A remote monitoring method for CNC machine tools

Abstract

The present invention discloses a remote monitoring method and system for CNC machine tools, which relates to the technical field of data analysis and includes the following steps: determining the operating status of the machine tool, executing a first operation, calculating the similarity of finished products, setting a similarity threshold, grading the quality of historical finished products, establishing a first mapping relationship, screening production machine tools according to the current finished product grade, and configuring a first production strategy. The present invention monitors the operating status and historical finished product data of the machine tool to promptly discover and solve problems that affect production efficiency, calculates the similarity of finished products using historical finished product data, and helps to identify and control product quality problems. By monitoring the operating data of the machine tool, preventive maintenance is achieved, and production machine tools are screened according to the current finished product grade and corresponding production strategies are configured to 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.

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 has been undergoing a transformation from traditional manufacturing to digitalization, networking, and intelligentization. By integrating sensors and the Internet of Things (IoT) technology, remote monitoring, fault prediction, and automated production are being achieved, significantly improving production efficiency and precision. Regarding intelligentization, the focus will be on developing deep integration with artificial intelligence and big data to elevate the intelligence level of machine tools.

[0003] At present, a Chinese invention patent with publication number CN115390509A discloses a control method and a CNC machine tool based on visual control. 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; based on the second image, it is determined whether the material is in the processing area. 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. However, 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 status of the machine tools is not judged based on historical big data and the machine tools that can be used for production are not screened, which easily leads to erroneous production, thereby reducing economic benefits. Summary of the Invention

[0004] The technical problem solved by the present invention is that the relevant technology does not reasonably allocate and schedule machine tools according to temporary production tasks, which is not conducive to the speed 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 leads to erroneous production and thus reduces economic benefits.

[0005] To solve the above technical problems, the present invention provides the following technical solutions: In a first aspect, a remote monitoring method for a CNC machine tool comprises the following steps:

[0006] Step S100: numbering the machine tools and matching the corresponding historical operation data and historical finished product data according to the numbered machine tools;

[0007] Step S200, acquiring historical operation data and historical finished product data corresponding to any machine tool, determining an operation status of the machine tool based on the historical operation data of the machine tool, and performing a first operation based on the operation status of the machine tool;

[0008] Step S300, in response to the first operation, calculating the finished product similarity based on the historical finished product data, setting a similarity threshold, classifying the historical finished product quality according to the similarity threshold to obtain the historical finished product grade, and establishing a first mapping relationship based on the historical finished product grade;

[0009] Step S400: Obtain the current machine tool number and the corresponding current finished product level according to the first mapping relationship, 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.

[0010] 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:

[0011] Step S101, numbering the machine tools, where the numbers are natural numbers;

[0012] Step S102: retrieve the production database, add the machine tool number in the production database, and match the historical operation data and historical finished product data corresponding to the first time period;

[0013] 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;

[0014] The historical production duration is expressed as the production duration of a single part;

[0015] The historical finished product data includes historical part models and historical finished product pictures.

[0016] As a preferred solution of the method for remote monitoring of a CNC machine tool according to the present invention, the numbering logic includes:

[0017] Obtain a top view of the interior of the factory building, filter and grayscale the top view to obtain a first top view, extract shape features of the first top view, record them as first features, obtain a standard top view of a machine tool, extract shape features of the standard top view of the machine tool, record them as second features, calculate the similarity between the first feature and the second feature, record them as first similarity, set a first value as a similarity threshold, compare the first similarity with the first value to obtain a first comparison result, the first comparison result includes a first similarity greater than or equal to the first value, and a first similarity less than the first value. When the first similarity is greater than or equal to the first value, obtain the image part corresponding to the shape feature, number the image part, and calculate the first similarity in the first top view from left to right and from top to bottom, where the priority from left and right is higher than the priority from top to bottom.

[0018] 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:

[0019] Step S201, obtaining historical operation data and historical finished product data corresponding to any machine tool;

[0020] Step S202, determining the operating state of the machine tool according to the historical operating data of the machine tool, where the operating state includes a normal state and an abnormal state;

[0021] 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 the next numbered machine tool, or performing a first analysis on the historical operating data and historical finished product data of the machine tool.

[0022] As a preferred solution of the method for remote monitoring of a CNC machine tool according to the present invention, the judgment logic of the operating status includes:

[0023] Obtaining a machine tool number, retrieving a machine tool database, inputting the machine tool number into the machine tool database, obtaining a rated current, obtaining historical currents within a first time period, comparing each historical current with the rated current, selecting historical currents whose values are greater than or equal to the rated current, and counting historical durations of the historical currents whose values are greater than or equal to the rated current, setting a second value as a historical duration threshold, and setting the operating state to an abnormal state when the historical duration is greater than or equal to the second value; otherwise, setting the operating state to a normal state;

[0024] The execution logic of the first operation includes:

[0025] 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 by the machine tool with the next number after the machine tool number.

[0026] 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:

[0027] Step S301, when the operating state is normal, in response to a first operation, performing a first analysis on historical operating data and historical finished product data of the machine tool;

[0028] Step S302: Obtain historical finished product images and historical finished product models, extract shape features of the historical finished product images, record them as third features, retrieve a finished product database, input the historical finished product models into the finished product database, match standard finished product images corresponding to the historical finished product models, extract fourth features of the standard finished product images, and calculate product similarity between the third and fourth features according to a cosine similarity formula.

[0029] Step S304: The third value and the fourth value are set as the finished product similarity threshold, and the historical finished product quality is graded according to the finished product similarity threshold to obtain a 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 are in descending order;

[0030] 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, and the machine tool number and the finished product grade are obtained.

[0031] 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:

[0032] Step S401, obtaining the current part model and current production quantity;

[0033] Step S402: Obtain a first mapping relationship, input the current part model into the first mapping relationship, obtain the machine tool number and historical finished product level corresponding to the current model, and record them as the current machine tool number and the corresponding current finished product level respectively;

[0034] Step S403, screening production machine tools according to the current finished product grade, wherein the screening logic of the production machine tools includes: traversing the current quality grades, selecting the machine tools with the current quality grade of the third grade, and recording them as production machine tools;

[0035] Step S404: Obtain historical operation data corresponding to the production machine tool, and configure a first production strategy based on the historical operation data. The configuration logic of the first production strategy includes:

[0036] 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 duration 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 represents the number of parts produced by the machine tool within the same period of time; calculate the sum of the first quantities, recorded as the first sum value; and compare the first sum value with the current production quantity;

[0037] When the first sum is greater than or equal to the current production quantity, the first durations are sorted in descending order, and the first quantity corresponding to each machine tool is allocated according to the descending sort order until the current production quantity is fully allocated;

[0038] 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;

[0039] When the first ratio is a natural number, allocating a first quantity corresponding to each machine tool;

[0040] When the first ratio is not a natural number, the integer and remainder of the first ratio are taken, the integer represents the number of production rounds, and the remainder represents the excess production quantity. Within the integer number of production rounds, the first quantity corresponding to each machine tool is allocated. When the integer number of production rounds is exceeded, the first time length is sorted in descending order, and the first quantity corresponding to each machine tool is allocated in the descending sorting order until the remainder is allocated and the allocation is stopped.

[0041] In a second aspect, a remote monitoring system for a CNC machine tool includes an acquisition module, an analysis module, and a configuration module;

[0042] 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;

[0043] The analysis module obtains historical operation data and historical finished product data corresponding to any machine tool, determines an operation status of the machine tool based on the historical operation data of the machine tool, performs a first operation based on the operation status of the machine tool, calculates finished product similarity based on the historical finished product data in response to the first operation, sets a similarity threshold, classifies the quality of the historical finished products into grades based on the similarity threshold to obtain historical finished product grades, and establishes a first mapping relationship based on the historical finished product grades;

[0044] The configuration module obtains the current machine tool number and the corresponding current finished product level based on the first mapping relationship, screens production machine tools based on the current finished product level, obtains historical operation data corresponding to the production machine tools, and configures the first production strategy based on the historical operation data.

[0045] In a third aspect, the present invention provides an electronic device comprising a memory, a processor and a memory storing computer-readable instructions. When the computer-readable instructions are executed by the processor, the steps in any one of the methods described above are executed.

[0046] 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.

[0047] 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 solved in a timely manner, such as insufficient processing efficiency caused by feed rate being 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 faults and maintenance needs can be predicted, thereby achieving preventive maintenance, reducing unexpected downtime and repair costs; by monitoring the operating data of machine tools, potential faults and maintenance needs can be predicted, thereby achieving preventive maintenance, reducing unexpected downtime and repair costs; screening production machines according to current finished product grades, and configuring corresponding production strategies, quickly adapting to changes in production needs, and 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 customer losses. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 A schematic diagram of the basic flow of a method for remote monitoring of a CNC machine tool provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0049] 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.

[0050] 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:

[0051] Step S100: numbering the machine tools and matching the corresponding historical operation data and historical finished product data according to the numbered machine tools;

[0052] Step S200, acquiring historical operation data and historical finished product data corresponding to any machine tool, determining an operation status of the machine tool based on the historical operation data of the machine tool, and performing a first operation based on the operation status of the machine tool;

[0053] Step S300, in response to the first operation, calculating the finished product similarity based on the historical finished product data, setting a similarity threshold, classifying the historical finished product quality according to the similarity threshold to obtain the historical finished product grade, and establishing a first mapping relationship based on the historical finished product grade;

[0054] Step S400: Obtain the current machine tool number and the corresponding current finished product level according to the first mapping relationship, 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.

[0055] 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 insufficient processing efficiency caused by feed rate being lower than expected. It uses historical finished product data to calculate the similarity of finished products and sets similarity thresholds to divide quality grades, 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 faults and maintenance needs are predicted, thereby achieving preventive maintenance and reducing unexpected downtime and repair costs. By monitoring the operating data of machine tools, potential faults and maintenance needs are predicted, thereby achieving preventive maintenance and reducing unexpected downtime and repair 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 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.

[0056] The step S100 includes the following sub-steps:

[0057] Step S101, numbering the machine tools, where the numbers are natural numbers;

[0058] Step S102: retrieve the production database, add the machine tool number in the production database, and match the historical operation data and historical finished product data corresponding to the first time period;

[0059] 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;

[0060] The historical production duration is expressed as the production duration of a single part;

[0061] The historical finished product data includes historical part models and historical finished product pictures.

[0062] In specific implementation, by assigning natural number numbers to machine tools, the uniqueness and traceability of each machine tool are ensured, which facilitates 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 error of linear axis and rotary axis, etc., and provides comprehensive data support for performance analysis and fault diagnosis of machine tools.

[0063] The numbering logic includes:

[0064] Obtain a top view of the interior of the factory building, filter and grayscale the top view to obtain a first top view, extract shape features of the first top view, record them as first features, obtain a standard top view of a machine tool, extract shape features of the standard top view of the machine tool, record them as second features, calculate the similarity between the first feature and the second feature, record them as first similarity, set a first value as a similarity threshold, compare the first similarity with the first value to obtain a first comparison result, the first comparison result includes a first similarity greater than or equal to the first value, and a first similarity less than the first value. When the first similarity is greater than or equal to the first value, obtain the image part corresponding to the shape feature, number the image part, and calculate the first similarity in the first top view from left to right and from top to bottom, where the priority from left and right is higher than the priority from top to bottom.

[0065] In 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 can be 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 can be used to more reasonably layout and manage the machine tool, optimize the production process, and by comparing the first similarity and the similarity threshold, the difference between the actual layout and the standard layout of the machine tool can be 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, improve the operating efficiency of machine tools, reduce maintenance costs, and enhance the reliability and stability of equipment.

[0066] The step S200 includes the following sub-steps:

[0067] Step S201, obtaining historical operation data and historical finished product data corresponding to any machine tool;

[0068] Step S202, determining the operating state of the machine tool according to the historical operating data of the machine tool, where the operating state includes a normal state and an abnormal state;

[0069] 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 the next numbered machine tool, or performing a first analysis on the historical operating data and historical finished product data of the machine tool.

[0070] The judgment logic of the operating state includes:

[0071] Obtaining a machine tool number, retrieving a machine tool database, inputting the machine tool number into the machine tool database, obtaining a rated current, obtaining historical currents within a first time period, comparing each historical current with the rated current, selecting historical currents whose values are greater than or equal to the rated current, and counting historical durations of the historical currents whose values are greater than or equal to the rated current, setting a second value as a historical duration threshold, and setting the operating state to an abnormal state when the historical duration is greater than or equal to the second value; otherwise, setting the operating state to a normal state;

[0072] The execution logic of the first operation includes:

[0073] 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 by the machine tool with the next number after the machine tool number.

[0074] 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 the 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.

[0075] The step S300 includes the following sub-steps:

[0076] Step S301, when the operating state is normal, in response to a first operation, performing a first analysis on historical operating data and historical finished product data of the machine tool;

[0077] Step S302: Obtain historical finished product images and historical finished product models, extract shape features of the historical finished product images, record them as third features, retrieve a finished product database, input the historical finished product models into the finished product database, match standard finished product images corresponding to the historical finished product models, extract fourth features of the standard finished product images, and calculate product similarity between the third and fourth features according to a cosine similarity formula.

[0078] Step S304: The third value and the fourth value are set as the finished product similarity threshold, and the historical finished product quality is graded according to the finished product similarity threshold to obtain a 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 are in descending order;

[0079] 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, and the machine tool number and the finished product grade are obtained.

[0080] In the specific implementation, the shape features of historical finished product pictures are extracted and compared with the features of standard finished product pictures. The cosine similarity formula is used to calculate the similarity of finished products, which provides a quantitative analysis method for the quality of finished products. The quality of historical finished products 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 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.

[0081] The step S400 includes the following sub-steps:

[0082] Step S401, obtaining the current part model and current production quantity;

[0083] Step S402: Obtain a first mapping relationship, input the current part model into the first mapping relationship, obtain the machine tool number and historical finished product level corresponding to the current model, and record them as the current machine tool number and the corresponding current finished product level respectively;

[0084] Step S403, screening production machine tools according to the current finished product grade, wherein the screening logic of the production machine tools includes: traversing the current quality grades, selecting the machine tools with the current quality grade of the third grade, and recording them as production machine tools;

[0085] Step S404: Obtain historical operation data corresponding to the production machine tool, and configure a first production strategy based on the historical operation data. The configuration logic of the first production strategy includes:

[0086] 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 duration 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 represents the number of parts produced by the machine tool within the same period of time; calculate the sum of the first quantities, recorded as the first sum value; and compare the first sum value with the current production quantity;

[0087] When the first sum is greater than or equal to the current production quantity, the first durations are sorted in descending order, and the first quantity corresponding to each machine tool is allocated according to the descending sort order until the current production quantity is fully allocated;

[0088] When the first sum is less than the current production quantity, calculating the ratio of the current production quantity to the first sum, and recording it as a first ratio;

[0089] When the first ratio is a natural number, allocating a first quantity corresponding to each machine tool;

[0090] When the first ratio is not a natural number, the integer and remainder of the first ratio are taken, the integer represents the number of production rounds, and the remainder represents the excess production quantity. Within the integer number of production rounds, the first quantity corresponding to each machine tool is allocated. When the integer number of production rounds is exceeded, the first time length is sorted in descending order, and the first quantity corresponding to each machine tool is allocated in the descending sorting order until the remainder is allocated and the allocation is stopped.

[0091] In specific implementation, the current part model and 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 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.

[0092] 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 insufficient processing efficiency caused by feed rate being lower than expected. It uses historical finished product data to calculate the similarity of finished products and sets similarity thresholds to divide quality grades, 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 faults and maintenance needs are predicted, thereby achieving preventive maintenance and reducing unexpected downtime and repair costs. By monitoring the operating data of machine tools, potential faults and maintenance needs are predicted, thereby achieving preventive maintenance and reducing unexpected downtime and repair 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 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.

[0093] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, 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 code. The storage medium may be implemented by any type of volatile or non-volatile storage device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work 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 The function specified in one or more boxes.

[0094] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. 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 replacements 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 an operation status of the machine tool based on the historical operation data of the machine tool, and performing a first operation based on the operation status of the machine tool; Step S300, in response to the first operation, calculating the finished product similarity based on the historical finished product data, setting a similarity threshold, classifying the historical finished product quality according to the similarity threshold to obtain the historical finished product grade, and establishing a first mapping relationship based on the historical finished product grade; Step S400: obtaining the current machine tool number and the corresponding current finished product level according to the first mapping relationship, screening the production machine tools according to the current finished product level, obtaining the historical operation data corresponding to the production machine tools, and configuring the first production strategy according to the historical operation data; The step S400 includes the following sub-steps: Step S401, obtaining the current part model and current production quantity; Step S402: Obtain a first mapping relationship, input the current part model into the first mapping relationship, obtain the machine tool number and historical finished product level corresponding to the current model, and record 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, wherein the screening logic of the production machine tools includes: traversing the current quality grades, selecting the machine tools with the current quality grade of the third grade, and recording them as production machine tools; Step S404: Obtain historical operation data corresponding to the production machine tool, and configure a first production strategy based on the historical operation data. 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 duration 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 represents the number of parts produced by the machine tool within the same period of time; calculate the sum of the first quantities, recorded as the first sum value; and compare the first sum value with the current production quantity; When the first sum is greater than or equal to the current production quantity, the first durations are sorted in descending order, and the first quantity corresponding to each machine tool is allocated according to the descending sort order until the current production quantity is fully allocated; When the first sum is less than the current production quantity, calculating the ratio of the current production quantity to the first sum, and recording it 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, the integer and remainder of the first ratio are taken, the integer represents the number of production rounds, and the remainder represents the excess production quantity. Within the integer number of production rounds, the first quantity corresponding to each machine tool is allocated. When the integer number of production rounds is exceeded, the first time length is sorted in descending order, and the first quantity corresponding to each machine tool is allocated in the descending sorting order until the remainder is allocated and the allocation is stopped.

2. A method for remote monitoring of a CNC machine tool according to 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: retrieve the production database, add the machine tool number in the production database, and match 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 pictures.

3. A method for remote monitoring of a CNC machine tool according to claim 2, characterized in that: The numbering logic includes: Obtain a top view of the interior of the factory building, filter and grayscale the top view to obtain a first top view, extract shape features of the first top view, record them as first features, obtain a standard top view of a machine tool, extract shape features of the standard top view of the machine tool, record them as second features, calculate the similarity between the first feature and the second feature, record them as first similarity, set a first value as a similarity threshold, compare the first similarity with the first value to obtain a first comparison result, the first comparison result includes a first similarity greater than or equal to the first value, and a first similarity less than the first value. When the first similarity is greater than or equal to the first value, obtain the image part corresponding to the shape feature, number the image part, and calculate the first similarity in the first top view from left to right and from top to bottom, where the priority from left and right is higher than the priority from top to bottom.

4. A method for remote monitoring of a CNC machine tool according to 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, determining the operating state of the machine tool according to the historical operating data of the machine tool, where 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 the next numbered machine tool, or performing a first analysis on the historical operating data and historical finished product data of the machine tool.

5. A method for remote monitoring of a CNC machine tool according to claim 4, characterized in that: The judgment logic of the operating state includes: Obtaining a machine tool number, retrieving a machine tool database, inputting the machine tool number into the machine tool database, obtaining a rated current, obtaining historical currents within a first time period, comparing each historical current with the rated current, selecting historical currents whose values are greater than or equal to the rated current, and counting historical durations of the historical currents whose values are greater than or equal to the rated current, setting a second value as a historical duration threshold, and setting the operating state to an abnormal state when the historical duration is greater than or equal to the second value; otherwise, setting 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 by the machine tool with the next number after the machine tool number.

6. A method for remote monitoring of a CNC machine tool according to claim 1, characterized in that: The step S300 includes the following sub-steps: Step S301, when the operating state is normal, in response to a first operation, performing a first analysis on historical operating data and historical finished product data of the machine tool; Step S302: Obtain historical finished product images and historical finished product models, extract shape features of the historical finished product images, record them as third features, retrieve a finished product database, input the historical finished product models into the finished product database, match standard finished product images corresponding to the historical finished product models, extract fourth features of the standard finished product images, and calculate product similarity between the third and fourth features according to a cosine similarity formula. Step S304: The third value and the fourth value are set as the finished product similarity threshold, and the historical finished product quality is graded according to the finished product similarity threshold to obtain a 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 are 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, and the machine tool number and the finished product grade are obtained.

7. A remote monitoring system for a CNC machine tool, the system being used to execute the remote monitoring method for a CNC machine tool according to claim 1, characterized in that: 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 an operation status of the machine tool based on the historical operation data of the machine tool, performs a first operation based on the operation status of the machine tool, calculates finished product similarity based on the historical finished product data in response to the first operation, sets a similarity threshold, classifies the quality of the historical finished products into grades based on the similarity threshold to obtain historical finished product grades, and establishes a first mapping relationship based on the historical finished product grades; The configuration module obtains the current machine tool number and the corresponding current finished product level based on the first mapping relationship, screens production machine tools based on the current finished product level, obtains historical operation data corresponding to the production machine tools, and configures the first production strategy based on the historical operation data.

8. 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 according to any one of claims 1 to 6 is implemented.

9. 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 the processor, the method for remote monitoring of a CNC machine tool according to any one of claims 1 to 6 is implemented.

Images