Intelligent numerical control system for numerical control machine tool

Abstract

The invention relates to the field of intelligent numerical control of numerical control machine tools, in particular to an intelligent numerical control system for a numerical control machine tool, which comprises an intelligent acquisition module, an adjustment module, an intelligent material identification module, an intelligent fault prediction module, a processing module, an intelligent numerical control terminal and a database, the material intelligent identification module carries out matching according to a preset integrated image of each type of processing material in the intelligent numerical control terminal and each actual processing material image acquired by a current high-definition camera, and guarantees that a feature extraction unit of the intelligent prediction module monitors the historical operation state of each numerical control machine tool device. By monitoring the quality of the processing materials, processing of bad materials is effectively avoided, and then the processing materials which are judged to be defective materials are intelligently replaced according to the material replacement priority value.

Description

Technical Field

[0001] The invention relates to the field of intelligent numerical control for numerically controlled machine tools, and in particular to an intelligent numerical control system for numerically controlled machine tools. Background Art

[0002] In modern manufacturing, CNC machine tools play an extremely important role and are widely used in various fields of precision machining. With the continuous development of manufacturing towards high precision and intelligence, traditional CNC machine tools have gradually exposed many limitations in practical applications and are unable to meet the growing production needs. In terms of processing material management, traditional CNC machine tools lack effective intelligent identification and management methods. For information such as the type and quality status of processing materials, they often rely on manual experience to judge, which is not only inefficient but also prone to misjudgment. When there are defects in the processing materials, they cannot be discovered and handled in time, which may lead to a decrease in processing accuracy during the processing process, or even cause the entire workpiece to be scrapped, thereby increasing production costs and reducing production efficiency.

[0003] In order to adapt to the intelligent development trend of the manufacturing industry and improve the overall performance and production efficiency of CNC machine tools, there is an urgent need for an innovative intelligent CNC system that can realize the intelligent identification and management of processing materials. In view of the above problems, the present invention proposes an intelligent CNC system for CNC machine tools, aiming to overcome the defects of the prior art and provide an effective solution for the intelligent development of CNC machine tools. Summary of the invention

[0004] In order to solve the technical problems raised by the above background technology, the present invention provides an intelligent numerical control system for a numerically controlled machine tool.

[0005] The purpose of the present invention can be achieved through the following technical solutions: The present invention is an intelligent numerical control system for numerically controlled machine tools, comprising an intelligent acquisition module, a material intelligent identification module, an adjustment module, an intelligent fault prediction module, a processing module, an intelligent numerical control terminal and a database.

[0006] The intelligent acquisition module installs various types of sensors on each CNC machine tool equipment to collect the equipment status and processing material information of each CNC machine tool equipment in real time. The specific process is as follows: Install a high-definition camera at each position of each CNC machine tool to collect the image data of each material to be processed in real time, and obtain the image data of each material to be processed; install a weight sensor on the material transmission path of each CNC machine tool to collect the weight parameter value of each material to be processed in real time, and the output end of the intelligent acquisition module is connected to the input end of the material intelligent identification module, and the image data and weight parameter value of each material to be processed are sent to the material intelligent identification module. Figure 1 The direction with an arrow is the input end, and the direction without an arrow is the output end.

[0007] The material intelligent recognition module matches the preset integrated images of various types of processing materials in the intelligent CNC terminal with the actual processing material images obtained by the current high-definition camera. The specific process is as follows: S01: the output end of the material intelligent recognition module is connected to the input end of the adjustment module, and the input end of the material intelligent recognition module is connected to the output end of the database. The material intelligent recognition module includes an information receiving unit, an intelligent recognition unit and an analysis unit. The information receiving unit obtains the image of the material to be processed and the weight parameter value of the material to be processed obtained by the current high-definition camera, and sends the image of the material to be processed to the intelligent numerical control terminal and the intelligent recognition unit; S02: The intelligent numerical control terminal receives the image of the material to be processed and generates a search instruction and sends it to the search unit. The search unit obtains the corresponding preset integrated image according to the image of the material to be processed and sends it to the intelligent recognition unit. The intelligent recognition unit matches the current image to be processed with the preset integrated image for the type of processing material. If the type matching is successful, the intelligent recognition unit continues to recognize the appearance of the current image of the material to be processed. S03: The intelligent recognition unit recognizes cracks and holes in the image of the material to be processed and extracts the number of cracks in the image of the material to be processed and the total crack area ; Extract the number of holes in the image of the material to be processed and the total volume of the pores , i represents the number of the image of the material to be processed, i=1, 2, ..., n; S04: extracting features of hair and dust particles of each processed material, converting the acquired processed material image into a grayscale image, obtaining the total pixel value number of the processed material image, extracting the pixel value number of hair and dust particles, marking them as the total pixel value affected, and obtaining the relative pollution coefficient RT based on the total pixel value number and the total pollution pixel value; S05: Obtain the weight parameter value of the current material to be processed, extract the preset weight parameter value of the corresponding material to be processed in the database, and subtract the actual weight parameter value from the preset weight parameter value to obtain the weight difference value of the current material to be processed, which is marked as GK; S06: Calculate based on the relative contamination coefficient, weight difference, number of cracks, total crack area, number of holes and total hole volume of the material to be processed, using the formula The material defect index TH of the current material to be processed is obtained, wherein D1, D2, D3 and D4 are preset proportional coefficients, which are 0.37, 0.45, 0.74 and 1.21 respectively. The preset material defect index in the database is extracted, and the material defect index of the current processing material is compared with the preset material defect index. If the material defect index of the current processing material is greater than the preset material defect index, the processing material is marked as a defective material, and a replacement signal is generated and sent to the adjustment module.

[0008] The adjustment module intelligently replaces the processing materials that have been determined to be defective materials according to the material replacement priority value. The specific acquisition process is as follows: K01: The output end of the adjustment module is connected to the input end of the database. The adjustment module receives the replacement signal, obtains the material type and specification of the current defective material, generates a query instruction according to the material type and specification, and sends it to the database. The database receives the query instruction and selects a list of replacement materials according to the material type and specification, marks the materials in the material list as screened materials, obtains the storage time point of each screened material, and subtracts the storage time point of each screened material from the current system time point to obtain the storage time of each material, arranges the storage time from small to large, obtains the maximum storage time, and marks it as ; K02: Take the CNC machine tool equipment of the material to be replaced as the center point, obtain the position of each screening material, connect the CNC machine tool equipment of the material to be replaced and the position of each screening material, obtain the distance value of each replacement line, and obtain the minimum replacement distance value ; K03: Set the score value of each screening material quality test report ; Calculate the maximum storage time, minimum replacement distance and score value, and use the formula The replacement priority value TW of each screened material is obtained, where B1, B2 and B3 are the weights corresponding to the maximum warehousing time, the minimum replacement distance value and the score value respectively, f represents the number of the screened material, g represents the total number of the screened materials, and each screened material is arranged from large to small according to the replacement priority value, and the screened material with the largest replacement priority value is marked as the priority replacement material. The position of the priority replacement material is obtained and sent to the adjustment module. The adjustment module generates a replacement instruction according to the position of the priority replacement material and sends it to the mobile phone terminal of the nearby staff, and the staff replaces the material.

[0009] The fault intelligent prediction module monitors and analyzes the historical operating status of each CNC machine tool equipment and determines the fault results of each CNC machine tool equipment. The specific process is as follows: F01: The input end of the intelligent fault prediction module is connected to the output end of the database. The intelligent fault prediction module includes a feature extraction unit and a fault analysis unit. The feature extraction unit obtains the historical maintenance times, maintenance duration, maintenance parts replacement frequency and fault interval time of each CNC machine tool equipment, which are marked as DK, DY, DH and DA respectively; F02: Obtain the operation time point of each CNC machine tool equipment, and as of the current operation time point, make a difference between the operation time point of each CNC machine tool equipment and the current operation time point to obtain the cumulative operation time QT of each CNC machine tool equipment, obtain the current operation value of the equipment within the cumulative operation time, extract the standard current operation range in the database, compare the current operation value of the equipment with the standard current operation range, mark the current value greater than or less than the standard current operation range as an abnormal current value, count the number and duration of abnormal current values, obtain the number of abnormal currents QA and the total abnormal duration QK, and the feature extraction unit sends the obtained data to the fault analysis unit; F03: The fault analysis unit calculates the historical maintenance times, maintenance duration, maintenance parts replacement frequency, fault interval, cumulative operation time, abnormal current times and total abnormal duration of each CNC machine tool equipment using the formula The fault tendency index FPG of each CNC machine tool equipment is obtained, where R1, R2, R3, R4, R5, R6 and R7 are preset proportional coefficients, the preset fault tendency index of the data center is extracted, and the actual fault tendency index of the equipment on each CNC machine tool is compared with the preset fault tendency index. If the actual fault tendency index of the equipment on the CNC machine tool is greater than the preset fault tendency index, the corresponding CNC machine tool equipment is marked as a high-risk fault equipment, and a detection signal is generated and sent to the processing module.

[0010] The processing module obtains the location of the corresponding high-risk equipment for fault repair based on the received detection signal. The specific process is as follows: The processing module receives the detection signal, and the input end of the processing module is connected to the port of the database to obtain the location of the high-risk equipment in real time. The location of the mobile terminal of each maintenance personnel is screened based on the high-risk equipment, the nearest mobile terminal location is obtained, and a maintenance instruction is generated and sent to the mobile terminal of the corresponding maintenance personnel for repair.

[0011] The intelligent CNC terminal includes a storage unit and a retrieval unit. It uses an industrial camera to collect all-round images of various types of processing materials. The all-round images include front images, side images and oblique images. The images of various directions of various types of processing materials are integrated to obtain preset integrated images of various types of processing materials and send them to the storage unit. The storage unit numbers each preset integrated image and records the corresponding processing material type, batch and supplier information. The retrieval unit connects with each preset integrated image number and creates an index. The index is each instruction action generated by the CNC machine tool equipment.

[0012] The port of the database is connected to each intelligent CNC terminal. One CNC machine tool equipment corresponds to one intelligent CNC terminal. The database stores the inventory information of various processing materials and the information of each CNC machine tool equipment. The inventory information includes the type, specification, quantity, storage location and warehousing time of the material. The information of each CNC machine tool equipment includes the time point, quantity and number of the equipment being put into operation.

[0013] Compared with the prior art, the beneficial effects of the present invention are as follows: the material intelligent identification module of the present invention can accurately identify and analyze the processing materials, collect images through a high-definition camera and match them with the preset integrated images in the intelligent CNC terminal, and combine the weight parameters obtained by the weight sensor to comprehensively evaluate the condition of the materials. For materials with cracks, holes, weight differences and contamination by hair and dust, the degree of defects can be accurately judged. If the material defect index exceeds the preset value, it is marked as defective material in time and a replacement signal is generated, which effectively avoids the processing of poor materials, reduces the scrap rate caused by material problems, ensures stable and reliable product quality, and avoids damage to cutting tools and other equipment caused by material defects during the processing. The adjustment module intelligently replaces defective materials according to the scientifically calculated material replacement priority value, comprehensively considers factors such as the warehousing time of the screened materials, the replacement distance of the equipment and the quality inspection report score, ensures that the replaced materials are of qualified quality, makes the material replacement process more efficient and reasonable, reduces the impact of material replacement on production progress, and improves the efficiency of the processing process. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. The following drawings are not intentionally scaled to the actual size, and the focus is on illustrating the main purpose of the present invention.

[0015] Figure 1 It is a principle block diagram of the present invention. DETAILED DESCRIPTION

[0016] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work also fall within the scope of protection of the present invention.

[0017] Please refer to Figure 1 As shown, the present invention is an intelligent numerical control system for numerically controlled machine tools, including an intelligent acquisition module, a material intelligent identification module, an adjustment module, an intelligent fault prediction module, a processing module, an intelligent numerical control terminal and a database.

[0018] The intelligent acquisition module installs various types of sensors on each CNC machine tool equipment to collect the equipment status and processing material information of each CNC machine tool equipment in real time. The specific process is as follows: Install a high-definition camera at each position of each CNC machine tool to collect the image data of each material to be processed in real time, and obtain the image data of each material to be processed; install a weight sensor on the material transmission path of each CNC machine tool to collect the weight parameter value of each material to be processed in real time, and the output end of the intelligent acquisition module is connected to the input end of the material intelligent identification module, and the image data and weight parameter value of each material to be processed are sent to the material intelligent identification module. Figure 1 The direction with an arrow is the input end, and the direction without an arrow is the output end.

[0019] The material intelligent recognition module matches the preset integrated images of various types of processing materials in the intelligent CNC terminal with the actual processing material images obtained by the current high-definition camera. The specific process is as follows: S01: the output end of the material intelligent recognition module is connected to the input end of the adjustment module, and the input end of the material intelligent recognition module is connected to the output end of the database. The material intelligent recognition module includes an information receiving unit, an intelligent recognition unit and an analysis unit. The information receiving unit obtains the image of the material to be processed and the weight parameter value of the material to be processed obtained by the current high-definition camera, and sends the image of the material to be processed to the intelligent numerical control terminal and the intelligent recognition unit; S02: The intelligent numerical control terminal receives the image of the material to be processed and generates a search instruction and sends it to the search unit. The search unit obtains the corresponding preset integrated image according to the image of the material to be processed and sends it to the intelligent recognition unit. The intelligent recognition unit matches the current image to be processed with the preset integrated image for the type of processing material. If the type matching is successful, the intelligent recognition unit continues to recognize the appearance of the current image of the material to be processed. S03: The intelligent recognition unit recognizes cracks and holes in the image of the material to be processed and extracts the number of cracks in the image of the material to be processed and the total crack area ; Extract the number of holes in the image of the material to be processed and the total volume of the pores , i represents the number of the image of the material to be processed, i=1, 2, ..., n; S04: extracting features of hair and dust particles of each processed material, converting the acquired processed material image into a grayscale image, obtaining the total pixel value number of the processed material image, extracting the pixel value number of hair and dust particles, marking them as the total pixel value affected, and obtaining the relative pollution coefficient RT based on the total pixel value number and the total pollution pixel value; S05: Obtain the weight parameter value of the current material to be processed, extract the preset weight parameter value of the corresponding material to be processed in the database, and subtract the actual weight parameter value from the preset weight parameter value to obtain the weight difference value of the current material to be processed, which is marked as GK; S06: Calculate based on the relative contamination coefficient, weight difference, number of cracks, total crack area, number of holes and total hole volume of the material to be processed, using the formula The material defect index TH of the current material to be processed is obtained, wherein D1, D2, D3 and D4 are preset proportional coefficients, which are 0.37, 0.45, 0.74 and 1.21 respectively. The preset material defect index in the database is extracted, and the material defect index of the current processing material is compared with the preset material defect index. If the material defect index of the current processing material is greater than the preset material defect index, the processing material is marked as a defective material, and a replacement signal is generated and sent to the adjustment module.

[0020] The adjustment module intelligently replaces the processing materials that have been determined to be defective materials according to the material replacement priority value. The specific acquisition process is as follows: K01: The output end of the adjustment module is connected to the input end of the database. The adjustment module receives the replacement signal, obtains the material type and specification of the current defective material, generates a query instruction according to the material type and specification, and sends it to the database. The database receives the query instruction and selects a list of replacement materials according to the material type and specification, marks the materials in the material list as screened materials, obtains the storage time point of each screened material, and subtracts the storage time point of each screened material from the current system time point to obtain the storage time of each material, arranges the storage time from small to large, obtains the maximum storage time, and marks it as ; K02: Take the CNC machine tool equipment of the material to be replaced as the center point, obtain the position of each screening material, connect the CNC machine tool equipment of the material to be replaced and the position of each screening material, obtain the distance value of each replacement line, and obtain the minimum replacement distance value ; K03: Set the score value of each screening material quality test report ; Calculate the maximum storage time, minimum replacement distance and score value, and use the formula The replacement priority value TW of each screened material is obtained, where B1, B2 and B3 are the weights corresponding to the maximum warehousing time, the minimum replacement distance value and the score value respectively. The screened materials are arranged from large to small according to the replacement priority value, and the screened material with the largest replacement priority value is marked as the priority replacement material. The position of the priority replacement material is obtained and sent to the adjustment module. The adjustment module generates a replacement instruction according to the position of the priority replacement material and sends it to the mobile phone terminal of the nearby staff, and the staff replaces the material.

[0021] The intelligent fault prediction module monitors and analyzes the historical operating status of each CNC machine tool equipment and determines the fault results of each CNC machine tool equipment. The specific process is as follows: F01: The input end of the intelligent fault prediction module is connected to the output end of the database. The intelligent fault prediction module includes a feature extraction unit and a fault analysis unit. The feature extraction unit obtains the historical maintenance times, maintenance duration, maintenance parts replacement frequency and fault interval time of each CNC machine tool equipment, which are marked as DK, DY, DH and DA respectively; F02: Obtain the operation time point of each CNC machine tool equipment, and as of the current operation time point, make a difference between the operation time point of each CNC machine tool equipment and the current operation time point to obtain the cumulative operation time QT of each CNC machine tool equipment, obtain the current operation value of the equipment within the cumulative operation time, extract the standard current operation range in the database, compare the current operation value of the equipment with the standard current operation range, mark the current value greater than or less than the standard current operation range as an abnormal current value, count the number and duration of abnormal current values, obtain the number of abnormal currents QA and the total abnormal duration QK, and the feature extraction unit sends the obtained data to the fault analysis unit; F03: The fault analysis unit calculates the historical maintenance times, maintenance duration, maintenance parts replacement frequency, fault interval, cumulative operation time, abnormal current times and total abnormal duration of each CNC machine tool equipment using the formula The fault tendency index FPG of each CNC machine tool equipment is obtained, where R1, R2, R3, R4, R5, R6 and R7 are preset proportional coefficients, the preset fault tendency index of the data center is extracted, and the actual fault tendency index of the equipment on each CNC machine tool is compared with the preset fault tendency index. If the actual fault tendency index of the equipment on the CNC machine tool is greater than the preset fault tendency index, the corresponding CNC machine tool equipment is marked as a high-risk fault equipment, and a detection signal is generated and sent to the processing module.

[0022] The processing module obtains the location of the corresponding high-risk equipment for fault repair based on the received detection signal. The specific process is as follows: The processing module receives the detection signal, and the input end of the processing module is connected to the port of the database to obtain the location of the high-risk equipment in real time. The location of the mobile terminal of each maintenance personnel is screened based on the high-risk equipment, the nearest mobile terminal location is obtained, and a maintenance instruction is generated and sent to the mobile terminal of the corresponding maintenance personnel for repair.

[0023] The intelligent CNC terminal includes a storage unit and a retrieval unit. It uses an industrial camera to collect all-round images of various types of processing materials. The all-round images include front images, side images and oblique images. The images of various directions of various types of processing materials are integrated to obtain preset integrated images of various types of processing materials and send them to the storage unit. The storage unit numbers each preset integrated image and records the corresponding processing material type, batch and supplier information. The retrieval unit connects with each preset integrated image number and creates an index. The index is each instruction action generated by the CNC machine tool equipment.

[0024] The port of the database is connected to each intelligent CNC terminal. One CNC machine tool equipment corresponds to one intelligent CNC terminal. The database stores the inventory information of various processing materials and the information of each CNC machine tool equipment. The inventory information includes the type, specification, quantity, storage location and warehousing time of the material. The information of each CNC machine tool equipment includes the time point, quantity and number of the equipment being put into operation.

[0025] The above is an explanation of the present invention and should not be considered as a limitation thereof. Although several exemplary embodiments of the present invention have been described, it will be readily appreciated by those skilled in the art that many modifications may be made to the exemplary embodiments without departing from the novel teachings and advantages of the present invention. Therefore, all such modifications are intended to be included within the scope of the present invention as defined in the claims. It should be understood that the above is an explanation of the present invention and should not be considered as being limited to the specific embodiments disclosed, and modifications to the disclosed embodiments and other embodiments are intended to be included within the scope of the appended claims. The present invention is defined by the claims and their equivalents.

Claims

1. An intelligent numerical control system for a numerically controlled machine tool, characterized in that: It includes intelligent acquisition module, material intelligent identification module, intelligent fault prediction module, processing module, intelligent CNC terminal and database, and also includes adjustment module; The adjustment module intelligently replaces the processing materials that have been determined to be defective materials according to the material replacement priority value. The output end of the adjustment module is connected to the input end of the database. The adjustment module receives the replacement signal, obtains the material type and specification of the current defective material, generates a query instruction according to the material type and specification, and sends it to the database. The database receives the query instruction and selects a list of materials for replacement according to the material type and specification, marks the materials in the material list as screened materials, obtains the storage time point of each screened material, and as of the current system time point, subtracts the storage time point of each screened material from the current system time point to obtain each storage duration, arranges each storage duration from small to large, and obtains the maximum storage duration ; Take the CNC machine tool equipment of the material to be replaced as the center point, obtain the position of each screening material, connect the CNC machine tool equipment of the material to be replaced and the position of each screening material, obtain the distance value of each replacement line, and obtain the minimum replacement distance value ; Set the score value for each screening material quality test report ; Calculate the maximum storage time, minimum replacement distance and score value, and use the formula The replacement priority value TW of each screened material is obtained, where B1, B2 and B3 are the weights corresponding to the maximum warehousing time, the minimum replacement distance value and the score value respectively, f represents the number of the screened material, g represents the total number of the screened materials, and each screened material is arranged from large to small according to the replacement priority value, and the screened material with the largest replacement priority value is marked as the priority replacement material. The position of the priority replacement material is obtained and sent to the adjustment module. The adjustment module generates a replacement instruction according to the position of the priority replacement material and sends it to the mobile phone terminal of the nearby staff, and the staff replaces the material.

2. The intelligent numerical control system for numerically controlled machine tools according to claim 1, characterized in that: The material intelligent recognition module matches the preset integrated images of various types of processing materials in the intelligent CNC terminal with the actual processing material images obtained by the current high-definition camera. The specific process is as follows: The output end of the material intelligent recognition module is connected to the input end of the adjustment module. The material intelligent recognition module includes an information receiving unit. The information receiving unit obtains the image of the material to be processed and the weight parameter value of the material to be processed obtained by the current high-definition camera, and sends the image of the material to be processed to the intelligent numerical control terminal and the intelligent recognition unit. The intelligent numerical control terminal receives the image of the material to be processed and generates a retrieval instruction and sends it to the retrieval unit. The retrieval unit obtains the corresponding preset integrated image according to the image of the material to be processed and sends it to the intelligent recognition unit.

3. The intelligent numerical control system for numerically controlled machine tools according to claim 2, characterized in that: The material intelligent identification module also includes an intelligent identification unit and an analysis unit. The specific process is as follows: The intelligent recognition unit matches the processing material type between the current image to be processed and the preset integrated image. If the type match is successful, the intelligent recognition unit continues to recognize the appearance of the current image of the material to be processed. The intelligent recognition unit identifies cracks and holes in the image of the material to be processed and extracts the number of cracks in the image of the material to be processed and the total crack area ; Extract the number of holes in the image of the material to be processed and the total volume of the pores ; Extract features of hair and dust particles of each processed material, convert the acquired processed material image into a grayscale image, obtain the total pixel value number of the processed material image, extract the pixel value number of hair and dust particles, mark it as the total pixel value affected, and obtain the relative pollution coefficient RT based on the total pixel value number and the total pollution pixel amount; Obtain the weight parameter value of the current material to be processed, extract the preset weight parameter value of the corresponding material to be processed in the database, and subtract the actual weight parameter value from the preset weight parameter value to obtain the weight difference value of the current material to be processed, marked as GK; The calculation is based on the relative contamination coefficient, weight difference, number of cracks, total crack area, number of holes and total hole volume of the material to be processed, using the formula The material defect index TH of the current material to be processed is obtained, wherein D1, D2, D3 and D4 are preset proportional coefficients, the preset material defect index in the database is extracted, and the material defect index of the current processing material is compared with the preset material defect index. If the material defect index of the current processing material is greater than the preset material defect index, the processing material is marked as a defective material, and a replacement signal is generated and sent to the adjustment module.

4. The intelligent numerical control system for numerically controlled machine tools according to claim 1, characterized in that: The feature extraction unit of the intelligent fault prediction module monitors the historical operating status of each CNC machine tool equipment. The specific process is as follows: The input end of the intelligent fault prediction module is connected to the output end of the database. The intelligent fault prediction module includes a feature extraction unit and a fault analysis unit. The feature extraction unit obtains the historical maintenance times, maintenance time, maintenance parts replacement frequency and fault interval time of each CNC machine tool equipment, which are marked as DK, DY, DH and DA respectively; obtains the operation time point of each CNC machine tool equipment, and as of the current operation time point, makes a difference between the operation time point of each CNC machine tool equipment and the current operation time point to obtain the cumulative operation time QT of each CNC machine tool equipment, obtains the current operation value of the equipment within the cumulative operation time, extracts the standard current operation range in the database, compares the current operation value of the equipment with the standard current operation range, marks the current value greater than or less than the standard current operation range as an abnormal current value, counts the number and duration of abnormal current values, obtains the number of abnormal currents QA and the total abnormal duration QK, and the feature extraction unit sends the obtained data to the fault analysis unit.

5. The intelligent numerical control system for numerically controlled machine tools according to claim 4, characterized in that: The fault analysis unit determines the fault results of each CNC machine tool equipment based on the data. The specific process is as follows: The fault analysis unit calculates the historical maintenance times, maintenance time, maintenance parts replacement frequency, fault interval, cumulative operation time, abnormal current times and total abnormal duration of each CNC machine tool equipment using the formula The fault tendency index FPG of each CNC machine tool equipment is obtained, where R1, R2, R3, R4, R5, R6 and R7 are preset proportional coefficients, the preset fault tendency index of the data center is extracted, and the actual fault tendency index of the equipment on each CNC machine tool is compared with the preset fault tendency index. If the actual fault tendency index of the equipment on the CNC machine tool is greater than the preset fault tendency index, the corresponding CNC machine tool equipment is marked as a high-risk fault equipment, and a detection signal is generated and sent to the processing module.

6. The intelligent numerical control system for numerically controlled machine tools according to claim 1, characterized in that: The processing module obtains the location of the corresponding high-risk equipment for fault repair based on the received detection signal. The specific process is as follows: The processing module receives the detection signal, and the input end of the processing module is connected to the port of the database to obtain the location of the high-risk equipment in real time. The location of the mobile terminal of each maintenance personnel is screened based on the high-risk equipment, the nearest mobile terminal location is obtained, and a maintenance instruction is generated and sent to the mobile terminal of the corresponding maintenance personnel for repair.

7. The intelligent numerical control system for numerically controlled machine tools according to claim 1, characterized in that: The specific process is as follows: the intelligent CNC terminal includes a storage unit and a retrieval unit. It uses an industrial camera to collect all-round images of various types of processing materials. The all-round images include front images, side images and oblique images. The images of various directions of various types of processing materials are integrated to obtain preset integrated images of various types of processing materials and send them to the storage unit. The storage unit numbers each preset integrated image and records the corresponding processing material type, batch and supplier information.

8. The intelligent numerical control system for numerically controlled machine tools according to claim 7, characterized in that: The specific process is as follows: the retrieval unit of the intelligent CNC terminal is connected with each preset integrated image number and creates an index, and the index is each instruction action generated by the CNC machine tool equipment.

9. The intelligent numerical control system for numerically controlled machine tools according to claim 1, characterized in that: The specific process is as follows: the port of the database is connected to each intelligent CNC terminal, and one CNC machine tool equipment corresponds to one intelligent CNC terminal. The database stores the inventory information of various processing materials and the information of each CNC machine tool equipment. The inventory information includes the type, specification, quantity, storage location and warehousing time of the material. The information of each CNC machine tool equipment includes the time point, quantity and number of the equipment being put into operation.

10. The intelligent numerical control system for numerically controlled machine tools according to claim 1, characterized in that: The intelligent acquisition module installs various types of sensors on each CNC machine tool equipment to collect the equipment status and processing material information of each CNC machine tool equipment in real time. The specific process is as follows: A high-definition camera is installed at each position of each CNC machine tool equipment to collect image data of each material to be processed in real time and obtain image data of each material to be processed; a weight sensor is installed on the material transmission path of each CNC machine tool to collect weight parameter values ​​of each material to be processed in real time, and the output end of the intelligent acquisition module is connected to the input end of the material intelligent recognition module to send the image data and weight parameter values ​​of each material to be processed to the material intelligent recognition module.

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