CN115600130A - A data analysis-based operation management and control system for plywood composite glue binding equipment - Google Patents

Abstract

The invention discloses a management and control system for operation of plywood composite glue equipment based on data analysis, which relates to the technical field of operation and control of plywood glue equipment and solves the technical problem that whether the current operation efficiency of plywood glue equipment is qualified or not can not be accurately judged according to ladder mark setting analysis in the glue process in the prior art; the analysis object is tracked in the maintenance process, the fault part is analyzed according to the historical operation of the analysis object, the maintenance mode is reasonably selected for the fault of the current part, the maintenance accuracy of the analysis object is guaranteed, and the work efficiency of the analysis pair is guaranteed.

Description

A data analysis-based operation management and control system for plywood composite glue binding equipment

technical field

The invention relates to the technical field of operation management and control of plywood composite glue binding equipment, in particular to an operation management and control system of plywood composite glue binding equipment based on data analysis.

Background technique

Plywood is one of the commonly used materials for furniture and is a kind of wood-based panel. Plywood is a three-layer or multi-layer board-like material that is made of wood sections that are peeled into veneers or sliced into thin wood, and then glued with adhesives. Usually, odd-numbered veneers are used, and adjacent layers of veneers are used. The fiber directions of the plywood are glued vertically to each other, and plywood groups of various thicknesses are obtained by gluing different quantities of plywood. During this process, every link needs to be inspected for quality.

However, in the prior art, it is impossible to accurately determine whether the operating efficiency of the current plywood composite glue is qualified based on the analysis of the ladder label setting during the glue binding process. Therefore, it is impossible to accurately determine the operating status of the glue binding equipment; The glue binding equipment makes accurate predictions according to the type of part failure, so that the impact of the failure of the plywood glue binding equipment cannot be controlled.

Aiming at the above-mentioned technical defects, a solution is now proposed.

Contents of the invention

The purpose of the present invention is to solve the above-mentioned problems, and propose a data analysis-based operation management and control system for plywood composite gluing equipment, which analyzes the real-time ladder setting during the operation of plywood composite gluing equipment, so that the real-time plywood The quality inspection of the glue binding process improves the qualification of the plywood glue binding. At the same time, when the execution process of the plywood glue binding is qualified, the detection of the glue binding equipment is more accurate; the real-time glue binding task is analyzed during the glue binding process Inspection, to judge the glue binding quality of the real-time glue binding task to monitor and analyze, improve the monitoring strength in the glue binding process, ensure the glue binding efficiency and rectify the abnormal glue binding in time, improve the glue binding efficiency and also be able to correct the glue binding equipment for efficient testing.

The purpose of the present invention can be achieved through the following technical solutions:

An operation management and control system for plywood composite binding equipment based on data analysis, including a server, and the communication connection of the server includes:

The ladder real-time analysis unit is used to analyze the real-time ladder settings during the operation of the plywood composite glued equipment, mark the plywood composite glued equipment as the analysis object, set the label i, i is a natural number greater than 1, and pass the real-time ladder Analyze and generate the abnormal signal of the glue binding process and the normal signal of the glue binding process, and send them to the server;

The glue binding process analysis unit is used to analyze and detect the glue binding process of the real-time glue binding task, generate a normal signal of the glue binding process and an abnormal signal of the glue binding process through analysis, and send them to the server;

The equipment operation tracking unit is used to track the operation of the analysis object during the maintenance process, analyze according to the historical operation fault parts of the analysis object, divide the analysis object into k parts, k is a natural number greater than 1, and obtain the analysis object through analysis Part failure analysis coefficient, according to the comparison of part failure analysis coefficients, parts are divided into first-level failure parts, second-level failure parts and third-level failure parts, and are sent to the server;

The fault prediction unit is operated to perform fault prediction on the analysis object performing the real-time glue binding task, generate a high fault risk prediction signal and a low fault risk prediction signal through analysis, and send them to the server.

As a preferred embodiment of the present invention, the running process of the ladder real-time analysis unit is as follows:

According to the analysis object corresponding to the real-time glue binding task, set the real-time glue binding task corresponding to the plywood ladder, divide the real-time glue binding task according to the real-time glue binding speed of the analysis object, and distinguish the real-time glue binding task according to the time point , the reduction amount of the real-time glue binding task at adjacent time points is divided by the setting ladder scalar, and the quotient corresponds to the execution amount of the real-time glue binding task, and the execution amount unit is a group; the real-time glue binding task ladder is set based on the real-time glue binding speed Scale the expected execution curve, and substitute the curve into the Cartesian coordinate system, and the X-axis of the Cartesian coordinate system is the time point, and the Y-axis is the ladder scalar; If it is ten, then the plywood is a group of ten sheets, and the real-time current glue binding can be judged whether it is qualified or not through the ladder scalar setting.

As a preferred embodiment of the present invention, according to the real-time adhesive task execution process of the analysis object, the ladder quantities at each time point are obtained, and are substituted into the Cartesian coordinate system to construct the real-time execution curve of the ladder; the predicted execution curve of the ladder is collected Compare the curve slope difference with the corresponding time period in the ladder real-time execution curve and the time point deviation duration of the two curves corresponding to the same ladder value, and compare them with the curve slope difference threshold range and the time point deviation time length threshold range respectively:

If the slope difference between the predicted execution curve of the ladder and the real-time execution curve of the ladder is not within the curve slope difference threshold range, or the time point deviation duration of the two curves corresponding to the same ladder value is not within the time point deviation duration threshold Scope, then generate the abnormal signal of the glue binding process and send the abnormal signal of the glue binding process and the corresponding abnormal time to the server together;

If the slope difference between the predicted execution curve of the ladder and the real-time execution curve of the ladder is within the curve slope difference threshold range, and the time point deviation duration of the two curves corresponding to the same ladder quantity is within the time point deviation duration threshold range, Then mark the corresponding time point as a normal time, generate a normal signal of the glue binding process, and send the normal signal of the glue binding process and the corresponding normal time to the server together.

As a preferred embodiment of the present invention, the operation process of the binding process analysis unit is as follows:

Collect the maximum rework amount difference between the time points in the glue binding process of the real-time glue binding task and the maximum rework amount increase at adjacent time points, and compare them with the rework amount difference threshold and the rework amount increase threshold respectively. Compare:

If the maximum rework amount difference between time points in the real-time glue binding process exceeds the rework amount difference threshold, or the maximum rework amount increase at adjacent time points exceeds the rework amount increase threshold, a glue binding process is generated Abnormal signal and send the abnormal signal of the glue binding process to the server; if the real-time glue binding task corresponds to the maximum rework amount difference between the time points in the glue binding process does not exceed the rework amount difference threshold, and the maximum rework amount at adjacent time points If the increase amount does not exceed the threshold value of the increase amount of the rework amount, a normal signal of the perfect binding process is generated and sent to the server.

As a preferred embodiment of the present invention, the operation process of the equipment operation tracking unit is as follows:

The historical operation time period of the analysis object is obtained by taking the maintenance time of the current analysis object as the end point, the duration of the failure of the part of the analysis object in the historical operation time period and the maintenance frequency of the corresponding part within the duration of the failure of the part are collected; the historical operation time period is collected The average maintenance interval of each part corresponding to the analysis object in the time period;

The part failure analysis coefficient of the analysis object is obtained through analysis; compare the part failure analysis coefficient of the analysis object with P1 and P2, where P1 and P2 are the thresholds of the part failure analysis coefficient, and P1 is greater than P2; if the part failure of the analysis object If the analysis coefficient exceeds P1, the corresponding part will be marked as the first-level fault part; if the analysis coefficient of the part of the analysis object does not exceed P1, and exceeds P2, then the corresponding part will be marked as the second-level fault part; If the coefficient does not exceed P2, the corresponding part will be marked as a third-level fault part.

As a preferred embodiment of the present invention, the operation process of the fault prediction unit is as follows:

Collect the growth rate of the transition from high-level fault parts to low-level fault parts during the real-time operation of the analysis object, and the real-time increase in the number of faults corresponding to the parts without faults in the historical time period, and compare them with the growth rate threshold and the increase number threshold respectively:

If the growth rate of high-level fault parts changing from low-level fault parts during the real-time operation of the analysis object exceeds the growth rate threshold, or the number of real-time faults corresponding to the parts that have not experienced faults in the historical time period exceeds the increase number threshold, a high fault risk prediction signal is generated and Send the high failure risk prediction signal to the server; if the growth rate of the high-level fault parts during the real-time operation of the analysis object changes to the low-level fault parts does not exceed the growth rate threshold, and the number of real-time faults corresponding to the parts that have not failed in the historical period does not exceed Increasing the quantity threshold, a low failure risk prediction signal is generated and sent to the server.

Compared with prior art, the beneficial effect of the present invention is:

1. In the present invention, the real-time ladder setting is analyzed during the operation of the plywood composite gluing equipment, so that the quality inspection of the real-time plywood gluing process is carried out, and the qualification of the plywood gluing is improved, and at the same time, the execution process of the plywood gluing is qualified When testing the glue binding equipment, it is more accurate; the real-time glue binding task is analyzed and detected during the glue binding process, and the glue binding quality of the real-time glue binding task is judged for monitoring and analysis, which improves the monitoring during the glue binding process. , to ensure the efficiency of glue binding and rectify the abnormal glue binding in time, improve the glue binding efficiency and efficiently detect the glue binding equipment;

2. In the present invention, the analysis object is tracked during the inspection and maintenance process, and the analysis is carried out according to the history of the analysis object’s fault location, and the maintenance mode is reasonably selected for the current location failure, which improves the efficiency of the analysis object inspection and maintenance, and at the same time ensures the accuracy of the analysis object inspection. Accuracy, reducing the occurrence of inefficient maintenance of the analysis object parts, which is conducive to ensuring the work efficiency of the analysis pair; judging whether the analysis object has a failure risk during operation, and predicting its failure, reducing the impact of the analysis object failure on the binding task The impact brought by the execution is conducive to early fault repair and guarantees the operating efficiency of the analysis object to the greatest extent.

Description of drawings

In order to facilitate the understanding of those skilled in the art, the present invention will be further described below in conjunction with the accompanying drawings.

Fig. 1 is a functional block diagram of an operation management and control system for plywood composite binding equipment based on data analysis according to the present invention.

detailed description

In order to enable those skilled in the art to better understand the solutions of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only It is a part of embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

Reference herein to an "embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the present invention. The occurrences of this phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is understood explicitly and implicitly by those skilled in the art that the embodiments described herein can be combined with other embodiments.

Please refer to Figure 1, a data analysis-based operation management and control system for plywood composite binding equipment, including a server, which is connected to a real-time analysis unit for ladder marks, a binding process analysis unit, an equipment operation tracking unit, and an operation failure prediction unit. , wherein, the server is connected with the ladder real-time analysis unit, the adhesive process analysis unit, the equipment operation tracking unit and the operation failure prediction unit in two-way communication;

The server generates the ladder real-time analysis signal and sends the ladder real-time analysis signal to the ladder real-time analysis unit. After the ladder real-time analysis unit receives the ladder real-time analysis signal, it sets the real-time ladder during the operation of the plywood composite glued equipment. Analysis, so as to conduct quality inspection of the real-time plywood glue binding process, improve the qualification of plywood glue binding, and at the same time, when the plywood glue binding execution process is qualified, the detection of glue binding equipment is more accurate;

Mark the plywood composite glue binding equipment as the analysis object, set the label i, i is a natural number greater than 1, analyze according to the analysis object corresponding to the real-time glue binding task, set the real-time glue binding task corresponding to the plywood ladder, and according to the real-time glue binding task of the analysis object The glue binding speed divides the real-time glue binding tasks, and divides the real-time glue binding tasks according to the time points. The reduction of the real-time glue binding tasks at adjacent time points is divided by the set ladder scalar value, and the quotient corresponds to the real-time glue binding tasks. Execution amount, the execution amount unit is a group; set the real-time glue binding task ladder estimated execution curve based on the real-time glue binding speed, and substitute the curve into the Cartesian coordinate system, and the X axis of the Cartesian coordinate system is the time point, and the Y axis is the ladder scale ;The ladder scalar represents the plywood binding process, and the set quantity threshold is the unit plywood. If the ladder scalar is ten, the plywood is a group of ten sheets. Through the ladder scalar setting, it can be determined whether the real-time current glue binding is qualified;

According to the execution process of the real-time binding task of the analysis object, the echelon quantity at each time point is obtained, and then substituted into the Cartesian coordinate system to construct the real-time execution curve of the echelon; the estimated execution curve of the echelon and the corresponding time period in the real-time execution curve of the echelon are collected The curve slope difference and the time point deviation duration of the two curves corresponding to the same ladder quantity, and the curve slope difference between the ladder predicted execution curve and the ladder real-time execution curve in the corresponding time period and the two curves corresponding to the same ladder quantity The time point deviation duration is compared with the curve slope difference threshold range and the time point deviation time length threshold range respectively:

If the slope difference between the predicted execution curve of the ladder and the real-time execution curve of the ladder is not within the curve slope difference threshold range, or the time point deviation duration of the two curves corresponding to the same ladder value is not within the time point deviation duration threshold range, it is determined that there is an abnormality in the execution of the real-time glue binding task, and the corresponding time point is marked as an abnormal moment, an abnormal signal of the glue binding process is generated and the abnormal signal of the glue binding process and the corresponding abnormal time are sent to the server together, and the server receives the glue binding process After the abnormal signal of the process, the glue binding process corresponding to the abnormal time will be monitored, and the abnormal time will be used as the starting point to detect the historical time, and the deviation value of the ladder scalar will be judged. Re-execute the real-time plastic binding task execution amount within the interval time period of the current system time point;

If the slope difference between the predicted execution curve of the ladder and the real-time execution curve of the ladder is within the curve slope difference threshold range, and the time point deviation duration of the two curves corresponding to the same ladder quantity is within the time point deviation duration threshold range, Then it is determined that the execution process of the real-time glue binding task is normal, the corresponding time point is marked as a normal time, a normal signal of the glue binding process is generated, and the normal signal of the glue binding process and the corresponding normal time are sent to the server together;

After receiving the normal signal of the glue binding process, the server generates the glue binding process analysis signal and sends the glue binding process analysis signal to the glue binding process analysis unit. Analyze and detect during the glue binding process, and monitor and analyze the glue binding quality of the real-time glue binding task, which improves the monitoring during the glue binding process, ensures the glue binding efficiency and rectifies the abnormal glue binding in time, and improves the glue quality. The packing efficiency can also be used for efficient detection of glue packing equipment;

The real-time glue binding tasks correspond to the maximum rework amount difference between the time points in the glue binding process and the maximum rework amount increase at adjacent time points, and the real-time glue binding tasks correspond to the maximum amount between the time points in the glue binding process. The rework amount difference and the maximum rework amount increase at adjacent time points are compared with the rework amount difference threshold and the rework amount increase threshold respectively:

If the maximum rework amount difference between the time points of the real-time glue binding task exceeds the rework amount difference threshold, or the maximum rework amount increase at adjacent time points exceeds the rework amount increase threshold, the real-time glue binding is determined. If the analysis of the glue binding process of the task is unqualified, an abnormal signal of the glue binding process is generated and sent to the server. After receiving the abnormal signal of the glue binding process, the server will check and repair the analysis object within the time period corresponding to the time point;

If the maximum rework amount difference between the time points in the real-time glue binding process does not exceed the rework amount difference threshold, and the maximum rework amount increase at adjacent time points does not exceed the rework amount increase threshold, it is determined that the real-time The glue binding process analysis of the glue binding task is qualified, the glue binding process normal signal is generated and the glue binding process normal signal is sent to the server;

During the maintenance process of the analysis object, the server generates the equipment operation tracking signal and sends the equipment operation tracking signal to the equipment operation tracking unit. Analyze the historical operation fault parts of the object, and reasonably select the maintenance method for the current part faults, which improves the efficiency of the analysis object maintenance, and at the same time ensures the accuracy of the analysis object maintenance, reduces the occurrence of inefficient maintenance of the analysis object parts, and is conducive to ensuring the analysis Right work efficiency;

Divide the analysis object into k parts, k is a natural number greater than 1, and the historical operation time period of the analysis object is obtained with the current analysis object maintenance time as the end point, and the duration of the failure of the analysis object part in the historical operation time period is collected And the maintenance frequency of the corresponding part within the duration of the part failure, and mark the duration of the failure of the part of the analysis object in the historical operation period and the maintenance frequency of the corresponding part within the duration of the part failure respectively as CXSk and WXPk; the collected historical operation The average maintenance interval of each part corresponding to the analysis object in the time period, and the average maintenance interval of each part corresponding to the analysis object in the historical operation time period is marked as WXJk;

获取到分析对象 的部位故障分析系数Wk，其中，a1、a2以及a3均为预设比例系数，且a1＞a2＞a3＞0，β为误差 修正因子，取值为0.698； by formula

The part failure analysis coefficient Wk of the analysis object is obtained, where a1, a2 and a3 are preset proportional coefficients, and a1>a2>a3>0, and β is an error correction factor with a value of 0.698;

Compare the part failure analysis coefficient Wk of the analysis object with P1 and P2, where P1 and P2 are both part failure analysis coefficient thresholds, and P1 is greater than P2:

If the part failure analysis coefficient Wk of the analysis object exceeds P1, mark the corresponding part as a first-level fault part; if the part failure analysis coefficient Wk of the analysis object does not exceed P1, and exceeds P2, then mark the corresponding part as a second-level fault part ; If the part failure analysis coefficient Wk of the analysis object does not exceed P2, then the corresponding part is marked as a third-level fault part; wherein, the application does not exceed or include equal to;

Send the corresponding fault levels of the first-level fault parts, second-level fault parts, and third-level fault parts to the server; after receiving the corresponding fault levels, the server will replace the equipment at the corresponding parts for the first-level fault parts, and replace the corresponding Replace the maintenance method of the part; for the three-level fault part, use the corresponding part according to the historical maintenance method as a reference, and continue to maintain this maintenance method; at the same time, the server generates an operation failure prediction signal and sends the operation failure prediction signal to the operation failure prediction unit;

After the operation fault prediction unit receives the operation fault prediction signal, it will perform fault prediction on the analysis object that performs the real-time glue binding task, judge whether the analysis object has a failure risk during the operation process, and perform fault prediction on it, which reduces the impact of the analysis object failure on the glue. The impact brought by the execution of the installation task is conducive to early fault maintenance and ensures the operating efficiency of the analysis object to the greatest extent;

Collect the growth rate of high-level fault parts changing from low-level fault parts during real-time operation of the analysis object and the number of real-time fault increases corresponding to the parts that have not failed in the historical period, and convert the high-level fault parts into low-level fault parts during the real-time operation of the analysis object The growth rate of the growth rate and the number of real-time fault increases corresponding to the parts that have not failed in the historical time period are compared with the growth rate threshold and the increase number threshold: The second-level fault location or the first-level fault location, the second-level fault location changes to the first-level fault location;

If the growth rate of high-level fault parts changing from low-level fault parts during the real-time operation of the analysis object exceeds the growth rate threshold, or the number of real-time faults corresponding to the parts that have not experienced faults in the historical time period exceeds the increase number threshold, then it is determined that the fault prediction of the analysis object is High failure risk, generate a high failure risk prediction signal and send the high failure risk prediction signal to the server, after the server receives the high failure risk prediction signal, it will suspend the currently unexecuted glue binding task, and execute the real-time glue binding task The speed is reduced, and after the speed is reduced, if there is a failure in the part, the plastic binding will be stopped, and the analysis object will be repaired;

If the growth rate of the transition from high-level fault parts to low-level fault parts during the real-time operation of the analysis object does not exceed the growth rate threshold, and the number of real-time fault increases corresponding to the parts that have not experienced faults in the historical time period does not exceed the increase number threshold, then the fault of the analysis object is determined A low failure risk is predicted, a low failure risk prediction signal is generated, and the low failure risk prediction signal is sent to the server.

The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula close to the real value. The coefficients in the formula are set by those skilled in the art according to the actual situation;

When the present invention is in use, the ladder mark real-time analysis unit analyzes the setting of the real-time ladder mark during the operation of the plywood composite glued equipment, marks the plywood composite glued equipment as the analysis object, sets the label i, and i is a natural number greater than 1, The abnormal signal of the glue binding process and the normal signal of the glue binding process are generated through real-time ladder analysis, and sent to the server; through the glue binding process analysis unit, the glue binding process of the real-time glue binding task is analyzed and detected, and the glue binding process is generated through analysis The normal process signal and the abnormal signal of the plastic binding process are sent to the server; the analysis object is tracked during the maintenance process through the equipment operation tracking unit, and the analysis object is divided into k parts according to the historical operation fault position of the analysis object , k is a natural number greater than 1, the part failure analysis coefficient of the analysis object is obtained through analysis, and the parts are divided into first-level fault parts, second-level fault parts and third-level fault parts according to the comparison of part failure analysis coefficients, and sent to The server: predicts the failure of the analysis object performing the real-time glue binding task by running the failure prediction unit, generates a high failure risk prediction signal and a low failure risk prediction signal through analysis, and sends them to the server.

The preferred embodiments of the invention disclosed above are only to help illustrate the invention. The preferred embodiments do not exhaust all details nor limit the invention to only specific embodiments. Obviously, many modifications and variations can be made based on the contents of this specification. This description selects and specifically describes these embodiments in order to better explain the principle and practical application of the present invention, so that those skilled in the art can well understand and utilize the present invention. The invention is to be limited only by the claims, along with their full scope and equivalents.

Claims (6)

1. An operation management and control system for plywood composite glued equipment based on data analysis, characterized in that it includes a server, and the communication connection of the server includes: a ladder real-time analysis unit, which is used to set the real-time ladder label during the operation of the plywood composite glued equipment To analyze, mark the plywood composite glue binding equipment as the analysis object, set the label i, i is a natural number greater than 1, generate the abnormal signal of the glue binding process and the normal signal of the glue binding process through real-time ladder analysis, and send them to the server; The glue binding process analysis unit is used to analyze and detect the glue binding process of the real-time glue binding task, and generate the normal signal of the glue binding process and the abnormal signal of the glue binding process through analysis, and send them to the server; the equipment operation tracking unit uses In order to track the operation of the analysis object in the maintenance process, analyze according to the history of the analysis object's operation fault position, divide the analysis object into k parts, k is a natural number greater than 1, and obtain the analysis coefficient of the analysis object's part failure through analysis, according to Part failure analysis coefficient comparison divides parts into first-level failure parts, second-level failure parts and third-level failure parts, and sends them to the server; runs the fault prediction unit to perform fault prediction on the analysis objects that perform real-time glue binding tasks , generate a high failure risk prediction signal and a low failure risk prediction signal through analysis, and send them to the server. 2. The operation management and control system of plywood composite binding equipment based on data analysis according to claim 1, characterized in that, the operation process of the ladder real-time analysis unit is as follows: according to the analysis object corresponding to the real-time binding task, the The real-time glue binding task is corresponding to the plywood to set the ladder mark, divide the real-time glue binding task according to the real-time glue binding speed of the analysis object, and distinguish the real-time glue binding task according to the time point, the reduction of the real-time glue binding task at adjacent time points Divide it with the set ladder scalar, and the quotient corresponds to the execution volume of the real-time glue binding task, and the execution volume unit is a group; set the real-time glue binding task ladder estimated execution curve based on the real-time glue binding speed, and substitute the curve into the Cartesian coordinate system, And the X-axis of the Cartesian coordinate system is the time point, and the Y-axis is the ladder scalar. 3. The operation management and control system of plywood composite binding equipment based on data analysis according to claim 2, characterized in that, according to the real-time binding task execution process of the analysis object, the ladder scalars at each time point are obtained and substituted into Build the real-time execution curve of the ladder after the Cartesian coordinate system; collect the curve slope difference between the predicted execution curve of the ladder and the real-time execution curve of the ladder, and the time difference between the two curves corresponding to the same ladder quantity, and compare them Compare them with the curve slope difference threshold range and the time point deviation duration threshold range respectively: if the curve slope difference between the ladder’s predicted execution curve and the ladder’s real-time execution curve for the corresponding time period is not within the curve slope difference threshold range, or both If the time point deviation duration of two curves corresponding to the same ladder scalar value is not within the time point deviation duration threshold range, an abnormal signal of the glue binding process will be generated and sent to the server together with the abnormal signal of the glue binding process and the corresponding abnormal time; if the ladder scale is expected to execute the curve and If the curve slope difference of the corresponding time period in the ladder real-time execution curve is within the curve slope difference threshold range, and the time point deviation duration of the two curves corresponding to the same ladder scalar value is within the time point deviation time length threshold range, then the corresponding time point will be marked as At normal time, a normal signal of the perfect binding process is generated and sent to the server together with the normal signal of the perfect binding process and the corresponding normal time. 4. The operation management and control system of plywood composite gluing equipment based on data analysis according to claim 1, characterized in that, the operation process of the gluing process analysis unit is as follows: the real-time gluing task is collected at any time during the gluing process The points correspond to the maximum rework amount difference and the maximum rework amount increase at adjacent time points, and compare them with the rework amount difference threshold and the rework amount increase threshold respectively: if the real-time glue binding task is in the glue binding process If the corresponding maximum rework amount difference between time points exceeds the rework amount difference threshold, or the maximum rework amount increase at adjacent time points exceeds the rework amount increase threshold, an abnormal signal of the glue binding process is generated and sent to the server; if the maximum rework amount difference corresponding to the real-time glue binding task does not exceed the rework amount difference threshold between time points during the glue binding process, and the maximum rework amount increase at adjacent time points does not exceed the rework amount increase threshold, Then generate a normal signal of the perfect binding process and send the normal signal of the perfect binding process to the server. 5. A data analysis-based operation management and control system for plywood composite gluing equipment according to claim 1, characterized in that the operation process of the equipment operation tracking unit is as follows: the analysis object is obtained at the end point of the current analysis object maintenance time Historical operation time period, the duration of the failure of the part of the analysis object within the historical operation time period and the maintenance frequency of the corresponding part within the failure duration of the part; the average maintenance interval of each part of the analysis object corresponding to the collection of the historical operation time period ; Obtain the part failure analysis coefficient of the analysis object through analysis; compare the part failure analysis coefficient of the analysis object with P1 and P2, where P1 and P2 are the thresholds of the part failure analysis coefficient, and P1 is greater than P2; if the part of the analysis object If the failure analysis coefficient exceeds P1, the corresponding part will be marked as a first-level failure part; if the failure analysis coefficient of the part of the analysis object does not exceed P1, and exceeds P2, the corresponding part will be marked as a second-level failure part; if the part of the analysis object is faulty If the analysis coefficient does not exceed P2, the corresponding part will be marked as a third-level fault part. 6. The operation management and control system of plywood composite glued equipment based on data analysis according to claim 1, characterized in that, the operation process of the operation failure prediction unit is as follows: the high-level fault position changes to low in the real-time operation process of the collected analysis object The growth rate of graded fault parts and the number of real-time faults corresponding to the parts without faults in the historical time period are compared with the growth rate threshold and the increase number threshold respectively: if the analysis object is running in real time If the growth rate of the part exceeds the growth rate threshold, or the number of real-time fault increases corresponding to parts that have not experienced faults in the historical time period exceeds the increase number threshold, a high fault risk prediction signal is generated and sent to the server; if the analysis object is real-time During operation, if the growth rate of the high-level fault position changes to the low-level fault position does not exceed the growth rate threshold, and the number of real-time fault increases corresponding to the parts that have not experienced faults in the historical time period does not exceed the increase number threshold, a low fault risk prediction signal is generated and low The failure risk prediction signal is sent to the server.

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