Remote monitoring method for numerical control machine tool

Abstract

The invention discloses a numerical control machine tool remote monitoring method and system, and relates to the technical field of data analysis, and the method comprises the following steps: judging the operation state of a machine tool, executing a first operation, calculating the similarity of finished products, setting a similarity threshold value, carrying out the grading of the quality of historical finished products, and building a first mapping relation; screening production machine tools according to the current finished product grade, and configuring a first production strategy. By monitoring the operation state and historical finished product data of the machine tool, the problems affecting the production efficiency are found and solved in time, the similarity of the finished products is calculated through the historical finished product data, the product quality problems can be recognized and controlled easily, preventive maintenance is achieved by monitoring the operation data of the machine tool, and the production efficiency is improved. Production machine tools are screened according to the current finished product grade, corresponding production strategies are configured, the flexibility and response speed of a production line are improved, the requirement of maintenance personnel on site is reduced through remote monitoring and fault diagnosis, and the manpower and material resource cost is saved.

Description

Technical Field

[0001] The present invention relates to the technical field of data analysis, and in particular to a remote monitoring method for a numerically controlled machine tool. Background Art

[0002] In recent years, the CNC machine tool industry is undergoing a transformation from traditional manufacturing to digitalization, networking, and intelligence. By integrating sensors and Internet of Things technology, remote monitoring, fault prediction, and automated production are achieved, which greatly improves production efficiency and precision. In terms of intelligence, the focus will be on developing deep integration with artificial intelligence and big data to enhance the intelligence level of machine tools.

[0003] At present, a control method and a CNC machine tool based on visual control are disclosed in a Chinese invention patent with publication number CN115390509A. The method determines whether the material is in the processing area through an air gap detection signal. If so, a camera device is called to shoot the processing area to obtain a second image; whether the material is in the processing area is determined according to the second image, and if so, the model of the material and the corresponding processing procedure of the material are obtained according to the second image; the control module controls the CNC machine tool to execute the corresponding processing procedure on the material, but the related technology does not reasonably allocate and schedule the machine tools according to temporary production tasks, which is not conducive to the speed and flexibility of production. The machine tools are not judged according to historical big data and the machine tools that can be used for production are not screened, which is easy to cause erroneous production, thereby reducing economic benefits. Summary of the invention

[0004] The technical problem solved by the present invention is that the related technology does not reasonably allocate and schedule machine tools according to temporary production tasks, which is not conducive to the rapidity and flexibility of production. It does not judge the status of machine tools based on historical big data and screen the machine tools that can be used for production, which easily causes erroneous production and thus reduces economic benefits.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: In the first aspect, a method for remote monitoring of a CNC machine tool comprises the following steps: Step S100, numbering the machine tools, and matching the corresponding historical operation data and historical finished product data according to the numbered machine tools; Step S200, acquiring historical operation data and historical finished product data corresponding to any machine tool, determining the operation status of the machine tool according to the machine tool operation data, and performing a first operation according to the operation status of the machine tool; Step S300, in response to the first operation, calculating the finished product similarity according to the historical finished product data, setting a similarity threshold, classifying the quality of the historical finished products according to the similarity threshold, obtaining the historical finished product grades, and establishing a first mapping relationship according to the historical finished product grades; Step S400, according to the first mapping relationship, obtain the current machine tool number and the corresponding current finished product level, filter the production machine tools according to the current finished product level, obtain the historical operation data corresponding to the production machine tools, and configure the first production strategy according to the historical operation data.

[0006] As a preferred solution of the method for remote monitoring of a CNC machine tool according to the present invention, step S100 includes the following sub-steps: Step S101, numbering the machine tools, where the numbers are natural numbers; Step S102, calling up a production database, adding a data machine tool number to the production database, and matching the historical operation data and historical finished product data corresponding to the first time period; The historical operation data includes historical current, historical production time, historical linear axis straightness error, historical linear axis perpendicularity error, historical rotary axis straightness error, historical spindle parallelism error, historical table flatness error and historical table parallelism error; The historical production duration is expressed as the production duration of a single part; The historical finished product data includes historical part models and historical finished product images.

[0007] As a preferred solution of the method for remote monitoring of a CNC machine tool described in the present invention, the logic of the numbering includes: A top view of the interior of a factory building is obtained, and the top view is filtered and grayed to obtain a first top view, and shape features of the first top view are extracted, recorded as first features. A standard top view of a machine tool is obtained, and shape features of the standard top view of the machine tool are extracted, recorded as second features. Similarity between the first feature and the second feature is calculated, recorded as first similarity, and a first value is set as a similarity threshold. The first similarity is compared with the first value to obtain a first comparison result, wherein the first comparison result includes that the first similarity is greater than or equal to the first value, and the first similarity is less than the first value. When the first similarity threshold is greater than or equal to the first similarity threshold, an image portion corresponding to the shape features is obtained, and the image portions are numbered. The calculation order of the first similarity in the first top view is from left to right and from top to bottom, wherein the priority from left and right is greater than the priority from top to bottom.

[0008] As a preferred solution of the method for remote monitoring of a CNC machine tool according to the present invention, step S200 includes the following sub-steps: Step S201, obtaining historical operation data and historical finished product data corresponding to any machine tool; Step S202, judging the operating state of the machine tool according to the machine tool operating data, wherein the operating state includes a normal state and an abnormal state; Step S203, performing a first operation according to the operating status of the machine tool, wherein the first operation includes sending a first maintenance signal and jumping to a next numbered machine tool, or performing a first analysis on historical operating data and historical finished product data of the machine tool.

[0009] As a preferred solution of the method for remote monitoring of a CNC machine tool described in the present invention, the judgment logic of the operating state includes: Obtain a machine tool number, retrieve a machine tool database, input the machine tool number into the machine tool database, obtain a rated current, obtain a historical current within a first time period, compare each historical current with the rated current, select a historical current whose value is greater than or equal to the rated current, and count the historical duration of the historical current whose value is greater than or equal to the rated current, set a second value as a historical duration threshold, and when the historical duration is greater than or equal to the second value, set the operating state to an abnormal state, otherwise, set the operating state to a normal state; The execution logic of the first operation includes: Obtain the operating status. When the operating status is normal, set the first operation to perform a first analysis on the historical operating data and historical finished product data of the machine tool. When the operating status is abnormal, set the first operation to send a first maintenance signal and jump to the next numbered machine tool. The next numbered machine tool is represented as the machine tool with the next number after the machine tool number.

[0010] As a preferred solution of the method for remote monitoring of a CNC machine tool according to the present invention, step S300 includes the following sub-steps: Step S301, when the operating state is a normal state, in response to a first operation, performing a first analysis on the historical operating data and historical finished product data of the machine tool; Step S302, obtaining historical finished product pictures and historical finished product models, extracting shape feature quantities of the historical finished product pictures, recording them as third feature quantities, retrieving a finished product database, inputting the historical finished product models into the finished product database, matching standard finished product pictures corresponding to the historical finished product models, extracting fourth feature quantities of the standard finished product pictures, and calculating finished product similarity between the third feature quantity and the fourth feature quantity according to a cosine similarity formula; Step S304, setting the third value and the fourth value as the finished product similarity threshold, and classifying the quality of the historical finished products according to the finished product similarity threshold to obtain the historical finished product grade, wherein the historical finished product grade includes a first grade, a second grade and a third grade, and the finished product quality represented by the first grade, the second grade and the third grade is in descending order; Step S305, establish a first mapping relationship between the historical finished product model and the machine tool number and the historical finished product grade. The first mapping relationship is used to associate the machine tool number, the historical finished product data and the historical finished product grade. Through the first mapping relationship, the finished product model is obtained to obtain the machine tool number and the finished product grade.

[0011] As a preferred solution of the method for remote monitoring of a CNC machine tool according to the present invention, step S400 includes the following sub-steps: Step S401, obtaining the current part model and current production quantity; Step S402, obtaining a first mapping relationship, inputting the current part model into the first mapping relationship, obtaining a machine tool number and a historical finished product level corresponding to the current model, and recording them as the current machine tool number and the corresponding current finished product level respectively; Step S403, screening production machine tools according to the current finished product grade, the screening logic of the production machine tools includes: traversing the current quality grades, selecting the machine tools whose current quality grade is the third grade, and recording them as production machine tools; Step S404, obtaining historical operation data corresponding to the production machine tool, and configuring a first production strategy according to the historical operation data, wherein the configuration logic of the first production strategy includes: Obtain the historical production duration corresponding to the production machine tool, recorded as the first duration, obtain the current production quantity, obtain the lowest common multiple of the first durations corresponding to each production machine tool, recorded as the first value, calculate the ratio of the first value to the first duration corresponding to each production machine tool, recorded as the first quantity, the first quantity is represented by the number of parts produced by the machine tool in the same time, calculate the sum of the first quantities, recorded as the first sum, and compare the first sum with the current production quantity; When the first sum is greater than or equal to the current production quantity, the first time durations are sorted in descending order, and the first quantity corresponding to each machine tool is allocated according to the descending sorting order until the current production quantity is allocated and the allocation is stopped; When the first sum is less than the current production quantity, a ratio of the current production quantity to the first sum is calculated and recorded as a first ratio; When the first ratio is a natural number, allocating a first quantity corresponding to each machine tool; When the first ratio is not a natural number, take the integer and remainder of the first ratio, the integer represents the number of production rounds, and the remainder represents the excess production quantity. Within the integer number of production rounds, allocate the first quantity corresponding to each machine tool. When the integer number of production rounds is exceeded, sort the first time length in descending order, and allocate the first quantity corresponding to each machine tool in the descending sorting order until the remainder is allocated and stops allocating.

[0012] In a second aspect, a remote monitoring system for a CNC machine tool includes an acquisition module, an analysis module, and a configuration module; The acquisition module numbers the machine tools and matches the corresponding historical operation data and historical finished product data according to the numbered machine tools; The analysis module obtains historical operation data and historical finished product data corresponding to any machine tool, determines the operation status of the machine tool according to the machine tool operation data, performs a first operation according to the operation status of the machine tool, calculates the finished product similarity according to the historical finished product data in response to the first operation, sets a similarity threshold, grades the historical finished product quality according to the similarity threshold, obtains the historical finished product grade, and establishes a first mapping relationship according to the historical finished product grade; The configuration module obtains the current machine tool number and the corresponding current finished product level according to the first mapping relationship, screens the production machine tools according to the current finished product level, obtains the historical operation data corresponding to the production machine tools, and configures the first production strategy according to the historical operation data.

[0013] In a third aspect, the present invention provides an electronic device comprising a memory, a processor and storage in the memory, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the steps in any one of the methods described above are executed.

[0014] In a fourth aspect, the present invention provides a storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps in any one of the methods described above are executed.

[0015] The beneficial effects of the present invention are as follows: by monitoring the operating status of machine tools and historical finished product data, problems affecting production efficiency can be discovered and resolved in a timely manner, such as insufficient processing efficiency caused by a feed rate lower than expected; the similarity of finished products can be calculated using historical finished product data, and similarity thresholds can be set for quality grade classification, which helps to identify and control product quality problems and reduce product quality problems caused by violations of process regulations; by monitoring the operating data of machine tools, potential failures and maintenance needs can be predicted, thereby achieving preventive maintenance and reducing unexpected downtime and maintenance costs; by monitoring the operating data of machine tools, potential failures and maintenance needs can be predicted, thereby achieving preventive maintenance and reducing unexpected downtime and maintenance costs; production machine tools can be screened according to the current finished product grade, and corresponding production strategies can be configured to quickly adapt to changes in production needs and improve the flexibility and response speed of the production line; remote monitoring and fault diagnosis reduce the need for maintenance personnel to go to the site, saving manpower and material costs, while providing customers with faster services and reducing their losses. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1A basic flow chart of a method for remote monitoring of a CNC machine tool provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0017] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, but not all of the embodiments.

[0018] Example, see Figure 1 , as an embodiment of the present invention, provides a method for remote monitoring of a CNC machine tool, comprising the following steps: Step S100, numbering the machine tools, and matching the corresponding historical operation data and historical finished product data according to the numbered machine tools; Step S200, acquiring historical operation data and historical finished product data corresponding to any machine tool, determining the operation status of the machine tool according to the machine tool operation data, and performing a first operation according to the operation status of the machine tool; Step S300, in response to the first operation, calculating the finished product similarity according to the historical finished product data, setting a similarity threshold, classifying the quality of the historical finished products according to the similarity threshold, obtaining the historical finished product grades, and establishing a first mapping relationship according to the historical finished product grades; Step S400, according to the first mapping relationship, obtain the current machine tool number and the corresponding current finished product level, filter the production machine tools according to the current finished product level, obtain the historical operation data corresponding to the production machine tools, and configure the first production strategy according to the historical operation data.

[0019] The present invention monitors the operating status of machine tools and historical finished product data to promptly discover and solve problems that affect production efficiency, such as the situation where the feed rate is lower than expected, resulting in insufficient processing efficiency. The historical finished product data is used to calculate the finished product similarity, and a similarity threshold is set to divide the quality grade. This helps to identify and control product quality problems and reduce product quality problems caused by violations of process regulations. By monitoring the operating data of machine tools, potential failures and maintenance needs are predicted, thereby achieving preventive maintenance and reducing unexpected downtime and maintenance costs. By monitoring the operating data of machine tools, potential failures and maintenance needs are predicted, thereby achieving preventive maintenance and reducing unexpected downtime and maintenance costs. Production machine tools are screened according to the current finished product grade, and corresponding production strategies are configured to quickly adapt to changes in production needs, thereby improving the flexibility and response speed of the production line. Remote monitoring and fault diagnosis reduce the need for maintenance personnel to go to the site, saving manpower and material costs, while providing customers with faster services and reducing their losses.

[0020] The step S100 includes the following sub-steps: Step S101, numbering the machine tools, where the numbers are natural numbers; Step S102, calling up a production database, adding a data machine tool number to the production database, and matching the historical operation data and historical finished product data corresponding to the first time period; The historical operation data includes historical current, historical production time, historical linear axis straightness error, historical linear axis perpendicularity error, historical rotary axis straightness error, historical spindle parallelism error, historical table flatness error and historical table parallelism error; The historical production duration is expressed as the production duration of a single part; The historical finished product data includes historical part models and historical finished product images.

[0021] In specific implementation, natural number numbers are assigned to machine tools to ensure the uniqueness and traceability of each machine tool, which is convenient for management and maintenance. By retrieving the production database and matching the machine tool number, the historical operation data and historical finished product data of the machine tool in the first time period can be quickly obtained, which improves the efficiency and real-time performance of data retrieval. It collects a variety of historical operation data including current, production time, precision errors of linear axes and rotary axes, etc., and provides comprehensive data support for performance analysis and fault diagnosis of machine tools.

[0022] The logic of the numbering includes: A top view of the interior of a factory building is obtained, and the top view is filtered and grayed to obtain a first top view, and shape features of the first top view are extracted, recorded as first features. A standard top view of a machine tool is obtained, and shape features of the standard top view of the machine tool are extracted, recorded as second features. Similarity between the first feature and the second feature is calculated, recorded as first similarity, and a first value is set as a similarity threshold. The first similarity is compared with the first value to obtain a first comparison result, wherein the first comparison result includes that the first similarity is greater than or equal to the first value, and the first similarity is less than the first value. When the first similarity threshold is greater than or equal to the first similarity threshold, an image portion corresponding to the shape features is obtained, and the image portions are numbered. The calculation order of the first similarity in the first top view is from left to right and from top to bottom, wherein the priority from left and right is greater than the priority from top to bottom.

[0023] In the specific implementation, by obtaining a top view of the interior of the factory and performing filtering and grayscale processing, the shape feature quantities of the machine tool are more accurately extracted, thereby improving the accuracy and efficiency of machine tool identification. The similarity calculation between the first feature quantity and the second feature quantity is used to make the machine tool more reasonably laid out and managed, and the production process is optimized. By comparing the first similarity and the similarity threshold, the difference between the actual layout and the standard layout of the machine tool is more effectively compared and analyzed, providing data support for the optimization of the machine tool, enabling the manufacturing industry to achieve real-time monitoring, fault prediction and remote maintenance of machine tools through cloud computing technology, thereby improving the operating efficiency of machine tools, reducing maintenance costs, and enhancing the reliability and stability of equipment.

[0024] The step S200 includes the following sub-steps: Step S201, obtaining historical operation data and historical finished product data corresponding to any machine tool; Step S202, judging the operating state of the machine tool according to the machine tool operating data, wherein the operating state includes a normal state and an abnormal state; Step S203, performing a first operation according to the operating status of the machine tool, wherein the first operation includes sending a first maintenance signal and jumping to a next numbered machine tool, or performing a first analysis on historical operating data and historical finished product data of the machine tool.

[0025] The judgment logic of the operating state includes: Obtain a machine tool number, retrieve a machine tool database, input the machine tool number into the machine tool database, obtain a rated current, obtain a historical current within a first time period, compare each historical current with the rated current, select a historical current whose value is greater than or equal to the rated current, and count the historical duration of the historical current whose value is greater than or equal to the rated current, set a second value as a historical duration threshold, and when the historical duration is greater than or equal to the second value, set the operating state to an abnormal state, otherwise, set the operating state to a normal state; The execution logic of the first operation includes: Obtain the operating status. When the operating status is normal, set the first operation to perform a first analysis on the historical operating data and historical finished product data of the machine tool. When the operating status is abnormal, set the first operation to send a first maintenance signal and jump to the next numbered machine tool. The next numbered machine tool is represented as the machine tool with the next number after the machine tool number.

[0026] In the specific implementation, the historical operation data and historical finished product data of the machine tool are obtained in time, and the current status of the machine tool is quickly evaluated, thereby improving the response speed to changes in the machine tool status. The judgment of the machine tool operation status helps to distinguish between normal and abnormal states, making maintenance work more targeted, optimizing the maintenance process, and reducing unnecessary inspections and repairs. When the machine tool is in an abnormal state, a maintenance signal is sent in time to speed up the response speed of maintenance personnel, improve maintenance efficiency, and reduce production delays caused by waiting for maintenance. By jumping to the next numbered machine tool to continue monitoring, the continuity of production monitoring is guaranteed. Even if a problem occurs with a machine tool, it will not affect the monitoring of the entire production process.

[0027] The step S300 includes the following sub-steps: Step S301, when the operating state is a normal state, in response to a first operation, performing a first analysis on the historical operating data and historical finished product data of the machine tool; Step S302, obtaining historical finished product pictures and historical finished product models, extracting shape feature quantities of the historical finished product pictures, recording them as third feature quantities, retrieving a finished product database, inputting the historical finished product models into the finished product database, matching standard finished product pictures corresponding to the historical finished product models, extracting fourth feature quantities of the standard finished product pictures, and calculating finished product similarity between the third feature quantity and the fourth feature quantity according to a cosine similarity formula; Step S304, setting the third value and the fourth value as the finished product similarity threshold, and classifying the quality of the historical finished products according to the finished product similarity threshold to obtain the historical finished product grade, wherein the historical finished product grade includes a first grade, a second grade and a third grade, and the finished product quality represented by the first grade, the second grade and the third grade is in descending order; Step S305, establish a first mapping relationship between the historical finished product model and the machine tool number and the historical finished product grade. The first mapping relationship is used to associate the machine tool number, the historical finished product data and the historical finished product grade. Through the first mapping relationship, the finished product model is obtained to obtain the machine tool number and the finished product grade.

[0028] In the specific implementation, the shape features of historical finished product images are extracted and compared with the features of standard finished product images. The cosine similarity formula is used to calculate the finished product similarity, which provides a quantitative analysis method for the finished product quality. The historical finished product quality is automatically graded according to the finished product similarity threshold, which simplifies the quality control process and improves efficiency. Through the division of historical finished product grades, production resources are allocated more reasonably, high-grade finished products are produced first, and the overall production efficiency is improved. The first mapping relationship established associates the machine tool number, historical finished product data and historical finished product grade, which enhances the traceability of product quality and facilitates tracing the source of the problem and taking improvement measures.

[0029] The step S400 includes the following sub-steps: Step S401, obtaining the current part model and current production quantity; Step S402, obtaining a first mapping relationship, inputting the current part model into the first mapping relationship, obtaining a machine tool number and a historical finished product level corresponding to the current model, and recording them as the current machine tool number and the corresponding current finished product level respectively; Step S403, screening production machine tools according to the current finished product grade, the screening logic of the production machine tools includes: traversing the current quality grades, selecting the machine tools whose current quality grade is the third grade, and recording them as production machine tools; Step S404, obtaining historical operation data corresponding to the production machine tool, and configuring a first production strategy according to the historical operation data, wherein the configuration logic of the first production strategy includes: Obtain the historical production duration corresponding to the production machine tool, recorded as the first duration, obtain the current production quantity, obtain the lowest common multiple of the first durations corresponding to each production machine tool, recorded as the first value, calculate the ratio of the first value to the first duration corresponding to each production machine tool, recorded as the first quantity, the first quantity is represented by the number of parts produced by the machine tool in the same time, calculate the sum of the first quantities, recorded as the first sum, and compare the first sum with the current production quantity; When the first sum is greater than or equal to the current production quantity, the first time durations are sorted in descending order, and the first quantity corresponding to each machine tool is allocated according to the descending sorting order until the current production quantity is allocated and the allocation is stopped; When the first sum is less than the current production quantity, a ratio of the current production quantity to the first sum is calculated and recorded as a first ratio; When the first ratio is a natural number, allocating a first quantity corresponding to each machine tool; When the first ratio is not a natural number, take the integer and remainder of the first ratio, the integer represents the number of production rounds, and the remainder represents the excess production quantity. Within the integer number of production rounds, allocate the first quantity corresponding to each machine tool. When the integer number of production rounds is exceeded, sort the first time length in descending order, and allocate the first quantity corresponding to each machine tool in the descending sorting order until the remainder is allocated and stops allocating.

[0030] In the specific implementation, the current part model and the current production quantity are obtained to formulate a more accurate production plan to ensure the realization of production goals. The first mapping relationship is used to obtain the machine tool number and historical finished product grade corresponding to the current model, which helps to screen suitable production machines according to the historical finished product grade and optimize the allocation of production resources. The first production strategy is configured according to the historical operation data. By calculating the production time and production quantity of each production machine tool, the production tasks are reasonably allocated to improve production efficiency. By accurately calculating and allocating production tasks, the waste caused by overproduction or underproduction is reduced and resource utilization is improved.

[0031] The present invention monitors the operating status of machine tools and historical finished product data to promptly discover and solve problems that affect production efficiency, such as the situation where the feed rate is lower than expected, resulting in insufficient processing efficiency. The historical finished product data is used to calculate the finished product similarity, and a similarity threshold is set to divide the quality grade. This helps to identify and control product quality problems and reduce product quality problems caused by violations of process regulations. By monitoring the operating data of machine tools, potential failures and maintenance needs are predicted, thereby achieving preventive maintenance and reducing unexpected downtime and maintenance costs. By monitoring the operating data of machine tools, potential failures and maintenance needs are predicted, thereby achieving preventive maintenance and reducing unexpected downtime and maintenance costs. Production machine tools are screened according to the current finished product grade, and corresponding production strategies are configured to quickly adapt to changes in production needs, thereby improving the flexibility and response speed of the production line. Remote monitoring and fault diagnosis reduce the need for maintenance personnel to go to the site, saving manpower and material costs, while providing customers with faster services and reducing their losses.

[0032] It should be understood by those skilled in the art that the embodiments of the present invention may be provided as methods, systems or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware aspects. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program codes. Wherein, the storage medium is implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read Only Memory, referred to as EPROM), programmable read-only memory (Programmable Red-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic memory, flash memory, magnetic disk or optical disk. These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0033] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions of the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention should be included in the scope of the claims of the present invention.

Claims

1. A remote monitoring method for a CNC machine tool, characterized in that: The following steps are involved: Step S100, numbering the machine tools, and matching the corresponding historical operation data and historical finished product data according to the numbered machine tools; Step S200, acquiring historical operation data and historical finished product data corresponding to any machine tool, determining the operation status of the machine tool according to the machine tool operation data, and performing a first operation according to the operation status of the machine tool; Step S300, in response to the first operation, calculating the finished product similarity according to the historical finished product data, setting a similarity threshold, classifying the quality of the historical finished products according to the similarity threshold, obtaining the historical finished product grades, and establishing a first mapping relationship according to the historical finished product grades; Step S400, according to the first mapping relationship, obtain the current machine tool number and the corresponding current finished product level, filter the production machine tools according to the current finished product level, obtain the historical operation data corresponding to the production machine tools, and configure the first production strategy according to the historical operation data.

2. A method for remote monitoring of a CNC machine tool as claimed in claim 1, characterized in that: The step S100 includes the following sub-steps: Step S101, numbering the machine tools, where the numbers are natural numbers; Step S102, calling up a production database, adding a data machine tool number to the production database, and matching the historical operation data and historical finished product data corresponding to the first time period; The historical operation data includes historical current, historical production time, historical linear axis straightness error, historical linear axis perpendicularity error, historical rotary axis straightness error, historical spindle parallelism error, historical table flatness error and historical table parallelism error; The historical production duration is expressed as the production duration of a single part; The historical finished product data includes historical part models and historical finished product images.

3. A method for remote monitoring of a CNC machine tool as claimed in claim 2, characterized in that: The logic of the numbering includes: A top view of the interior of a factory building is obtained, and the top view is filtered and grayed to obtain a first top view, and shape features of the first top view are extracted, recorded as first features. A standard top view of a machine tool is obtained, and shape features of the standard top view of the machine tool are extracted, recorded as second features. Similarity between the first feature and the second feature is calculated, recorded as first similarity, and a first value is set as a similarity threshold. The first similarity is compared with the first value to obtain a first comparison result, wherein the first comparison result includes that the first similarity is greater than or equal to the first value, and the first similarity is less than the first value. When the first similarity threshold is greater than or equal to the first similarity threshold, an image portion corresponding to the shape features is obtained, and the image portions are numbered. The calculation order of the first similarity in the first top view is from left to right and from top to bottom, wherein the priority from left and right is greater than the priority from top to bottom.

4. A method for remote monitoring of a CNC machine tool as claimed in claim 1, characterized in that: The step S200 includes the following sub-steps: Step S201, obtaining historical operation data and historical finished product data corresponding to any machine tool; Step S202, judging the operating state of the machine tool according to the machine tool operating data, wherein the operating state includes a normal state and an abnormal state; Step S203, performing a first operation according to the operating status of the machine tool, wherein the first operation includes sending a first maintenance signal and jumping to a next numbered machine tool, or performing a first analysis on historical operating data and historical finished product data of the machine tool.

5. A method for remote monitoring of a CNC machine tool as claimed in claim 4, characterized in that: The judgment logic of the operating state includes: Obtain a machine tool number, retrieve a machine tool database, input the machine tool number into the machine tool database, obtain a rated current, obtain a historical current within a first time period, compare each historical current with the rated current, select a historical current whose value is greater than or equal to the rated current, and count the historical duration of the historical current whose value is greater than or equal to the rated current, set a second value as a historical duration threshold, and when the historical duration is greater than or equal to the second value, set the operating state to an abnormal state, otherwise, set the operating state to a normal state; The execution logic of the first operation includes: Obtain the operating status. When the operating status is normal, set the first operation to perform a first analysis on the historical operating data and historical finished product data of the machine tool. When the operating status is abnormal, set the first operation to send a first maintenance signal and jump to the next numbered machine tool. The next numbered machine tool is represented as the machine tool with the next number after the machine tool number.

6. A method for remote monitoring of a CNC machine tool as claimed in claim 1, characterized in that: The step S300 includes the following sub-steps: Step S301, when the operating state is a normal state, in response to a first operation, performing a first analysis on the historical operating data and historical finished product data of the machine tool; Step S302, obtaining historical finished product pictures and historical finished product models, extracting shape feature quantities of the historical finished product pictures, recording them as third feature quantities, retrieving a finished product database, inputting the historical finished product models into the finished product database, matching standard finished product pictures corresponding to the historical finished product models, extracting fourth feature quantities of the standard finished product pictures, and calculating finished product similarity between the third feature quantity and the fourth feature quantity according to a cosine similarity formula; Step S304, setting the third value and the fourth value as the finished product similarity threshold, and classifying the quality of the historical finished products according to the finished product similarity threshold to obtain the historical finished product grade, wherein the historical finished product grade includes a first grade, a second grade and a third grade, and the finished product quality represented by the first grade, the second grade and the third grade is in descending order; Step S305, establish a first mapping relationship between the historical finished product model and the machine tool number and the historical finished product grade. The first mapping relationship is used to associate the machine tool number, the historical finished product data and the historical finished product grade. Through the first mapping relationship, the finished product model is obtained to obtain the machine tool number and the finished product grade.

7. A method for remote monitoring of a CNC machine tool as claimed in claim 1, characterized in that: The step S400 includes the following sub-steps: Step S401, obtaining the current part model and current production quantity; Step S402, obtaining a first mapping relationship, inputting the current part model into the first mapping relationship, obtaining a machine tool number and a historical finished product level corresponding to the current model, and recording them as the current machine tool number and the corresponding current finished product level respectively; Step S403, screening production machine tools according to the current finished product grade, the screening logic of the production machine tools includes: traversing the current quality grades, selecting the machine tools whose current quality grade is the third grade, and recording them as production machine tools; Step S404, obtaining historical operation data corresponding to the production machine tool, and configuring a first production strategy according to the historical operation data, wherein the configuration logic of the first production strategy includes: Obtain the historical production duration corresponding to the production machine tool, recorded as the first duration, obtain the current production quantity, obtain the lowest common multiple of the first durations corresponding to each production machine tool, recorded as the first value, calculate the ratio of the first value to the first duration corresponding to each production machine tool, recorded as the first quantity, the first quantity is represented by the number of parts produced by the machine tool in the same time, calculate the sum of the first quantities, recorded as the first sum, and compare the first sum with the current production quantity; When the first sum is greater than or equal to the current production quantity, the first time durations are sorted in descending order, and the first quantity corresponding to each machine tool is allocated according to the descending sorting order until the current production quantity is allocated and the allocation is stopped; When the first sum is less than the current production quantity, a ratio of the current production quantity to the first sum is calculated and recorded as a first ratio; When the first ratio is a natural number, allocating a first quantity corresponding to each machine tool; When the first ratio is not a natural number, take the integer and remainder of the first ratio, the integer represents the number of production rounds, and the remainder represents the excess production quantity. Within the integer number of production rounds, allocate the first quantity corresponding to each machine tool. When the integer number of production rounds is exceeded, sort the first time length in descending order, and allocate the first quantity corresponding to each machine tool in the descending sorting order until the remainder is allocated and stops allocating.

8. A remote monitoring system for a numerically controlled machine tool, the system being used to execute a remote monitoring method for a numerically controlled machine tool as claimed in claim 1, characterized in that: It includes acquisition module, analysis module and configuration module; The acquisition module numbers the machine tools and matches the corresponding historical operation data and historical finished product data according to the numbered machine tools; The analysis module obtains historical operation data and historical finished product data corresponding to any machine tool, determines the operation status of the machine tool according to the machine tool operation data, performs a first operation according to the operation status of the machine tool, calculates the finished product similarity according to the historical finished product data in response to the first operation, sets a similarity threshold, grades the historical finished product quality according to the similarity threshold, obtains the historical finished product grade, and establishes a first mapping relationship according to the historical finished product grade; The configuration module obtains the current machine tool number and the corresponding current finished product level according to the first mapping relationship, screens the production machine tools according to the current finished product level, obtains the historical operation data corresponding to the production machine tools, and configures the first production strategy according to the historical operation data.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the method for remote monitoring of a CNC machine tool described in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for remote monitoring a CNC machine tool according to any one of claims 1 to 7 is implemented.

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