A remote intelligent monitoring system for automatic laminating machines

Abstract

The present invention discloses a remote intelligent monitoring system for an automatic laminating machine, which belongs to the field of laminating machines and is used to solve the problem that the automatic laminating machine needs to be manually checked in real time for the laminating effect of the product and cannot detect the abnormal operating conditions. The system comprises a model matching module, an operating analysis module, a monitoring and judging module and a labeling analysis module. The model matching module obtains the standard operating parameters of the laminating machine according to the model matching. The operating analysis module is used to analyze the operating conditions of the laminating machine and obtain the operating power deviation value of the laminating machine within the remote monitoring period through analysis. The labeling analysis module is used to analyze the labeling work of the laminating machine and obtain the labeling difference value of the laminating machine within the remote monitoring period through analysis. The monitoring and judging module is used to remotely monitor and judge the working conditions of the laminating machine. The present invention realizes remote monitoring of the automatic laminating machine, effectively ensures the product laminating efficiency of the automatic laminating machine and timely understands the abnormal operating conditions.

Description

Technical Field

[0001] The invention belongs to the field of laminating machines and relates to remote monitoring technology, in particular to a remote intelligent monitoring system for an automatic laminating machine. Background Art

[0002] The laminating machine includes unwinding device, gluing device, conveying and pressurizing device, driving motor and other major mechanical parts. The fully automatic laminating machine is mainly designed for the production characteristics of small displays and small touch components. It is one of the necessary equipment for the production of liquid crystal displays. It is used in the post-production process of liquid crystal displays to attach polarizers on the front and back sides of the formed liquid crystal glass substrate according to the polarization angle. It is also suitable for various combination processes of touch components and window protection components. It can complete the pressure-sensitive lamination of various materials such as film / film, film / B glass substrate, film to acrylic panel, etc. It has the advantages of high efficiency, convenient alignment, and high product yield.

[0003] In the prior art, when the automatic laminating machine is in use, manual observation and checking of the laminating effect of the product is required in real time. This consumes a lot of manpower, but also fails to guarantee the laminating effect and efficiency of the product. It also fails to detect abnormal operating conditions of the automatic laminating machine. Therefore, we propose a remote intelligent monitoring system for the automatic laminating machine. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention aims to provide a remote intelligent monitoring system for an automatic laminating machine.

[0005] The technical problems to be solved by the present invention are:

[0006] How to achieve remote intelligent monitoring of automatic laminating machines based on laminating efficiency and operating conditions.

[0007] The purpose of the present invention can be achieved by the following technical solutions:

[0008] A remote intelligent monitoring system for an automatic laminating machine, comprising a user terminal, a model matching module, a data acquisition module, an operation analysis module, a monitoring determination module, a labeling analysis module and a server, wherein the user terminal is used to input the model of the laminating machine and send the model to the server, and the server sends the model to the model matching module;

[0009] The model matching module is data-connected to a database, in which standard operating parameters of laminating machines of different models are stored; the model matching module obtains the standard operating parameters of the laminating machine according to the model matching, and sends the standard operating parameters to the server, and the server sends the standard operating parameters to the operation analysis module and the labeling analysis module;

[0010] The data acquisition module is used to collect real-time operating parameters of the laminating machine and send the real-time operating parameters to the server, and the server sends the real-time operating parameters to the operation analysis module and the labeling analysis module;

[0011] The operation analysis module is used to analyze the operation status of the laminating machine, and the operation power deviation value of the laminating machine obtained by the analysis is fed back to the server, and the server sends the operation power deviation value of the laminating machine in the remote monitoring period to the monitoring determination module;

[0012] The labeling analysis module is used to analyze the labeling work of the laminating machine, and the labeling difference of the laminating machine in the remote monitoring period is obtained by analysis and fed back to the server, and the server sends the labeling difference of the laminating machine in the remote monitoring period to the monitoring and determination module;

[0013] The monitoring and judging module is used to remotely monitor and judge the working condition of the laminating machine, and generate a working abnormality signal or a working normal signal to feed back to the server;

[0014] If the server receives a work abnormality signal, it forwards the work abnormality signal to the user terminal;

[0015] If the server receives a normal working signal, no operation is performed.

[0016] Furthermore, the standard operating parameters include a standard operating power range and a standard labeling number range;

[0017] The real-time operation parameters include real-time operation power and real-time labeling number.

[0018] Furthermore, the analysis process of the operation analysis module is specifically as follows:

[0019] Step 1: mark the laminating machine as u, where u=1, 2, ..., z, where z is a positive integer; set a remote monitoring period for the laminating machine, and set a number of time points Tut within the remote monitoring period, where t=1, 2, ..., x, where x is a positive integer and t represents the number of the time point;

[0020] Step 2: Obtain the operating power of the laminating machine at each time point and mark the operating power at each time point as GL Tut ;

[0021] Step 3: Count the number of time points and record the number of time points as the time point number DSu;

[0022] By formula The average operating power JGLu of the laminating machine during the remote monitoring period is calculated as follows:

[0023] Step 4: Compare the average operating power of the laminating machine during the remote monitoring period with the standard operating power;

[0024] If the average operating power is within the standard operating power range, the average operating power is calibrated as the standard operating power;

[0025] If the average operating power is not within the standard operating power range, the standard operating power is calibrated according to the standard operating power range;

[0026] Step 5: Calculate the difference between the operating power of the laminating machine at each time point and the standard operating power, and obtain the operating power difference GLC of the laminating machine at each time point Tut ;

[0027] Step 6: Add the operating power differences at each time point and divide the sum by the number of time points to obtain the operating power deviation value GPCu of the laminating machine during the remote monitoring period.

[0028] Furthermore, the analysis process of the labeling analysis module is as follows:

[0029] Step S1: divide the remote monitoring time period into time periods, with minutes as the unit, to obtain a number of minute time periods Fui, i=1, 2, ..., v, v is a positive integer, and i represents the number of the minute time period;

[0030] Step S2: The start time of each minute period is used as the labeling start counting time, and the end time of each minute period is used as the labeling end counting time;

[0031] Step S3: Get the number of labels in each minute period and mark the number of labels as TB Fui ; Count the number of minute time periods and record the number of minute time periods as the time period number SSu;

[0032] Step S4: By formula The average number of labels JTBu of the laminating machine during the remote monitoring period is calculated;

[0033] Step S5: Calculate the difference between the average number of labels applied by the laminating machine during the remote monitoring period and the standard labeling number interval to obtain the labeling difference TBCu of the laminating machine during the remote monitoring period.

[0034] Furthermore, the calculation process of the labeling difference of the laminating machine during the remote monitoring period is as follows:

[0035] The difference between the average labeling number JTBu of the laminating machine during the remote monitoring period and the upper limit of the standard labeling number interval is calculated, and the difference between the average labeling number JTBu of the laminating machine during the remote monitoring period and the lower limit of the standard labeling number interval is calculated. The two sets of differences are added and averaged to obtain the labeling difference TBCu.

[0036] Furthermore, the working process of the monitoring and determination module is as follows:

[0037] Step SS1: Obtain the operating power deviation value GPCu and labeling difference value TBCu of the laminating machine during the remote monitoring period;

[0038] Step SS2: Obtain the operating power deviation threshold and labeling difference threshold stored in the server;

[0039] If the operating power deviation value is greater than or equal to the operating power deviation threshold or the labeling difference value is greater than or equal to the labeling difference threshold, a work abnormality signal is generated;

[0040] If the operating power deviation value is less than the operating power deviation threshold and the labeling difference value is less than the labeling difference threshold, proceed to the next step;

[0041] Step SS3: Calculate the abnormal value YCu of the laminating machine during the remote monitoring period by formula;

[0042] Step SS4: if the abnormal value of the laminating machine during the remote monitoring period is greater than or equal to the abnormal threshold, a work abnormality signal is generated;

[0043] If the abnormal value of the laminating machine during the remote monitoring period is less than the abnormal threshold, a normal operation signal is generated.

[0044] Furthermore, the calculation formula of the abnormal value of the laminating machine during the remote monitoring period is as follows:

[0045] YCu=GPCu×α+TBCu×β; wherein α and β are weight coefficients with fixed values, and the values ​​of α and β are both greater than zero.

[0046] Compared with the prior art, the present invention has the following beneficial effects:

[0047] During remote monitoring, the present invention inputs the model of the laminating machine in the user terminal, and the model matching module obtains the standard operating parameters of the laminating machine based on the model matching, and then analyzes the operating status of the laminating machine through the operation analysis module, and obtains the operating power deviation value of the laminating machine during the remote monitoring period. The labeling analysis module is then combined to analyze the labeling work of the laminating machine, and the labeling difference of the laminating machine during the remote monitoring period is analyzed. The operating power deviation value and the labeling difference of the laminating machine during the remote monitoring period are sent to the monitoring and judgment module. The monitoring and judgment module remotely monitors and judges the working status of the laminating machine, and determines whether a working abnormality signal or a working normal signal is generated. The present invention realizes remote monitoring of the automatic laminating machine, effectively ensures the product laminating efficiency of the automatic laminating machine and timely understands the abnormal operating status. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0049] Figure 1 It is the overall system block diagram of the present invention. DETAILED DESCRIPTION

[0050] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than 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.

[0051] See also Figure 1 As shown, a remote intelligent monitoring system for an automatic laminating machine includes a user terminal, a model matching module, a data acquisition module, an operation analysis module, a monitoring determination module, a labeling analysis module and a server;

[0052] Before remote monitoring, the user terminal is used for the staff to register and log into the system after entering personal information, and send the personal information to the server; the personal information includes the staff's name, real-name authenticated mobile phone number, etc.;

[0053] At the same time, the server signal is connected to several laminating machines;

[0054] During remote monitoring, the user terminal is used to input the model of the laminating machine and send the model to the server, and the server sends the model to the model matching module;

[0055] The model matching module data is connected to a database, and the database stores standard operating parameters of laminating machines of different models;

[0056] It should be specifically noted that the standard operating parameters include standard operating power range, standard labeling number range, etc.;

[0057] The model matching module obtains standard operating parameters of the laminating machine according to the model matching, and sends the standard operating parameters to the server, and the server sends the standard operating parameters to the operation analysis module and the labeling analysis module;

[0058] The data acquisition module is used to collect real-time operating parameters of the laminating machine and send the real-time operating parameters to the server, and the server sends the real-time operating parameters to the operation analysis module and the labeling analysis module;

[0059] It should be specifically noted that the real-time operating parameters include real-time operating power, real-time number of labels, etc.;

[0060] The operation analysis module is used to analyze the operation status of the laminating machine, and the analysis process is as follows:

[0061] Step 1: mark the laminating machine as u, where u=1, 2, ..., z, where z is a positive integer; set a remote monitoring period for the laminating machine, and set a number of time points Tut within the remote monitoring period, where t=1, 2, ..., x, where x is a positive integer and t represents the number of the time point;

[0062] Step 2: Obtain the operating power of the laminating machine at each time point and mark the operating power at each time point as GL Tut ;

[0063] Step 3: Count the number of time points and record the number of time points as the time point number DSu;

[0064] By formula The average operating power JGLu of the laminating machine during the remote monitoring period is calculated as follows:

[0065] Step 4: Compare the average operating power of the laminating machine during the remote monitoring period with the standard operating power;

[0066] If the average operating power is within the standard operating power range, the average operating power is calibrated as the standard operating power;

[0067] If the average operating power is not within the standard operating power range, the standard operating power is calibrated according to the standard operating power range;

[0068] It should be specifically stated that when the standard operating power is calibrated according to the standard operating power range, the upper limit value and the lower limit value of the standard operating power range are added together and the average value is taken as the standard operating power;

[0069] Step 5: Calculate the difference between the operating power of the laminating machine at each time point and the standard operating power, and obtain the operating power difference GLC of the laminating machine at each time point Tut ;

[0070] Step 6: Add the operating power differences at each time point and divide by the number of time points to obtain the operating power deviation value GPCu of the laminating machine during the remote monitoring period. The calculation formula is:

[0071] GPCu=(GLC Tu1 +GLC Tu2 +……+GLC Tux ) / DSu;

[0072] The operation analysis module feeds back the operation power deviation value GPCu of the laminating machine during the remote monitoring period to the server, and the server sends the operation power deviation value GPCu of the laminating machine during the remote monitoring period to the monitoring determination module;

[0073] The labeling analysis module is used to analyze the labeling work of the laminating machine. The analysis process is as follows:

[0074] Step S1: divide the remote monitoring time period into time periods, with minutes as the unit, to obtain a number of minute time periods Fui, i=1, 2, ..., v, v is a positive integer, and i represents the number of the minute time period;

[0075] Step S2: The start time of each minute period is used as the labeling start counting time, and the end time of each minute period is used as the labeling end counting time;

[0076] It is understandable that the end counting time of labeling in the previous minute period is the start counting time of labeling in the next minute period;

[0077] Step S3: Get the number of labels in each minute period and mark the number of labels as TB Fui ; Count the number of minute time periods and record the number of minute time periods as the time period number SSu;

[0078] Step S4: By formula The average number of labels JTBu of the laminating machine during the remote monitoring period is calculated;

[0079] Step S5: Calculate the difference between the average number of labels applied by the laminating machine during the remote monitoring period and the standard labeling number interval to obtain the labeling difference TBCu of the laminating machine during the remote monitoring period, which is specifically:

[0080] The difference between the average number of labels JTBu of the laminating machine in the remote monitoring period and the upper limit of the standard labeling number interval is calculated, and the difference between the average number of labels JTBu of the laminating machine in the remote monitoring period and the lower limit of the standard labeling number interval is calculated. The two sets of differences are added and averaged to obtain the labeling difference TBCu;

[0081] The labeling analysis module feeds back the labeling difference TBCu of the laminating machine during the remote monitoring period to the server, and the server sends the labeling difference TBCu of the laminating machine during the remote monitoring period to the monitoring determination module;

[0082] The monitoring and determination module combines the operating power deviation value and labeling difference value of the laminating machine during the remote monitoring period to remotely monitor and determine the working condition of the laminating machine. The specific working process is as follows:

[0083] Step SS1: Obtain the operating power deviation value GPCu and labeling difference value TBCu of the laminating machine during the remote monitoring period obtained by the above calculation;

[0084] Step SS2: Obtain the operating power deviation threshold and labeling difference threshold stored in the server;

[0085] If the operating power deviation value is greater than or equal to the operating power deviation threshold or the labeling difference value is greater than or equal to the labeling difference threshold, a work abnormality signal is generated;

[0086] If the operating power deviation value is less than the operating power deviation threshold and the labeling difference value is less than the labeling difference threshold, proceed to the next step;

[0087] Step SS3: The abnormal value YCu of the laminating machine during the remote monitoring period is calculated by the formula YCu=GPCu×α+TBCu×β; wherein α and β are weight coefficients with fixed values, and the values ​​of α and β are both greater than zero:

[0088] Step SS4: if the abnormal value of the laminating machine during the remote monitoring period is greater than or equal to the abnormal threshold, a work abnormality signal is generated;

[0089] If the abnormal value of the laminating machine during the remote monitoring period is less than the abnormal threshold, a normal operation signal is generated;

[0090] The monitoring and determining module feeds back the abnormal working signal or the normal working signal to the server;

[0091] If the server receives a work abnormality signal, it forwards the work abnormality signal to the user terminal;

[0092] If the server receives a normal working signal, no operation is performed.

[0093] A remote intelligent monitoring system for an automatic laminating machine, when working, during remote monitoring, a user terminal inputs the model of the laminating machine and sends the model to a server, the server sends the model to a model matching module, the model matching module data is connected to a database, the database stores standard operating parameters of laminating machines of different models, the model matching module obtains the standard operating parameters of the laminating machine according to the model matching, and sends the standard operating parameters to the server, the server sends the standard operating parameters to an operation analysis module and a labeling analysis module;

[0094] The real-time operating parameters of the laminating machine are collected through the data collection module, and the real-time operating parameters are sent to the server, and the server sends the real-time operating parameters to the operation analysis module and the labeling analysis module;

[0095] The operation status of the laminating machine is analyzed through the operation analysis module, the laminating machine is marked as u, the remote monitoring period of the laminating machine is set, and several time points Tut are set within the remote monitoring period, and then the operating power of the laminating machine at each time point is obtained and marked as GL Tut , and count the number of time points at the same time, and record the number of time points as the time point number DSu, combined with the formula The average operating power JGLu of the laminating machine during the remote monitoring period is calculated, and the average operating power of the laminating machine during the remote monitoring period is compared with the standard operating power. If the average operating power is within the standard operating power range, the average operating power is calibrated as the standard operating power. If the average operating power is not within the standard operating power range, the standard operating power is calibrated according to the standard operating power range. The difference between the operating power of the laminating machine at each time point and the standard operating power is calculated to obtain the operating power difference GLC of the laminating machine at each time point. Tut , the operating power difference at each time point is added and divided by the number of time points to obtain the operating power deviation value GPCu of the laminating machine during the remote monitoring period, the operation analysis module feeds back the operating power deviation value GPCu of the laminating machine during the remote monitoring period to the server, and the server sends the operating power deviation value GPCu of the laminating machine during the remote monitoring period to the monitoring determination module;

[0096] The labeling analysis module is used to analyze the labeling work of the laminating machine, and the remote monitoring period is divided into time periods. The time period division is in minutes, and several minute time periods Fui are obtained. The start time of each minute time period is used as the labeling start counting time, and the end time of each minute time period is used as the labeling end counting time, and then the labeling number TB of each minute time period is obtained. Fui , and count the number of minute periods, and record the number of minute periods as the period number SSu, combined with the formula The average number of labels JTBu of the laminating machine in the remote monitoring period is calculated, and the difference between the average number of labels and the standard number of labels in the remote monitoring period is calculated to obtain the labeling difference TBCu of the laminating machine in the remote monitoring period. The labeling analysis module feeds back the labeling difference TBCu of the laminating machine in the remote monitoring period to the server, and the server sends the labeling difference TBCu of the laminating machine in the remote monitoring period to the monitoring judgment module;

[0097] The monitoring and judgment module remotely monitors and judges the working condition of the laminating machine in combination with the operating power deviation value and the labeling difference value of the laminating machine during the remote monitoring period, obtains the operating power deviation value GPCu and the labeling difference value TBCu of the laminating machine during the remote monitoring period, and then obtains the operating power deviation threshold and the labeling difference threshold stored in the server. If the operating power deviation value is greater than or equal to the operating power deviation threshold or the labeling difference value is greater than or equal to the labeling difference threshold, a working abnormality signal is generated. If the operating power deviation value is less than the operating power deviation threshold and the labeling difference value is less than the labeling difference threshold, the abnormal value YCu of the laminating machine during the remote monitoring period is calculated by the formula YCu=GPCu×α+TBCu×β. If the abnormal value of the laminating machine during the remote monitoring period is greater than or equal to the abnormal threshold, a working abnormality signal is generated. If the abnormal value of the laminating machine during the remote monitoring period is less than the abnormal threshold, a working normal signal is generated. The monitoring and judgment module feeds back the working abnormality signal or the working normal signal to the server. If the server receives the working abnormality signal, it forwards the working abnormality signal to the user terminal. If the server receives the working normal signal, no operation is performed.

[0098] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions. The size of the weight coefficient and the proportional coefficient is to quantify each parameter to obtain a specific value, which is convenient for subsequent comparison. Regarding the size of the weight coefficient and the proportional coefficient, as long as it does not affect the proportional relationship between the parameter and the quantized value, it is fine.

[0099] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A remote intelligent monitoring system for an automatic laminating machine, characterized in that: It includes a user terminal, a model matching module, a data acquisition module, an operation analysis module, a monitoring and determination module, a labeling analysis module and a server. The user terminal is used to input the model of the laminating machine and send the model to the server, and the server sends the model to the model matching module; The model matching module is data-connected to a database, in which standard operating parameters of laminating machines of different models are stored; the model matching module obtains the standard operating parameters of the laminating machine according to the model matching, and sends the standard operating parameters to the server, and the server sends the standard operating parameters to the operation analysis module and the labeling analysis module; The data acquisition module is used to collect real-time operating parameters of the laminating machine and send the real-time operating parameters to the server, and the server sends the real-time operating parameters to the operation analysis module and the labeling analysis module; The operation analysis module is used to analyze the operation status of the laminating machine, and the operation power deviation value of the laminating machine obtained by the analysis is fed back to the server, and the server sends the operation power deviation value of the laminating machine in the remote monitoring period to the monitoring determination module; The labeling analysis module is used to analyze the labeling work of the laminating machine, and the labeling difference of the laminating machine in the remote monitoring period is obtained by analysis and fed back to the server, and the server sends the labeling difference of the laminating machine in the remote monitoring period to the monitoring and determination module; The monitoring and judging module is used to remotely monitor and judge the working condition of the laminating machine, and generate a working abnormality signal or a working normal signal to feed back to the server; If the server receives a work abnormality signal, it forwards the work abnormality signal to the user terminal; If the server receives a normal working signal, no operation will be performed; The analysis process of the labeling analysis module is as follows: Step S1: divide the remote monitoring time period into time periods, with minutes as the unit, to obtain a number of minute time periods Fui, i=1, 2, ..., v, v is a positive integer, and i represents the number of the minute time period; Step S2: The start time of each minute period is used as the labeling start counting time, and the end time of each minute period is used as the labeling end counting time; Step S3: Get the number of labels in each minute period and mark the number of labels as TB F ui; count the number of minute time periods, and record the number of minute time periods as the time period number SSu; Step S4: By formula The average number of labels JTBu of the laminating machine during the remote monitoring period is calculated; Step S5: Calculate the difference between the average number of labels applied by the laminating machine during the remote monitoring period and the standard labeling number interval to obtain the labeling difference TBCu of the laminating machine during the remote monitoring period; The calculation process of the labeling difference of the laminating machine during the remote monitoring period is as follows: The difference between the average number of labels JTBu of the laminating machine in the remote monitoring period and the upper limit of the standard labeling number interval is calculated, and the difference between the average number of labels JTBu of the laminating machine in the remote monitoring period and the lower limit of the standard labeling number interval is calculated. The two sets of differences are added and averaged to obtain the labeling difference TBCu; The working process of the monitoring and determination module is as follows: Step SS1: Obtain the operating power deviation value GPCu and labeling difference value TBCu of the laminating machine during the remote monitoring period; Step SS2: Obtain the operating power deviation threshold and labeling difference threshold stored in the server; If the operating power deviation value is greater than or equal to the operating power deviation threshold or the labeling difference value is greater than or equal to the labeling difference threshold, a work abnormality signal is generated; If the operating power deviation value is less than the operating power deviation threshold and the labeling difference value is less than the labeling difference threshold, proceed to the next step; Step SS3: Calculate the abnormal value YCu of the laminating machine during the remote monitoring period by formula; Step SS4: if the abnormal value of the laminating machine during the remote monitoring period is greater than or equal to the abnormal threshold, a work abnormality signal is generated; If the abnormal value of the laminating machine during the remote monitoring period is less than the abnormal threshold, a normal operation signal is generated; The standard operating parameters include standard operating power range and standard labeling number range; Real-time operating parameters include real-time operating power and real-time labeling number; The analysis process of the operation analysis module is as follows: Step 1: mark the laminating machine as u, where u=1, 2, ..., z, where z is a positive integer; set a remote monitoring period for the laminating machine, and set a number of time points Tut within the remote monitoring period, where t=1, 2, ..., x, where x is a positive integer and t represents the number of the time point; Step 2: Obtain the operating power of the laminating machine at each time point and mark the operating power at each time point as GL T ut; Step 3: Count the number of time points and record the number of time points as the time point number DSu; By formula The average operating power JGLu of the laminating machine during the remote monitoring period is calculated as follows: Step 4: Compare the average operating power of the laminating machine during the remote monitoring period with the standard operating power; If the average operating power is within the standard operating power range, the average operating power is calibrated as the standard operating power; If the average operating power is not within the standard operating power range, the standard operating power is calibrated according to the standard operating power range; when the standard operating power is calibrated according to the standard operating power range, the upper limit value and the lower limit value of the standard operating power range are added together and the average value is taken as the standard operating power; Step 5: Calculate the difference between the operating power of the laminating machine at each time point and the standard operating power, and obtain the operating power difference GLC of the laminating machine at each time point T ut; Step 6: Add the operating power differences at each time point and divide the sum by the number of time points to obtain the operating power deviation value GPCu of the laminating machine during the remote monitoring period.

2. According to claim 1, the remote intelligent monitoring system for an automatic laminating machine is characterized in that: The calculation formula of the abnormal value of the laminating machine during the remote monitoring period is as follows: YCu=GPCu×α+TBCu×β; wherein α and β are weight coefficients with fixed values, and the values ​​of α and β are both greater than zero.

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