Door and window processing regulation and control system

Abstract

The invention, which relates to the technical field of door and window processing, discloses a door and window processing regulation and control system comprising a monitoring module, an intelligent regulation and control module, an abnormal activity identification module and an abnormal hidden danger classification and processing module. The monitoring module monitors the size, shape and position of the glass plate in real time through a sensor; and the intelligent regulation and control module is used for regulating and controlling real-time data detected by the sensor and parameters set by the intelligent regulation and control system. According to the method, the cutting process is divided according to the fixed-time-length windows, a real-time monitoring mechanism is established, abnormal activities of the system can be detected in time, abnormal cutting precision is effectively prevented, and the cutting precision is improved through comprehensive processing and analysis of the cutting speed deviation index and the cutting path expected similarity index. The system can quickly generate the cutting precision analysis model, and the abnormal activity of the intelligent regulation and control system is identified through the cutting precision analysis model, so that the stability and the production efficiency of a production line are improved.

Description

[0001] This application is a divisional application of the application filed on July 31, 2024, with application number 202411040801.0 and invention name “A intelligent control system for door and window processing”. Technical Field

[0002] The invention relates to the technical field of door and window processing, and in particular to a door and window processing control system. Background Art

[0003] The door and window processing control system is a system that uses advanced technology and intelligent means to monitor, analyze and adjust various parameters in the door and window processing process in real time. It uses components such as sensors, controllers and software to perceive and collect data on factors such as the operating status of door and window processing equipment, material properties and production environment in real time, and then uses advanced algorithms and models to analyze and optimize, thereby realizing intelligent control and management of the processing process. This system can improve the production efficiency and product quality of door and window processing, reduce waste and loss in the production process, and also reduce labor costs and improve production safety.

[0004] Automatic glass cutting machines play a key role in door and window processing. Their main function is to cut large glass plates into required sizes and shapes through precise cutting operations to meet various specifications and requirements for glass in door and window production. These cut glass pieces will be used to make glass panels for doors and windows, such as windows, door panels or partitions. Automatic glass cutting machines are usually equipped with advanced sensors and intelligent control systems, which can automatically adjust cutting parameters such as length, width and shape according to door and window design drawings and user needs, thereby ensuring that each piece of glass can be accurately cut and maintain high precision. This automated cutting process not only improves production efficiency, but also reduces human operation errors, ensures the quality and safety of glass, and provides a reliable glass processing solution for door and window processing.

[0005] The prior art has the following deficiencies:

[0006] When the intelligent control system used by the automatic glass cutting machine has accuracy abnormalities, serious consequences may occur. First, due to inaccurate cutting precision, the size of the cut glass pieces may not meet the design requirements, making it difficult or even impossible to assemble the door and window frames, seriously affecting the quality and appearance of the products. In addition, accuracy abnormalities may cause the door and window processing production line to produce batches of unqualified products. If batches of unqualified products flow in for a long time, it will cause serious economic losses and reputational impacts to the company.

[0007] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0008] The purpose of the present invention is to provide a door and window processing and control system, which divides the cutting process into fixed time windows and establishes a real-time monitoring mechanism, so as to detect abnormal system activities in time and effectively prevent the occurrence of abnormal cutting accuracy. Through the comprehensive processing and analysis of the cutting speed deviation index and the expected similarity index of the cutting path, the system can quickly generate a cutting accuracy analysis model, and identify abnormal activities of the intelligent control system through the cutting accuracy analysis model, thereby improving the stability and production efficiency of the production line to solve the problems in the above-mentioned background technology.

[0009] In order to achieve the above-mentioned object, the present invention provides the following technical solutions: a door and window processing and control system, including a monitoring module, an intelligent control module, an abnormal activity identification module and an abnormal hidden danger classification and processing module;

[0010] A monitoring module that uses sensors to monitor the size, shape and position of the glass sheet in real time;

[0011] The intelligent control module controls the automatic glass cutting machine to cut the glass sheet through the intelligent control system according to the real-time data detected by the sensor and the parameters set by the intelligent control system;

[0012] The abnormal activity identification module divides the process of the intelligent control system for the automatic glass cutting machine into windows according to fixed time lengths, so that the duration of each fixed time window remains equal. In each fixed time window, a real-time monitoring mechanism is established for the intelligent control system for controlling the automatic glass cutting machine to detect abnormal activities of the intelligent control system;

[0013] The abnormal hidden danger classification and processing module, if abnormal hidden dangers occur in the process of intelligent control of the automatic glass cutting machine by the intelligent control system, the abnormal hidden dangers will be further divided into occasional abnormal hidden dangers, recurrent abnormal hidden dangers and high-risk abnormal hidden dangers, and different types of abnormal hidden dangers will be classified and processed.

[0014] Preferably, the steps of the intelligent control system controlling the automatic glass cutting machine to cut the glass sheet are as follows:

[0015] The intelligent control system receives real-time data from sensors;

[0016] According to the received real-time data and pre-set cutting requirements, the intelligent control system sets the parameters of the cutting machine;

[0017] Based on the received real-time data and the set cutting parameters, the intelligent control system plans the cutting path;

[0018] The intelligent control system sends instructions to the automatic glass cutting machine to perform cutting operations.

[0019] Preferably, the cutting speed, actual cutting path and expected cutting path are obtained when the intelligent control system performs intelligent control on the automatic glass cutting machine, the cutting speed is processed to generate a cutting speed deviation index, and the actual cutting path and the expected cutting path are comprehensively processed to generate an expected cutting path similarity index.

[0020] Preferably, the cutting speed deviation index Cut generated by the intelligent control system in a fixed time window when the intelligent control system performs intelligent control on the automatic glass cutting machine is obtained. Sp and the expected similarity index of the cutting path Man Sim After that, the cutting speed deviates from the index Cut Sp and the expected similarity index of the cutting path Man Sim Establish cutting accuracy analysis model and generate cutting accuracy Φ pr , based on the formula: Where r1 and r2 are the cutting speed deviation index Cut Sp and the expected similarity index of the cutting path Man Sim The preset proportional coefficient, and r1 and r2 are both greater than 0.

[0021] Preferably, the cutting accuracy generated by the intelligent control system in a fixed time window when the automatic glass cutting machine is intelligently controlled is compared and analyzed with a pre-generated cutting accuracy reference threshold, and the result of the comparison and analysis is as follows:

[0022] If the cutting accuracy is greater than or equal to the cutting accuracy reference threshold, a normal cutting signal is generated to continue cutting the glass plate;

[0023] If the cutting accuracy is less than the cutting accuracy reference threshold, an abnormal cutting signal is generated for subsequent abnormal analysis.

[0024] Preferably, the logic of obtaining the cutting speed deviation index is as follows:

[0025] Obtain the optimal cutting speed range per unit time when the intelligent control system performs intelligent control on the automatic glass cutting machine, and calibrate the optimal cutting speed range as [Cut min , Cut max ];

[0026] Under a fixed time window, the actual cutting speed of the glass automatic cutting machine when cutting the glass plate in unit time is obtained, and the actual cutting speed is represented by the function Cu(T) according to the time series, where T represents time;

[0027] The actual cutting speed Cu(T) and the optimal cutting speed range [Cut min , Cut max ] After comparison, the cutting speed deviation index is calculated, and the calculation expression is: In the formula, Cit Sp Indicates the cutting speed deviation index, [T x , T y ] indicates that the actual cutting speed Ci(T) is greater than Cut max Time period, T x <T y , [T m , T n ] indicates that the actual cutting speed Cu(T) is less than Cut min Time period, T m <T n .

[0028] Preferably, the logic for obtaining the expected similarity index of the cutting path is as follows:

[0029] The actual cutting path and expected cutting path are obtained when the intelligent control system performs intelligent control on the automatic glass cutting machine in a fixed time window, and the actual cutting path is represented as a sequence of length n (x1, x2, ..., x n ), where x i represents the position of the i-th cutting point, and represents the expected cutting path as a sequence of length m (y1, y2, ..., y m ), where y j Indicates the position of the jth cutting point;

[0030] The Manhattan distance is calculated based on each cutting point of the actual cutting path and each cutting point of the expected cutting path. The Manhattan distance d(i, j) is calculated by the following formula: Among them, |x i -y j | represents the Manhattan distance between the i-th cutting point of the actual cutting path and the j-th cutting point of the expected cutting path;

[0031] The expected similarity index of the cutting path is calculated by the Manhattan distance d(i, j), and the calculation expression is: In the formula, Man Sim It represents the expected similarity index of the cutting path, indicating the similarity between the actual cutting path and the expected cutting path. The larger the performance value of the expected similarity index of the cutting path, the more similar the actual cutting path is to the expected cutting path, and vice versa.

[0032] Preferably, if the cutting accuracy is less than the cutting accuracy reference threshold value during the intelligent control system's intelligent control of the automatic glass cutting machine, then several cutting accuracies generated subsequently are collected to establish an analysis set for comprehensive analysis. The specific analysis process is as follows:

[0033] By analyzing the cutting accuracy generated in the set, the discrete value of the cutting accuracy and the average value of the cutting accuracy are calculated. The calculation formula is: In the formula, τ1 represents the discrete value of cutting accuracy, τ2 represents the average value of cutting accuracy, represents the cutting accuracy in the analysis set, v represents the subscript of the cutting accuracy in the analysis set, and V represents the total number of cutting accuracy in the analysis set.

[0034] Preferably, the discrete value of cutting accuracy and the average value of cutting accuracy are compared and analyzed with a preset discrete reference threshold of cutting accuracy and a preset reference threshold of cutting accuracy, respectively. The results of the comparison and analysis are as follows:

[0035] If the discrete value of the cutting accuracy is less than the discrete reference threshold of the cutting accuracy and the average value of the cutting accuracy is greater than the reference threshold of the cutting accuracy, an occasional signal is generated to continue cutting the subsequent glass sheets;

[0036] If the cutting accuracy discrete value is greater than or equal to the cutting accuracy discrete reference threshold, a repetitive signal is generated, the corresponding cut glass plate is marked and selected, and the subsequent glass plates are cut continuously;

[0037] If the discrete value of the cutting accuracy is less than the discrete reference threshold of the cutting accuracy and the average value of the cutting accuracy is less than the reference threshold of the cutting accuracy, a high-frequency signal is generated and the machine is shut down for maintenance.

[0038] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0039] The present invention monitors the size, shape and position of the glass plate in real time, and according to the real-time data detected by the sensor and the set parameters, the intelligent control system can accurately control the automatic glass cutting machine to cut, ensuring that the size of the cut glass pieces meets the design requirements, thereby avoiding the difficulty or even the inability to assemble the door and window frames, and ensuring the quality and appearance of the product.

[0040] The present invention divides the cutting process into fixed time windows and establishes a real-time monitoring mechanism, which can detect abnormal system activities in a timely manner and effectively prevent the occurrence of abnormal cutting accuracy. Through the comprehensive processing and analysis of the cutting speed deviation index and the expected similarity index of the cutting path, the system can quickly generate a cutting accuracy analysis model, and identify abnormal activities of the intelligent control system through the cutting accuracy analysis model, thereby improving the stability and production efficiency of the production line.

[0041] The present invention can further identify and process precision anomalies in a timely manner, classify anomalies into occasional, recurring and high-frequency types, and adopt corresponding classification and processing methods. Through the generation of abnormal signals, the system can achieve timely response and processing of abnormal situations, thereby avoiding economic losses and reputation impacts caused by batches of unqualified products entering the market. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0043] Figure 1 The present invention is a module schematic diagram of a door and window processing and control system.

[0044] Figure 2 The present invention is a method flow chart of a door and window processing and control system. DETAILED DESCRIPTION

[0045] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these example embodiments are provided so that the description of the present disclosure will be more comprehensive and complete, and the concept of the example embodiments will be fully conveyed to those skilled in the art.

[0046] The present invention provides Figure 1 A door and window processing and control system shown includes a monitoring module, an intelligent control module, an abnormal activity recognition module, and an abnormal hidden danger classification and processing module;

[0047] A monitoring module that uses sensors to monitor the size, shape and position of the glass sheet in real time;

[0048] In the process of door and window processing, it is crucial to monitor the size, shape and position of glass panels in real time through sensors. The following are some commonly used sensors and their functions (including but not limited to):

[0049] Laser distance sensor: The laser distance sensor can accurately measure the size of the glass plate, including length and width, by emitting a laser beam and measuring the time for the laser to reflect. It can achieve non-contact measurement and has the characteristics of high precision and fast response.

[0050] Photoelectric sensor: Photoelectric sensor can detect the edge of the glass sheet or the position of specific marks to determine the shape and position of the glass sheet. It is usually used to detect the edge of the glass sheet or specific features of the edge so that the system can accurately identify the position and shape of the glass sheet.

[0051] Camera sensor (visual sensor): The camera sensor can capture images of glass plates and analyze and process the images through image processing algorithms to obtain the size, shape and position information of the glass plates. It can achieve high-precision glass plate detection and positioning and is suitable for glass plates with complex shapes and special requirements.

[0052] Pressure sensor: The pressure sensor can be installed on the cutting table or clamping device of the cutting machine to monitor the pressure of the glass sheet. By monitoring the pressure changes between the glass sheet and the cutting table, the system can detect the position and shape of the glass sheet in real time and adjust the cutting parameters to ensure the accuracy and stability of the cutting.

[0053] Acceleration sensor: The acceleration sensor can detect the vibration and movement state of the cutting machine, so as to judge the working state and cutting quality during the cutting process. It can be used to monitor the movement trajectory and speed of the cutting machine, and to judge whether there are any abnormal conditions during the cutting process.

[0054] Through the synergistic effect of these sensors, the intelligent control system can accurately monitor and locate the size, shape and position of the glass plate, thereby achieving efficient, precise and stable glass cutting processing.

[0055] The intelligent control module controls the automatic glass cutting machine to cut the glass sheet through the intelligent control system according to the real-time data detected by the sensor and the parameters set by the intelligent control system;

[0056] The steps for the intelligent control system to control the automatic glass cutting machine to cut the glass plate are as follows:

[0057] The intelligent control system receives real-time data from sensors;

[0058] The real-time data received from the sensors includes the size, shape, position and other relevant parameters of the glass sheet. This data will be used to calculate and adjust the parameters during the cutting process.

[0059] According to the received real-time data and pre-set cutting requirements, the intelligent control system sets the parameters of the cutting machine;

[0060] Parameters include cutting speed, tool pressure, cutting path, etc. These parameters will be adjusted according to real-time conditions to ensure the accuracy and efficiency of the cutting process.

[0061] Based on the received real-time data and the set cutting parameters, the intelligent control system plans the cutting path;

[0062] This includes determining the cutting start point, cutting end point and cutting path to ensure that the cutting process can cover all the parts of the glass sheet that need to be cut and avoid unnecessary waste.

[0063] The intelligent control system sends instructions to the automatic glass cutting machine to perform cutting operations.

[0064] The abnormal activity identification module divides the process of the intelligent control system for the automatic glass cutting machine into windows according to fixed time lengths, so that the duration of each fixed time window remains equal. In each fixed time window, a real-time monitoring mechanism is established for the intelligent control system for controlling the automatic glass cutting machine to detect abnormal activities of the intelligent control system;

[0065] The cutting speed, actual cutting path and expected cutting path of the glass automatic cutting machine are obtained when the intelligent control system performs intelligent control on the glass automatic cutting machine, the cutting speed is processed to generate a cutting speed deviation index, and the actual cutting path and the expected cutting path are comprehensively processed to generate an expected similarity index of the cutting path;

[0066] When the cutting speed is too high or too low, the cutting accuracy of the glass sheet may be abnormal. Although the reasons for the abnormality are different, both have an important impact on the cutting quality. First, when the cutting speed is too high, the tool may not be able to fully contact the glass plate, resulting in reduced cutting quality. Fast cutting speed may cause vibration and instability during the cutting process, which may lead to uneven or inaccurate cuts. When the cutting speed is too low, the tool may stay in the same position for a long time, causing excessive heat to the glass plate, causing the glass plate around the cut to burn or deform. In addition, if the cutting speed is too low, the cut may not be smooth enough, and the contact time between the tool and the glass plate is too long, which may easily produce cutting marks, thus affecting the flatness and accuracy of the cut.

[0067] Therefore, by obtaining the cutting speed when the intelligent control system performs intelligent control on the automatic glass cutting machine and analyzing the cutting speed, the problem of abnormal cutting speed can be intelligently perceived.

[0068] The logic of obtaining the cutting speed deviation index is as follows:

[0069] Obtain the optimal cutting speed range per unit time when the intelligent control system performs intelligent control on the automatic glass cutting machine, and calibrate the optimal cutting speed range as [Cut min , Cut max ];

[0070] Manufacturers usually provide recommendations on the optimal cutting speed range in the user manual or technical specifications of the equipment. These recommendations are based on a comprehensive consideration of equipment performance, material properties and processing requirements, and can serve as an important reference for setting the optimal cutting speed range.

[0071] Under a fixed time window, the actual cutting speed of the glass automatic cutting machine when cutting the glass plate in unit time is obtained, and the actual cutting speed is represented by the function Cu(T) according to the time series, where T represents time;

[0072] The actual cutting speed Cu(T) and the optimal cutting speed range [Cut min , Cut max ] After comparison, the cutting speed deviation index is calculated, and the calculation expression is: In the formula, Cit Sp Indicates the cutting speed deviation index, [Y x , T y ] indicates that the actual cutting speed Cu(T) is greater than Cut max Time period, T x <T y , [T m , T n ] indicates that the actual cutting speed Cu(T) is less than Cut min Time period, T m <T n .

[0073] It can be seen from the calculation formula of the cutting speed deviation index that, within a fixed time window, the larger the cutting speed deviation index generated by the automatic glass cutting machine when cutting the glass plate, the greater the potential risk of abnormal cutting accuracy of the glass plate, and vice versa.

[0074] Deviations between the actual cutting path and the system's expected cutting path may cause abnormalities in the glass sheet cutting accuracy. First, when there is a deviation between the actual cutting path and the expected path, the glass cutting position may be inaccurate, and the size or shape may not meet the design requirements. This deviation may be caused by mechanical structure problems, sensor errors, or inaccurate system algorithms. Even if the deviation is small, the cumulative result will cause the cutting result to be inconsistent with expectations, affecting the cutting accuracy. Secondly, the deviation of the actual cutting path from the expected path may cause the quality of the glass sheet cutting to deteriorate. For example, excessive deviation may cause burrs, breakage, or unevenness on the edge of the glass during cutting, affecting the quality of the cut. This quality problem not only affects the appearance, but may also affect the structural strength and safety of the glass sheet, increasing the risk of use.

[0075] Therefore, by obtaining the actual cutting path and the expected cutting path when the intelligent control system performs intelligent control on the automatic glass cutting machine, and performing deviation analysis on the actual cutting path and the expected cutting path, the abnormal problem of deviation between the actual cutting path and the expected cutting path can be intelligently perceived.

[0076] The logic for obtaining the expected similarity index of the cutting path is as follows:

[0077] The actual cutting path and expected cutting path are obtained when the intelligent control system performs intelligent control on the automatic glass cutting machine in a fixed time window, and the actual cutting path is represented as a sequence of length n (x1, x2, ..., x n ), where x i represents the position of the i-th cutting point, and represents the expected cutting path as a sequence of length m (y1, y2, ..., y m ), where y j Indicates the position of the jth cutting point;

[0078] The Manhattan distance is calculated based on each cutting point of the actual cutting path and each cutting point of the expected cutting path. The Manhattan distance d(i, j) is calculated by the following formula: Among them, |x i -y j | represents the Manhattan distance between the i-th cutting point of the actual cutting path and the j-th cutting point of the expected cutting path;

[0079] The expected similarity index of the cutting path is calculated by the Manhattan distance d(i, j), and the calculation expression is: In the formula, Man Sim It represents the expected similarity index of the cutting path, indicating the similarity between the actual cutting path and the expected cutting path. The larger the performance value of the expected similarity index of the cutting path, the more similar the actual cutting path is to the expected cutting path, and vice versa.

[0080] It can be seen from the calculation formula of the expected similarity index of the cutting path that, under a fixed time window, the larger the expected similarity index of the cutting path generated by the automatic glass cutting machine when cutting the glass plate, the smaller the potential risk of abnormal cutting accuracy of the glass plate; conversely, the greater the potential risk of abnormal cutting accuracy of the glass plate.

[0081] Get the cutting speed deviation index Cut generated by the intelligent control system in a fixed time window when it performs intelligent control on the automatic glass cutting machine Sp and the expected similarity index of the cutting path Man Sim After that, the cutting speed deviates from the index Cut Sp and the expected similarity index of the cutting path Man Sim Establish cutting accuracy analysis model and generate cutting accuracy Φ pr , based on the formula: Where r1 and r2 are the cutting speed deviation index Cut Sp and the expected similarity index of the cutting path Man SimThe preset proportional coefficient, and r1 and r2 are both greater than 0.

[0082] It can be seen from the calculation formula that under a fixed time window, the greater the performance value of the cutting speed deviation index generated by the automatic glass cutting machine when cutting the glass plate, the smaller the expected similarity index of the cutting path, that is, the generated cutting accuracy Φ pr The smaller the performance value, the greater the risk of abnormal cutting accuracy of the glass plate. The smaller the performance value of the cutting speed deviation index generated by the automatic glass cutting machine when cutting the glass plate, the greater the expected similarity index of the cutting path, that is, the generated cutting accuracy Φ pr The larger the performance value is, the smaller the hidden danger of abnormal cutting accuracy of the glass plate is.

[0083] The cutting accuracy generated by the intelligent control system in a fixed time window when the glass automatic cutting machine is intelligently controlled is compared and analyzed with the pre-generated cutting accuracy reference threshold. The results of the comparison and analysis are as follows:

[0084] If the cutting accuracy is greater than or equal to the cutting accuracy reference threshold, a normal cutting signal is generated. When the intelligent control system performs intelligent control on the automatic glass cutting machine to generate a normal cutting signal, it indicates that the hidden danger of abnormal cutting accuracy of the glass plate is small, and further indicates that the intelligent control system performs intelligent control on the automatic glass cutting machine to achieve normal cutting of the glass plate, and the glass plate continues to be cut;

[0085] If the cutting accuracy is less than the cutting accuracy reference threshold, an abnormal cutting signal is generated. When the intelligent control system performs intelligent control on the automatic glass cutting machine and generates an abnormal cutting signal, it indicates that there is a great risk of abnormal cutting accuracy of the glass plate. It further indicates that the intelligent control system may not be able to perform normal cutting of the glass plate when performing intelligent control on the automatic glass cutting machine. Subsequent abnormal analysis is performed.

[0086] Abnormal hidden danger classification and processing module: if abnormal hidden dangers occur during the intelligent control system's intelligent control of the automatic glass cutting machine, the abnormal hidden dangers are further classified into occasional abnormal hidden dangers, recurrent abnormal hidden dangers and high-risk abnormal hidden dangers, and different types of abnormal hidden dangers are classified and processed;

[0087] If the cutting accuracy of the glass automatic cutting machine is less than the cutting accuracy reference threshold during the intelligent control system's intelligent control of the glass automatic cutting machine, then several cutting accuracies generated subsequently are collected to establish an analysis set for comprehensive analysis. The specific analysis process is as follows:

[0088] By analyzing the cutting accuracy generated in the set, the discrete value of the cutting accuracy and the average value of the cutting accuracy are calculated. The calculation formula is: In the formula, τ1 represents the discrete value of cutting accuracy, τ2 represents the average value of cutting accuracy, represents the cutting accuracy in the analysis set, v represents the subscript of the cutting accuracy in the analysis set, and V represents the total number of cutting accuracy in the analysis set.

[0089] The discrete value of cutting accuracy and the average value of cutting accuracy are compared and analyzed with the preset discrete reference threshold of cutting accuracy and the preset reference threshold of cutting accuracy respectively. The results of the comparison and analysis are as follows:

[0090] If the discrete value of cutting accuracy is less than the discrete reference threshold of cutting accuracy and the average value of cutting accuracy is greater than the reference threshold of cutting accuracy, an occasional signal is generated. When an occasional signal is generated, it indicates that there are occasional abnormal risks when the intelligent control system performs intelligent control on the automatic glass cutting machine. The occasional abnormal risks indicate that occasional abnormal risks will occur when the intelligent control system performs intelligent control on the automatic glass cutting machine, and will not affect the cutting accuracy of the glass plate. For the occasional abnormal risks, the subsequent glass plates will continue to be cut;

[0091] If the discrete value of the cutting accuracy is greater than or equal to the discrete reference threshold of the cutting accuracy, a repetitive signal is generated. When a repetitive signal is generated, it indicates that there are repetitive abnormal hidden dangers when the intelligent control system performs intelligent control on the automatic glass cutting machine. The repetitive abnormal hidden danger indicates that when the intelligent control system performs intelligent control on the automatic glass cutting machine, abnormal hidden dangers sometimes occur and sometimes are normal, which may affect the cutting accuracy of the glass plate. For the repetitive abnormal hidden dangers, the corresponding cut glass plates are marked and selected, and the subsequent glass plates are cut continuously;

[0092] If the discrete value of cutting accuracy is less than the discrete reference threshold of cutting accuracy and the average value of cutting accuracy is less than the reference threshold of cutting accuracy, a high-frequency signal is generated. When a high-frequency signal is generated, it indicates that there are high-incidence abnormal risks when the intelligent control system performs intelligent control on the automatic glass cutting machine. High-incidence abnormal risks indicate that high-frequency abnormal risks will occur when the intelligent control system performs intelligent control on the automatic glass cutting machine, which is likely to affect the cutting accuracy of the glass plate. For high-incidence abnormal risks, the machine should be shut down for maintenance.

[0093] The present invention monitors the size, shape and position of the glass plate in real time, and according to the real-time data detected by the sensor and the set parameters, the intelligent control system can accurately control the automatic glass cutting machine to cut, ensuring that the size of the cut glass pieces meets the design requirements, thereby avoiding the difficulty or even the inability to assemble the door and window frames, and ensuring the quality and appearance of the product.

[0094] The present invention divides the cutting process into fixed time windows and establishes a real-time monitoring mechanism, which can detect abnormal system activities in a timely manner and effectively prevent the occurrence of abnormal cutting accuracy. Through the comprehensive processing and analysis of the cutting speed deviation index and the expected similarity index of the cutting path, the system can quickly generate a cutting accuracy analysis model, and identify abnormal activities of the intelligent control system through the cutting accuracy analysis model, thereby improving the stability and production efficiency of the production line.

[0095] The present invention can further identify and process precision anomalies in a timely manner, classify anomalies into occasional, recurring and high-frequency types, and adopt corresponding classification and processing methods. Through the generation of abnormal signals, the system can achieve timely response and processing of abnormal situations, thereby avoiding economic losses and reputation impacts caused by batches of unqualified products entering the market.

[0096] 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.

[0097] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0098] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0099] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0100] In the several embodiments provided in the present application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0101] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0102] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0103] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks or optical disks.

[0104] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0105] The above description is only by way of illustration of certain exemplary embodiments of the present invention. It is undoubted that those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the above drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A door and window processing and control system, characterized in that: It includes monitoring module, intelligent control module, abnormal activity identification module and abnormal hidden danger classification and processing module; A monitoring module that uses sensors to monitor the size, shape and position of the glass sheet in real time; The intelligent control module controls the automatic glass cutting machine to cut the glass sheet through the intelligent control system according to the real-time data detected by the sensor and the parameters set by the intelligent control system; The abnormal activity identification module divides the process of the intelligent control system for the automatic glass cutting machine into windows according to fixed time lengths, so that the duration of each fixed time window remains equal. In each fixed time window, a real-time monitoring mechanism is established for the intelligent control system for controlling the automatic glass cutting machine to detect abnormal activities of the intelligent control system; The cutting speed, actual cutting path and expected cutting path of the glass automatic cutting machine are obtained when the intelligent control system performs intelligent control on the glass automatic cutting machine, the cutting speed is processed to generate a cutting speed deviation index, and the actual cutting path and the expected cutting path are comprehensively processed to generate an expected similarity index of the cutting path; Get the cutting speed deviation index Cut generated by the intelligent control system in a fixed time window when it performs intelligent control on the automatic glass cutting machine Sp and the expected similarity index of the cutting path Maxn Sim After that, the cutting speed deviates from the index Cut Sp and the expected similarity index of the cutting path Man Sim Establish cutting accuracy analysis model and generate cutting accuracy Φ pr , based on the formula: Where r1 and r2 are the cutting speed deviation index Cut Sp and the expected similarity index of the cutting path Man Sim The preset proportional coefficient, and r1 and r2 are both greater than 0; The cutting accuracy generated by the intelligent control system in a fixed time window when the glass automatic cutting machine is intelligently controlled is compared and analyzed with the pre-generated cutting accuracy reference threshold. The results of the comparison and analysis are as follows: If the cutting accuracy is greater than or equal to the cutting accuracy reference threshold, a normal cutting signal is generated to continue cutting the glass plate; If the cutting accuracy is less than the cutting accuracy reference threshold, an abnormal cutting signal is generated for subsequent abnormal analysis; The logic of obtaining the cutting speed deviation index is as follows: Obtain the optimal cutting speed range per unit time when the intelligent control system performs intelligent control on the automatic glass cutting machine, and calibrate the optimal cutting speed range as [Cut min , Cut max ]; Under a fixed time window, the actual cutting speed of the glass automatic cutting machine when cutting the glass plate in unit time is obtained, and the actual cutting speed is represented by the function Cu(T) according to the time series, where T represents time; The actual cutting speed Cu(T) and the optimal cutting speed range [Cut min , Cut max ] After comparison, the cutting speed deviation index is calculated, and the calculation expression is: In the formula, Cut Sp Indicates the cutting speed deviation index, [T x , T y ] indicates that the actual cutting speed Cu(T) is greater than Cut max Time period, T x <T y , [T m , T n ] indicates that the actual cutting speed Cu(T) is less than Cut min Time period, T m <T n ; The logic for obtaining the expected similarity index of the cutting path is as follows: The actual cutting path and expected cutting path are obtained when the intelligent control system performs intelligent control on the automatic glass cutting machine in a fixed time window, and the actual cutting path is represented as a sequence of length n (x1, x2, ..., x n ), where x i represents the position of the i-th cutting point, and represents the expected cutting path as a sequence of length m (y1, y2, ..., y m ), where y j Indicates the position of the jth cutting point; The Manhattan distance is calculated based on each cutting point of the actual cutting path and each cutting point of the expected cutting path. The Manhattan distance d(i, j) is calculated by the following formula: Among them, |x i -y j | represents the Manhattan distance between the i-th cutting point of the actual cutting path and the j-th cutting point of the expected cutting path; The expected similarity index of the cutting path is calculated by the Manhattan distance d(i, j), and the calculation expression is: In the formula, Man Sim It indicates the expected similarity index of the cutting path, which indicates the similarity between the actual cutting path and the expected cutting path. The larger the value of the expected similarity index of the cutting path, the more similar the actual cutting path is to the expected cutting path, and vice versa. The abnormal hidden danger classification and processing module, if abnormal hidden dangers occur in the process of intelligent control of the automatic glass cutting machine by the intelligent control system, the abnormal hidden dangers will be further divided into occasional abnormal hidden dangers, recurrent abnormal hidden dangers and high-risk abnormal hidden dangers, and different types of abnormal hidden dangers will be classified and processed.

2. A door and window processing and control system according to claim 1, characterized in that: If the cutting accuracy of the glass automatic cutting machine is less than the cutting accuracy reference threshold during the intelligent control system's intelligent control of the glass automatic cutting machine, then several cutting accuracies generated subsequently are collected to establish an analysis set for comprehensive analysis. The specific analysis process is as follows: By analyzing the cutting accuracy generated in the set, the discrete value of the cutting accuracy and the average value of the cutting accuracy are calculated. The calculation formula is: In the formula, τ1 represents the discrete value of cutting accuracy, τ2 represents the average value of cutting accuracy, represents the cutting accuracy in the analysis set, v represents the subscript of the cutting accuracy in the analysis set, and V represents the total number of cutting accuracy in the analysis set.

3. A door and window processing and control system according to claim 1, characterized in that: The discrete value of cutting accuracy and the average value of cutting accuracy are compared and analyzed with the preset discrete reference threshold of cutting accuracy and the preset reference threshold of cutting accuracy respectively. The results of the comparison and analysis are as follows: If the cutting accuracy discrete value is less than the cutting accuracy discrete reference threshold and the cutting accuracy average value is greater than the cutting accuracy reference threshold, an occasional signal is generated to continue cutting the subsequent glass plates.

4. A door and window processing and control system according to claim 3, characterized in that: If the cutting accuracy discrete value is greater than or equal to the cutting accuracy discrete reference threshold, a repetitive signal is generated, the corresponding cut glass plate is marked and selected, and the subsequent glass plates are cut continuously.

5. A door and window processing and control system according to claim 3, characterized in that: If the discrete value of the cutting accuracy is less than the discrete reference threshold of the cutting accuracy and the average value of the cutting accuracy is less than the reference threshold of the cutting accuracy, a high-frequency signal is generated and the machine is shut down for maintenance.

6. A door and window processing and control system according to claim 1, characterized in that: The steps for the intelligent control system to control the automatic glass cutting machine to cut the glass plate are as follows: The intelligent control system receives real-time data from sensors; According to the received real-time data and pre-set cutting requirements, the intelligent control system sets the parameters of the cutting machine; Based on the received real-time data and the set cutting parameters, the intelligent control system plans the cutting path; The intelligent control system sends instructions to the automatic glass cutting machine to perform cutting operations.

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