A monitoring and early warning system for the production process of four-corner cartons

Abstract

The present invention provides a monitoring and early warning system for a four-corner carton production process, belonging to the technical field of process monitoring; the system comprises: a monitoring module: monitoring the key environmental parameters of a four-corner carton production workshop, and performing partition matching on the key environmental parameters of the workshop according to the division rules of the workshop responsibility area; a data acquisition module: real-time monitoring of the carton production parameters of each partition workshop, and extracting characteristic parameters from the carton production parameters according to the work responsibilities of the partition workshop, and obtaining the safety index of the partition workshop according to the characteristic parameters and the preset standard safety parameters; an abnormal index partition module: judging the actual abnormal process of the corresponding partition workshop according to the matching environmental parameters and the corresponding safety indicators in combination with the safety evaluation model; an early warning module: outputting a safety early warning signal for the production process according to the actual abnormal process of different partition workshops. The production efficiency is improved, and the accuracy of the monitoring and early warning results is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of process monitoring technology, and in particular to a monitoring and early warning system for a four-corner carton production process. Background Art

[0002] At present, with the continuous development of sensor technology and big data technology, they are widely used in various production lines. Taking the four-corner carton production line as an example, in the actual production of the four-corner carton, the general settings of the monitoring equipment for the manufacturing process will be carried out in advance. However, due to the complex process of the production workshop, the general settings will lead to incomplete or inaccurate analysis data collection, and finally the abnormal warning cannot be accurately located.

[0003] Therefore, the present invention proposes a monitoring and early warning system for the production process of four-corner cartons. Summary of the invention

[0004] The present invention provides a monitoring and early warning system for the production process of four-corner cartons, which is used to divide the workshop into zones according to the workshop process responsibilities, and judge abnormal situations in combination with the collection results of the zone sensors, and output a safety early warning signal warning, thereby realizing effective monitoring and early warning of the four-corner carton production process, improving production efficiency, and ensuring the accuracy of the monitoring and early warning results.

[0005] On the one hand, the present invention provides a monitoring and early warning system for a four-corner carton production process, comprising:

[0006] Monitoring module: monitors the key environmental parameters of the four-corner carton production workshop, and divides and matches the key environmental parameters of the workshop according to the division rules of the workshop responsibility areas;

[0007] Data acquisition module: monitors the carton production parameters of each partition workshop in real time, extracts characteristic parameters from the carton production parameters according to the work responsibilities of the partition workshop, and then obtains the safety index of the partition workshop according to the characteristic parameters and preset standard safety parameters;

[0008] Index abnormality partition module: according to the matching environmental parameters and corresponding safety indicators of the partitioned workshop, combined with the safety evaluation model, the actual abnormal process of the corresponding partitioned workshop in making four-corner cartons is judged;

[0009] Early warning module: outputs safety early warning signals for the production process of four-corner cartons based on the actual abnormal process conditions in different partition workshops.

[0010] On the other hand, it also includes:

[0011] Sensor determination module: determines the type and quantity of sensors to be configured based on the preset key environmental parameter monitoring requirements of the workshop;

[0012] Sensor installation module: According to the sensor's user manual, determine the specific installation requirements for different types of sensors and complete the installation.

[0013] On the other hand, the monitoring module comprises:

[0014] Workshop division unit: divide the work responsibility area of ​​the four-corner carton making workshop into zones according to the division rules of the workshop responsibility area;

[0015] Parameter matching unit: Based on the key environmental parameters obtained by the workshop sensors and combined with the sensors set up in each partition workshop, the matching environmental parameters of the partition workshop are obtained.

[0016] On the other hand, the data acquisition module includes:

[0017] Feature parameter unit: obtains real-time carton production parameters based on sensors in partitioned workshops and constructs carton production parameter matrix A:

[0018] ;

[0019] in, represents the parameter value of the i-th parameter at the j-th monitoring time, ;

[0020] According to the covariance matrix of the production parameter matrix A Get the feature vector B:

[0021] ;

[0022] in, Represents the eigenvector corresponding to the i-th parameter;

[0023] Determine the characteristic parameters of different carton production parameters based on the characteristic vector B:

[0024] ;

[0025] in, represents the characteristic parameter of the i-th parameter, represents the parameter value of the i-th parameter at the j-th monitoring time, represents the mean of the row vector corresponding to the i-th parameter, represents the maximum parameter value in the row vector corresponding to the i-th parameter, represents the minimum parameter value in the row vector corresponding to the i-th parameter, Represents the average value of the eigenvector of the i-th parameter after modulo calculation.

[0026] On the other hand, the data acquisition module further includes:

[0027] Safety index unit: according to the production safety manual and safety standards of the partition workshop, set the preset safety parameter range for the i-th parameter in the partition workshop ;

[0028] Determine the safety index value of the i-th parameter:

[0029] ;

[0030] in, represents the safety index value of the i-th parameter, represents the r monitoring times of the i-th parameter in the historical time period, represents the preset safety weight coefficient of the i-th parameter, represents logarithmic operation, represents the parameter value of the i-th parameter at the g1-th monitoring time, represents the characteristic parameter of the i-th parameter, Indicates the far end value of the preset safety parameter range of the i-th parameter, represents the near-end value of the preset safety parameter range of the i-th parameter, represents the preset error constant of the i-th parameter;

[0031] The safety index of the partitioned workshop is comprehensively obtained based on the safety index values ​​of all parameters involved in the corresponding partitioned workshop.

[0032] On the other hand, the indicator abnormality partitioning module includes:

[0033] A weight adjustment unit: adjusting a preset safety weight coefficient of each parameter in the partitioned workshop;

[0034] ;

[0035] in, represents the weight adjustment coefficient of the safety index of the i-th parameter, Represents the total number of valid parameters in the corresponding row vector of the i-th parameter, Represents the activation function, and x represents the total number of all valid parameters in the carton production parameter matrix A.

[0036] On the other hand, the indicator abnormality partitioning module includes:

[0037] Safety evaluation unit: construct the safety evaluation model of the partitioned workshop:

[0038] ;

[0039] in, represents the coefficient of variation of the actual effective parameters in the partition workshop, represents the actual parameter screening rate in the partition workshop, Indicates the proportion of preset effective parameters in the partitioned workshop, represents the error coefficient in the partitioned workshop, represents the logarithmic function with base 2;

[0040] Based on the actual effective parameter proportion G and combined with the weight adjustment coefficient, the overall safety evaluation value D of the corresponding partition workshop is determined:

[0041] ;

[0042] in, represents the overall safety evaluation value of the partitioned workshop, represents the preset weight coefficient of the i-th parameter;

[0043] when , the safety evaluation warning level is judged to be zero, where L represents the number of partitioned workshops; represents the overall safety evaluation value of the h-th partition workshop;

[0044] when , the safety assessment warning level is judged to be level one;

[0045] when , the safety assessment warning level is judged to be level 2;

[0046] According to the warning level and in combination with the abnormal parameter conditions of the partitioned workshop, the actual abnormal process conditions of the partitioned workshop are obtained.

[0047] On the other hand, the early warning module includes:

[0048] Early warning unit: When the safety evaluation early warning level is zero, there is no abnormality in the current partition workshop;

[0049] When the safety evaluation warning level is level one, a general alarm is issued to the partition workshop, and a warning signal is issued to check for abnormal parameters of the partition workshop;

[0050] When the safety assessment warning level is level 2, the partition workshop issues an emergency warning and sends a warning signal to suspend the production process;

[0051] Signal warning unit: It integrates the actual abnormal process conditions corresponding to different partition workshops and the related warning signals, and outputs safety warning signals for the carton production process.

[0052] The present invention provides a monitoring and early warning system for the production process of four-corner cartons, which is used to divide the workshop into zones according to the workshop process responsibilities, and judge abnormal situations in combination with the collection results of the zone sensors, and output a safety early warning signal warning, thereby realizing effective monitoring and early warning of the four-corner carton production process, improving production efficiency, and ensuring the accuracy of the monitoring and early warning results. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0054] Figure 1 It is a structural schematic diagram of a monitoring and early warning system for a four-corner carton production process provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0056] Embodiment 1:

[0057] like Figure 1 As shown, a monitoring and early warning system for a four-corner carton production process provided by an embodiment of the present invention includes:

[0058] Monitoring module: monitors the key environmental parameters of the four-corner carton production workshop, and divides and matches the key environmental parameters of the workshop according to the division rules of the workshop responsibility areas;

[0059] Data acquisition module: monitors the carton production parameters of each partition workshop in real time, extracts characteristic parameters from the carton production parameters according to the work responsibilities of the partition workshop, and then obtains the safety index of the partition workshop according to the characteristic parameters and preset standard safety parameters;

[0060] Index abnormality partition module: according to the matching environmental parameters and corresponding safety indicators of the partitioned workshop, combined with the safety evaluation model, the actual abnormal process of the corresponding partitioned workshop in making four-corner cartons is judged;

[0061] Early warning module: outputs safety early warning signals for the production process of four-corner cartons based on the actual abnormal process conditions in different partition workshops.

[0062] In this embodiment, the four-corner carton is a carton with four right angles, also known as a square carton.

[0063] In this embodiment, the production workshop refers to a workplace area specifically used for the production and manufacturing of four-corner cartons, including equipment, staff, and related process environment.

[0064] In this embodiment, the key environmental parameters are some important parameters for the environmental status and conditions of the production workshop, including temperature, humidity, air quality, light, etc., as shown in Table 1.

[0065] Table 1 Key environmental parameters

[0066]

[0067] In this embodiment, the responsibility area refers to dividing the production workshop into different areas, each area is responsible for specific work responsibilities and tasks, including: planning according to factors such as production process, equipment layout, and work responsibilities.

[0068] In this embodiment, the division rule is to divide the entire production workshop into different areas according to factors such as the internal layout of the workshop, production process and division of responsibilities. The areas include: raw material area, production area, testing area, etc.

[0069] In this embodiment, the carton production parameters are real-time monitoring parameters of each production link of making four-corner cartons, including: raw material parameters, equipment parameters, environmental parameters, etc.

[0070] In this embodiment, the work responsibilities are specific duties and tasks for different areas of the workshop for making four-corner cartons.

[0071] In this embodiment, the characteristic parameters are representative parameters extracted from the carton production parameters, such as temperature, humidity, pressure, operating speed, energy consumption and other parameters of the partitioned workshop, as shown in Table 2.

[0072] Table 2 Characteristic parameters

[0073]

[0074] In this embodiment, the preset standard safety parameters refer to the safety index standards set during the production process of making four-corner cartons, including: air quality, noise level, temperature, humidity, etc.

[0075] In this embodiment, the safety index is a parameter used to determine whether the production process of the four-corner carton meets the safety standards, including: air quality, pressure, temperature, humidity, etc.

[0076] In this embodiment, the matching environmental parameters refer to the key parameters of the matching environment in different responsibility areas in the four-corner carton production workshop, including temperature, humidity, air quality, light, etc.

[0077] In this embodiment, the safety evaluation model is a mathematical model used to evaluate, predict and judge the safety of the production system of four-corner cartons.

[0078] In this embodiment, the actual abnormal process situation refers to the abnormalities that occur in the production process of the four-corner carton production workshop, including: abnormal environmental parameters, abnormal production parameters, abnormal safety indicators, etc.

[0079] In this embodiment, the safety warning signal is an alarm signal generated when an abnormal situation is detected in the four-corner carton production workshop.

[0080] The working principle and beneficial effects of the above technical solution are: through real-time monitoring of the workshop environment and production parameters, combined with abnormal analysis and early warning modules, it is possible to complete the refined management and safety early warning of the four-corner carton production process, realize effective monitoring and early warning of the four-corner carton production process, improve production efficiency, and ensure the accuracy of monitoring and early warning results.

[0081] Embodiment 2:

[0082] Based on the above embodiment 1, it also includes:

[0083] Sensor determination module: determines the type and quantity of sensors to be configured based on the preset key environmental parameter monitoring requirements of the workshop;

[0084] Sensor installation module: According to the sensor's user manual, determine the specific installation requirements for different types of sensors and complete the installation.

[0085] In this embodiment, the preset environmental key parameter monitoring requirement refers to the need to monitor the key environmental parameters of the four-corner carton production workshop, such as temperature, humidity, gas concentration, etc., to ensure that the production process is carried out in a suitable environment, as shown in Table 3.

[0086] Table 3 Key parameters of the preset environment

[0087]

[0088] In this embodiment, the user manual provides detailed instructions to help users better use the sensor, including basic parameters of the sensor, usage methods, installation requirements, precautions and other information.

[0089] In this embodiment, the specific installation requirements include the installation position, installation height, installation angle, fixing method, wiring method, etc. of the sensor.

[0090] The working principle and beneficial effects of the above technical solution are: by configuring different types of sensors to monitor the workshop environmental parameters in real time, refined management and safety warning can be achieved, and a data basis can be provided for the effective monitoring and early warning of the four-corner carton production process, finally helping to improve production efficiency and ensure the accuracy of monitoring and early warning results.

[0091] Embodiment 3:

[0092] Based on the above embodiment 2, the monitoring module includes:

[0093] Workshop division unit: divide the work responsibility area of ​​the four-corner carton making workshop into zones according to the division rules of the workshop responsibility area;

[0094] Parameter matching unit: Based on the key environmental parameters obtained by the workshop sensors and combined with the sensors set up in each partition workshop, the matching environmental parameters of the partition workshop are obtained.

[0095] The working principle and beneficial effects of the above technical solution are: through the division of workshop responsibility areas and sensor parameter matching, it provides a data basis for the effective monitoring and early warning of the four-corner carton production process, and finally helps to improve production efficiency and ensure the accuracy of monitoring and early warning results.

[0096] Embodiment 4:

[0097] Based on the above embodiment 1, the data acquisition module includes:

[0098] Feature parameter unit: obtains real-time carton production parameters based on sensors in partitioned workshops and constructs carton production parameter matrix A:

[0099] ;

[0100] in, represents the parameter value of the i-th parameter at the j-th monitoring time, ;

[0101] According to the covariance matrix of the production parameter matrix A Get the feature vector B:

[0102] ;

[0103] in, Represents the eigenvector corresponding to the i-th parameter;

[0104] Determine the characteristic parameters of different carton production parameters based on the characteristic vector B:

[0105] ;

[0106] in, represents the characteristic parameter of the i-th parameter, represents the parameter value of the i-th parameter at the j-th monitoring time, represents the mean of the row vector corresponding to the i-th parameter, represents the maximum parameter value in the row vector corresponding to the i-th parameter, represents the minimum parameter value in the row vector corresponding to the i-th parameter, Represents the average value of the eigenvector of the i-th parameter after modulo calculation.

[0107] In this embodiment, the carton production parameter matrix is ​​a matrix with m rows and n columns, where m represents the number of monitoring parameters and n represents the number of monitoring times. Each row is the value of a monitoring parameter at different times, and each column is a monitoring time point.

[0108] In this embodiment, the monitoring time refers to the time point at which various key parameters are periodically monitored and recorded during the carton production process.

[0109] In this embodiment, the eigenvector refers to a set of vectors obtained by performing eigenvalue decomposition on the carton production parameter matrix.

[0110] In this embodiment, the characteristic parameters refer to a set of statistical indicators obtained by extracting and calculating characteristic vectors and used to describe important characteristics of different parameters in the carton production process.

[0111] In this embodiment, the modular calculation is to perform modular calculation on the feature vector.

[0112] The working principle and beneficial effects of the above technical solution are: obtaining carton production parameters through sensors, constructing parameter matrices and calculating eigenvectors, extracting statistical information of key characteristic parameters, providing a data basis for effective monitoring and early warning of the four-corner carton production process, and finally helping to improve production efficiency and ensure the accuracy of monitoring and early warning results.

[0113] Embodiment 5:

[0114] Based on the above embodiment 4, the data acquisition module further includes:

[0115] Safety index unit: according to the production safety manual and safety standards of the partition workshop, set the preset safety parameter range for the i-th parameter in the partition workshop ;

[0116] Determine the safety index value of the i-th parameter:

[0117] ;

[0118] in, represents the safety index value of the i-th parameter, represents the r monitoring times of the i-th parameter in the historical time period, represents the preset safety weight coefficient of the i-th parameter, represents logarithmic operation, represents the parameter value of the i-th parameter at the g1-th monitoring time, represents the characteristic parameter of the i-th parameter, Indicates the far end value of the preset safety parameter range of the i-th parameter, represents the near-end value of the preset safety parameter range of the i-th parameter, represents the preset error constant of the i-th parameter;

[0119] The safety index of the partitioned workshop is comprehensively obtained based on the safety index values ​​of all parameters involved in the corresponding partitioned workshop.

[0120] In this embodiment, the production safety manual is a manual that describes the safety regulations, operating procedures, emergency measures, etc. of the workshop.

[0121] In this embodiment, safety standards refer to a series of specifications, requirements and standards formulated to ensure the safety of the workplace, production processes and products, including regulations on production equipment, process flow, material control, working environment, etc.

[0122] In this embodiment, the preset safety parameter range is a range limit set for parameters in a partitioned workshop according to safety standards and a production safety manual.

[0123] In this embodiment, the safety index value is a safety level measurement value for parameters in the partitioned workshop.

[0124] In this embodiment, the preset safety weight coefficient is a parameter used to quantitatively evaluate the safety importance of a parameter.

[0125] The working principle and beneficial effects of the above technical solution are: by monitoring and evaluating the parameters of the production workshop, the safety index value is comprehensively calculated, and the effective monitoring and early warning of the four-corner carton production process is achieved, thereby improving production efficiency and ensuring the accuracy of the monitoring and early warning results.

[0126] Embodiment 6:

[0127] Based on the above embodiment 5, the indicator abnormality partitioning module includes:

[0128] A weight adjustment unit: adjusting a preset safety weight coefficient of each parameter in the partitioned workshop;

[0129] ;

[0130] in, represents the weight adjustment coefficient of the safety index of the i-th parameter, Represents the total number of valid parameters in the corresponding row vector of the i-th parameter, Represents the activation function, and x represents the total number of all valid parameters in the carton production parameter matrix A.

[0131] In this embodiment, the weight adjustment coefficient is calculated based on the number and proportion of valid parameters, and adjusts the impact of each parameter on the safety index in the overall weight distribution.

[0132] In this embodiment, the effective parameters are parameters with reasonable values ​​in the carton production parameter matrix A.

[0133] In this embodiment, the activation function is used to calculate the adjustment function for the ratio of the total number x of valid parameters to the total number N of valid parameters in the corresponding row vector of the i-th parameter.

[0134] The working principle and beneficial effects of the above technical solution are: by dynamically adjusting parameter weights and using activation functions to optimize safety indicators, effective monitoring and early warning of the four-corner carton production process can be achieved, production efficiency is improved, and the accuracy of monitoring and early warning results is ensured.

[0135] Embodiment 7:

[0136] Based on the above embodiment 6, the indicator abnormality partitioning module includes:

[0137] Safety evaluation unit: construct the safety evaluation model of the partitioned workshop:

[0138] ;

[0139] in, represents the coefficient of variation of the actual effective parameters in the partition workshop, represents the actual parameter screening rate in the partition workshop, Indicates the proportion of preset effective parameters in the partitioned workshop, represents the error coefficient in the partitioned workshop, represents the logarithmic function with base 2;

[0140] Based on the actual effective parameter proportion G and combined with the weight adjustment coefficient, the overall safety evaluation value D of the corresponding partition workshop is determined:

[0141] ;

[0142] in, represents the overall safety evaluation value of the partitioned workshop, represents the preset weight coefficient of the i-th parameter;

[0143] when , the safety evaluation warning level is judged to be zero, where L represents the number of partitioned workshops; represents the overall safety evaluation value of the h-th partition workshop;

[0144] when , the safety assessment warning level is judged to be level one;

[0145] when , the safety assessment warning level is judged to be level 2;

[0146] According to the warning level and in combination with the abnormal parameter conditions of the partitioned workshop, the actual abnormal process conditions of the partitioned workshop are obtained.

[0147] In this embodiment, the safety evaluation model is a comprehensive evaluation model based on the actual effective parameter proportions and weight adjustment coefficients of the partitioned workshops.

[0148] In this embodiment, the coefficient of variation is an indicator for measuring the variation range of the actual effective parameters in the partitioned workshop.

[0149] In this embodiment, the actual parameter screening rate refers to the ratio of effective parameters in the partitioned workshop.

[0150] In this embodiment, the error coefficient is used to represent the error constant in the parameter evaluation process in the partition workshop.

[0151] In this embodiment, the overall safety evaluation value is used to represent an indicator for evaluating the overall safety status of the partitioned workshop.

[0152] The working principle and beneficial effects of the above technical solution are: by calculating the overall safety evaluation value based on parameter changes, screening rate, etc., judging the warning level and analyzing abnormal situations, effective monitoring and early warning of the four-corner carton production process can be achieved, thereby improving production efficiency and ensuring the accuracy of monitoring and early warning results.

[0153] Embodiment 8:

[0154] Based on the above embodiment 7, the early warning module includes:

[0155] Early warning unit: When the safety evaluation early warning level is zero, there is no abnormality in the current partition workshop;

[0156] When the safety evaluation warning level is level one, a general alarm is issued to the partition workshop, and a warning signal is issued to check for abnormal parameters of the partition workshop;

[0157] When the safety assessment warning level is level 2, the partition workshop issues an emergency warning and sends a warning signal to suspend the production process;

[0158] Signal warning unit: It integrates the actual abnormal process conditions corresponding to different partition workshops and the related warning signals, and outputs safety warning signals for the carton production process.

[0159] In this embodiment, the general alarm is an early warning signal issued for abnormal conditions of parameters in the partition workshop, prompting the management personnel to check the abnormal conditions in the partition workshop.

[0160] In this embodiment, the early warning signal refers to a warning signal issued according to the rating result in the safety evaluation, which reminds the management personnel to pay attention to the abnormal situation of the partition workshop.

[0161] In this embodiment, the emergency warning is the highest level warning signal in the safety evaluation, indicating that a serious abnormal situation exists in the partition workshop and immediate measures need to be taken to ensure the safety of personnel and equipment.

[0162] The working principle and beneficial effects of the above technical solution are: through the early warning unit, different degrees of early warning are given to the safety evaluation level, and the signal early warning unit comprehensively partitions the workshop information to output safety early warning signals, so as to realize effective monitoring and early warning of the four-corner carton production process, improve production efficiency, and ensure the accuracy of monitoring and early warning results.

[0163] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A monitoring and early warning system for the production process of four-corner cartons, characterized in that: include: Monitoring module: monitors the key environmental parameters of the four-corner carton production workshop, and divides and matches the key environmental parameters of the workshop according to the division rules of the workshop responsibility areas; Data acquisition module: monitors the carton production parameters of each partition workshop in real time, extracts characteristic parameters from the carton production parameters according to the work responsibilities of the partition workshop, and then obtains the safety index of the partition workshop according to the characteristic parameters and preset standard safety parameters; Index abnormality partition module: according to the matching environmental parameters and corresponding safety indicators of the partitioned workshop, combined with the safety evaluation model, the actual abnormal process of the corresponding partitioned workshop in making four-corner cartons is judged; Early warning module: outputs safety early warning signals for the production process of four-corner cartons according to the actual abnormal process conditions of different partition workshops; Wherein, the data acquisition module includes: Feature parameter unit: obtains real-time carton production parameters based on sensors in partitioned workshops and constructs carton production parameter matrix A: ； in, represents the parameter value of the i-th parameter at the j-th monitoring time, ; According to the covariance matrix of the production parameter matrix A Get the feature vector B: ； in, Represents the eigenvector corresponding to the i-th parameter; Determine the characteristic parameters of different carton production parameters based on the characteristic vector B: ； in, represents the characteristic parameter of the i-th parameter, represents the parameter value of the i-th parameter at the j-th monitoring time, represents the mean of the row vector corresponding to the i-th parameter, represents the maximum parameter value in the row vector corresponding to the i-th parameter, represents the minimum parameter value in the row vector corresponding to the i-th parameter, Represents the average value of the eigenvector of the i-th parameter after modulo calculation.

2. A monitoring and early warning system for the production process of four-corner cartons according to claim 1, characterized in that: Also includes: Sensor determination module: determines the type and quantity of sensors to be configured based on the preset key environmental parameter monitoring requirements of the workshop; Sensor installation module: According to the sensor's user manual, determine the specific installation requirements for different types of sensors and complete the installation.

3. A monitoring and early warning system for the production process of four-corner cartons according to claim 2, characterized in that: The monitoring module comprises: Workshop division unit: divide the work responsibility area of ​​the four-corner carton making workshop into zones according to the division rules of the workshop responsibility area; Parameter matching unit: Based on the key environmental parameters obtained by the workshop sensors and combined with the sensors set up in each partition workshop, the matching environmental parameters of the partition workshop are obtained.

4. A monitoring and early warning system for the production process of four-corner cartons according to claim 1, characterized in that: The data acquisition module further includes: Safety index unit: according to the production safety manual and safety standards of the partition workshop, set the preset safety parameter range for the i-th parameter in the partition workshop ; Determine the safety index value of the i-th parameter: ； in, represents the safety index value of the i-th parameter, represents the r monitoring times of the ith parameter in the historical time period, represents the preset safety weight coefficient of the i-th parameter, represents the parameter value of the i-th parameter at the g1-th monitoring time, represents the characteristic parameter of the i-th parameter, Indicates the far end value of the preset safety parameter range of the i-th parameter, represents the near-end value of the preset safety parameter range of the i-th parameter, represents the preset error constant of the i-th parameter; The safety index of the partitioned workshop is comprehensively obtained based on the safety index values ​​of all parameters involved in the corresponding partitioned workshop.

5. A monitoring and early warning system for the production process of four-corner cartons according to claim 4, characterized in that: The indicator abnormality partitioning module includes: A weight adjustment unit: adjusting a preset safety weight coefficient of each parameter in the partitioned workshop; ； in, represents the weight adjustment coefficient of the safety index of the i-th parameter, Represents the total number of valid parameters in the corresponding row vector of the i-th parameter, Represents the activation function, and x represents the total number of all valid parameters in the carton production parameter matrix A.

6. A monitoring and early warning system for the production process of four-corner cartons according to claim 5, characterized in that: The indicator abnormality partitioning module includes: Safety evaluation unit: construct the safety evaluation model of the partitioned workshop: ； in, represents the coefficient of variation of the actual effective parameters in the partition workshop, represents the actual parameter screening rate in the partition workshop, Indicates the proportion of preset effective parameters in the partitioned workshop, represents the error coefficient in the partitioned workshop, represents the logarithmic function with base 2; Based on the actual effective parameter proportion G and combined with the weight adjustment coefficient, the overall safety evaluation value D of the corresponding partition workshop is determined: ； in, represents the overall safety evaluation value of the partitioned workshop, represents the preset weight coefficient of the i-th parameter; when , the safety evaluation warning level is judged to be zero, where L represents the number of partitioned workshops; represents the overall safety evaluation value of the h-th partition workshop; when , the safety assessment warning level is judged to be level one; when , the safety assessment warning level is judged to be level 2; According to the warning level and in combination with the abnormal parameter conditions of the partitioned workshop, the actual abnormal process conditions of the partitioned workshop are obtained.

7. A monitoring and early warning system for the production process of four-corner cartons according to claim 6, characterized in that: The early warning module comprises: Early warning unit: When the safety evaluation early warning level is zero, there is no abnormality in the current partition workshop; When the safety evaluation warning level is level one, a general alarm is issued to the partition workshop, and a warning signal is issued to check for abnormal parameters of the partition workshop; When the safety assessment warning level is level 2, the partition workshop issues an emergency warning and sends a warning signal to suspend the production process; Signal warning unit: It integrates the actual abnormal process conditions corresponding to different partition workshops and the related warning signals, and outputs safety warning signals for the carton production process.

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