the corresponding temperature drift compensation coefficient is used as auxiliary data input, and the temperature drift compensation coefficient is combined with the temperature data at each time point to fit the mathematical model of the temperature drift of the sealing area of ​​the packaging production equipment. Using the fitted model, it is possible to predict how the temperature drift changes under different production conditions, thereby obtaining the temperature drift relationship of the sealing area of ​​each packaging production equipment.

[0069] It should be noted that the temperature drift relationship described in this application refers to the deviation law of the temperature change of the sealing area of ​​the equipment relative to its ideal working temperature or the trusted domain range within a specific time period. This relationship describes the temperature change trend and deviation degree of the equipment over time during the production process, which is usually manifested as a gradual or sudden temperature drift with changes in the external environment or operating conditions.

[0070] In step S4, the temperature change state of the sealing area of ​​each packaging production equipment is obtained, and the abnormal confidence value of the temperature of the sealing area of ​​each packaging production equipment during the probiotic tablet packaging process is determined through all temperature drift relationships and all temperature change states.

[0071] In this embodiment, the temperature change state of the sealing area of ​​each packaging production equipment is obtained, and the abnormal confidence value of the temperature of the sealing area of ​​each packaging production equipment during the probiotic tablet packaging process is determined by all temperature drift relationships and all temperature change states. The following steps can be used:

[0072] Obtain the temperature change status of the sealing area of ​​each packaging production equipment;

[0073] Make abnormal judgments on all temperature change states and obtain the abnormal temperature value of the sealing area of ​​each packaging production equipment during the probiotic tablet packaging process;

[0074] The abnormal confidence value of the temperature in the sealing area of ​​each packaging production equipment during the probiotic tablet packaging process is determined based on all temperature abnormal values ​​and all temperature drift relationships.

[0075] In the specific implementation, first, the surface temperature of the sealing area of ​​each packaging production equipment can be obtained in real time, and its rate of change and fluctuation range over time can be calculated. The temperature change state is defined as the change characteristics of the temperature of the sealing area of ​​the packaging production equipment within a certain time range; secondly, the mean and standard deviation of the surface temperature of the sealing area of ​​each packaging production equipment are calculated, and the Z-score method is used to determine whether the temperature change exceeds the set threshold. The Z-score value exceeds 3, which is abnormal. At the same time, the IQR method is used to calculate the quartile of the temperature change, and the temperature fluctuation exceeds 1.5 times the IQR range, so as to obtain the temperature abnormality value of each packaging production equipment sealing area during the probiotic tablet packaging process; then, the temperature abnormality value of each packaging production equipment sealing area is regarded as the observed data, and the temperature drift relationship is used as the prior information. The Bayesian theorem is used to calculate the temperature abnormality confidence of each packaging production equipment sealing area. The specific method is to jointly model the probability distribution of the temperature abnormality value and the temperature drift relationship, and obtain the abnormal confidence value of the temperature of each packaging production equipment sealing area during the probiotic tablet packaging process by calculating the posterior probability.

[0076] It should be noted that the abnormal confidence value of temperature in this application is an indicator to measure the credibility of the temperature change in the sealing area of ​​the packaging production equipment beyond the normal fluctuation range.

[0077] In step S5, a temperature reduction instruction for the sealing area of ​​each packaging production equipment is generated according to all abnormal confidence values, and all temperature reduction adjustment instructions are sent to the monitoring center of the packaging production equipment.

[0078] In this embodiment, the following steps can be used to generate the temperature reduction instructions for the sealing areas of each packaging production equipment through all abnormal confidence values:

[0079] Determine the temperature reduction range of the sealing area of ​​each packaging production equipment based on all abnormal confidence values;

[0080] The temperature reduction instruction of the sealing area of ​​each packaging production equipment is determined by the temperature reduction amplitude of the sealing area of ​​each packaging production equipment and the temperature fluctuation of the sealing area of ​​each packaging production equipment.

[0081] In the specific implementation, first, all abnormal confidence values ​​are mapped to the input variables of the fuzzy control system, and different abnormal confidence levels (such as slight abnormality, moderate abnormality, and severe abnormality) are defined. The fuzzy rule base is used to define the corresponding temperature reduction amplitude according to the different levels of abnormal confidence values. Specifically, when the abnormal confidence value is high, the system automatically increases the temperature reduction amplitude; when the abnormal confidence value is low, the temperature reduction amplitude is reduced, and the temperature reduction amplitude of the sealing area of ​​each packaging production equipment is calculated through the fuzzy inference engine; secondly, based on the PID control algorithm, all temperature reduction amplitudes and temperature fluctuations are used to calculate the temperature fluctuation error of the sealing area of ​​each packaging production equipment. All temperature reduction amplitudes and temperature fluctuations are used as data input, and the temperature reduction instruction is calculated through the three parts of the PID control algorithm: the proportional (P) term adjusts the current temperature reduction amount according to the current temperature error, the integral (I) term corrects the long-term deviation by accumulating the past temperature fluctuation errors, and the differential (D) term predicts the temperature change trend and adjusts the temperature reduction response. Through the output of the PID controller, the temperature reduction instruction of each packaging production equipment sealing area is adjusted in real time.

[0082] In specific implementation, all cooling adjustment instructions are sent to the monitoring center of the packaging production equipment, that is, the calculated cooling adjustment instructions are summarized and sent to the monitoring center of the packaging production equipment through a reliable communication protocol (such as Modbus or MQTT). The monitoring center verifies and distributes the instructions. The equipment adjusts the cooling system according to the instructions, and provides real-time feedback on temperature changes to ensure stable temperature control.

[0083] Embodiment 2:

[0084] This application provides an intelligent monitoring system for probiotic tablet packaging production equipment, referring to Figure 4 As shown, this figure is a schematic diagram of the intelligent monitoring system of the probiotic tablet packaging production equipment shown in this embodiment of the present application, and the intelligent monitoring system of the probiotic tablet packaging production equipment includes:

[0085] The temperature monitoring module 100 is used to monitor the surface temperature of the sealing area of ​​each packaging production equipment on the probiotic tableting production line;

[0086] The temperature credible domain determination module 200 is used to determine the temperature fluctuation of the sealing area of ​​each packaging production equipment on the probiotic tableting production line, and extract the temperature credible domain of each packaging production equipment sealing area from the surface temperature of all packaging production equipment sealing areas;

[0087] The temperature drift compensation module 300 is used to compensate the temperature trust region of the sealing area of ​​each packaging production equipment according to all temperature fluctuations, and obtain the temperature drift relationship of the sealing area of ​​each packaging production equipment during the probiotic tablet packaging process;

[0088] The temperature abnormality confidence value determination module 400 is used to obtain the temperature change state of the sealing area of ​​each packaging production equipment, and determine the abnormality confidence value of the temperature of the sealing area of ​​each packaging production equipment during the probiotic tablet packaging process through all temperature drift relationships and all temperature change states;

[0089] The instruction sending module 500 is used to generate a temperature reduction instruction for the sealing area of ​​each packaging production equipment according to all abnormal confidence values, and send all the temperature reduction adjustment instructions to the monitoring center of the packaging production equipment.

[0090] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0091] A person skilled in the art may understand that all or part of the steps in the various methods of the above embodiments may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, the storage medium including a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically-erasable programmable read-only memory (EEPROM), a compact disc (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0092] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

Claims

1. An intelligent monitoring method for probiotic tablet packaging production equipment, characterized in that: The intelligent monitoring method comprises the following steps: Monitor the surface temperature of the sealing area of ​​each packaging production equipment on the probiotic tableting production line; Determine the temperature fluctuations in the sealing areas of each packaging production equipment on the probiotic tableting production line, and extract the temperature trustworthy region of each packaging production equipment sealing area from the surface temperatures of all packaging production equipment sealing areas; According to all temperature fluctuations, drift compensation is performed on the temperature trustworthy region of the sealing area of ​​each packaging production equipment to obtain the temperature drift relationship of the sealing area of ​​each packaging production equipment during the probiotic tablet packaging process; Obtain the temperature change state of the sealing area of ​​each packaging production equipment, and determine the abnormal confidence value of the temperature of the sealing area of ​​each packaging production equipment during the probiotic tablet packaging process through all temperature drift relationships and all temperature change states; Generate cooling instructions for the sealing area of ​​each packaging production equipment through all abnormal confidence values, and send all cooling adjustment instructions to the monitoring center of the packaging production equipment; The temperature trustworthy domain of each packaging production equipment sealing area is extracted from the surface temperature of the sealing area of ​​all packaging production equipment, including: Obtain historical surface temperature data of the sealing area of ​​each packaging production equipment; The temperature trend of the sealing area of ​​each packaging production equipment is extracted from the historical surface temperature data of the sealing area of ​​each packaging production equipment based on the pre-trained machine learning model; The temperature credible region of the sealing area of ​​each packaging production equipment is determined according to the temperature trend of the sealing area of ​​each packaging production equipment and the surface temperature of the sealing area of ​​each packaging production equipment.

2. The intelligent monitoring method for probiotic tablet packaging production equipment according to claim 1, characterized in that: Determine the temperature fluctuations in the sealing area of ​​each packaging production equipment on the probiotic tableting production line, including: Based on the probiotic tableting production process specifications, set the reference temperature of the sealing area of ​​each packaging production equipment; The fluctuation range of the surface temperature of the sealing area of ​​each packaging production equipment is calculated based on the reference temperature of the sealing area of ​​each packaging production equipment, and the temperature fluctuation of the sealing area of ​​each packaging production equipment on the probiotic tableting production line is obtained.

3. The intelligent monitoring method for probiotic tablet packaging production equipment according to claim 1, characterized in that: According to all temperature fluctuations, the temperature trust region of the sealing area of ​​each packaging production equipment is drift compensated, and the temperature drift relationship of the sealing area of ​​each packaging production equipment during the probiotic tablet packaging process is obtained, which specifically includes: Determine the temperature drift of each sealing area of ​​packaging production equipment through the temperature trust region of each sealing area of ​​packaging production equipment; All temperature drifts are compensated to obtain the temperature drift compensation coefficient of the sealing area of ​​each packaging production equipment during the probiotic tablet packaging process; The temperature drift relationship of the sealing area of ​​each packaging production equipment during the probiotic tablet packaging process is determined according to the temperature drift compensation coefficient of the sealing area of ​​each packaging production equipment.

4. The intelligent monitoring method for probiotic tablet packaging production equipment according to claim 1, characterized in that: The abnormal confidence values ​​of the temperature in the sealing area of ​​each packaging production equipment during the probiotic tablet packaging process are determined through all temperature drift relationships and all temperature change states, including: Make abnormal judgments on all temperature change states and obtain the abnormal temperature value of the sealing area of ​​each packaging production equipment during the probiotic tablet packaging process; The abnormal confidence value of the temperature in the sealing area of ​​each packaging production equipment during the probiotic tablet packaging process is determined based on all temperature abnormal values ​​and all temperature drift relationships.

5. The intelligent monitoring method for probiotic tablet packaging production equipment according to claim 1, characterized in that: The cooling instructions for the sealing area of ​​each packaging production equipment are generated through all abnormal confidence values, including: Determine the temperature reduction range of the sealing area of ​​each packaging production equipment based on all abnormal confidence values; The temperature reduction instruction of the sealing area of ​​each packaging production equipment is determined by the temperature reduction amplitude of the sealing area of ​​each packaging production equipment and the temperature fluctuation of the sealing area of ​​each packaging production equipment.

6. The intelligent monitoring method for probiotic tablet packaging production equipment according to claim 1, characterized in that: The packaging production equipment is an automated mechanical equipment for producing and packaging probiotic tablets.

7. The intelligent monitoring method for probiotic tablet packaging production equipment according to claim 1, characterized in that: The sealing area of ​​the packaging production equipment is a key area used for sealing and packaging probiotic tablets during the probiotic tablet packaging production process.

8. The intelligent monitoring method for probiotic tablet packaging production equipment according to claim 1, characterized in that: Use infrared sensors to collect surface temperatures in the sealing area of ​​packaging production equipment.

9. An intelligent monitoring system for probiotic tablet packaging production equipment, used to execute an intelligent monitoring method for probiotic tablet packaging production equipment according to any one of claims 1 to 8, characterized in that: The probiotic tablet packaging production equipment intelligent monitoring system comprises: Temperature monitoring module, used to monitor the surface temperature of the sealing area of ​​each packaging production equipment on the probiotic tableting production line; The temperature credible domain determination module is used to determine the temperature fluctuation of the sealing area of ​​each packaging production equipment on the probiotic tableting production line, and extract the temperature credible domain of each packaging production equipment sealing area from the surface temperature of all packaging production equipment sealing areas; The temperature drift compensation module is used to compensate the temperature trust region of the sealing area of ​​each packaging production equipment according to all temperature fluctuations, and obtain the temperature drift relationship of the sealing area of ​​each packaging production equipment during the probiotic tablet packaging process; The temperature abnormality confidence value determination module is used to obtain the temperature change state of the sealing area of ​​each packaging production equipment, and determine the abnormality confidence value of the temperature of the sealing area of ​​each packaging production equipment during the probiotic tablet packaging process through all temperature drift relationships and all temperature change states; The instruction sending module is used to generate a cooling instruction for the sealing area of ​​each packaging production equipment through all abnormal confidence values, and send all the cooling adjustment instructions to the monitoring center of the packaging production equipment.

Images