Milling blade detection system

Abstract

The invention discloses a milling blade detection system, which is characterized in that a processing analysis module performs first analysis processing on input initial data including image data, mechanical data, acoustic data and vibration data, and compares the data with a preset parameter database, so that detection parameters of each detection module are dynamically adjusted; each detection module carries out matching detection on the working condition of the current milling blade, and then carries out second analysis processing on the obtained actual data to obtain the final detection data of the current milling blade. According to the milling blade detection system disclosed by the invention, the optical detection module, the mechanical detection module, the acoustic detection module, the vibration detection module and the processing analysis module are linked, and each parameter of the milling blade is automatically detected and analyzed according to different analysis modes, so that final detection data of the milling blade are obtained.

Description

Technical Field

[0001] The invention belongs to the technical field of milling blade detection, and in particular relates to a milling blade detection system. Background Art

[0002] Milling inserts are commonly used tool components in mechanical processing, and their quality directly affects processing accuracy and efficiency. In actual production, problems such as wear, cracks, and dimensional deviations of milling inserts may lead to processing defects and even cause safety accidents. At present, the inspection of milling inserts mainly relies on manual visual inspection or simple measuring tools. This method is inefficient and has poor accuracy, and it is difficult to meet the high requirements of modern manufacturing for tool inspection.

[0003] Therefore, further improvements are made to the above problems. Summary of the invention

[0004] The main purpose of the present invention is to provide a milling blade detection system, which is linked through an optical detection module, a mechanical detection module, an acoustic detection module, a vibration detection module and a processing and analysis module, and automatically detects and analyzes various parameters of the milling blade according to different analysis modes, so as to obtain the final detection data of the milling blade.

[0005] To achieve the above objectives, the present invention provides a milling blade detection system, including an optical detection module, a mechanical detection module, an acoustic detection module, a vibration detection module and a processing and analysis module, wherein:

[0006] The optical detection module collects images of the milling blade through an industrial camera, and transmits the pre-processed (noise removal, edge feature enhancement) image data to the processing and analysis module;

[0007] The mechanical detection module monitors the force change of the milling blade in real time through a piezoelectric force sensor installed on the milling blade, and transmits the pre-processed (force signal converted into digital signal) mechanical data to the processing and analysis module;

[0008] The acoustic detection module collects the sound signal generated by the milling blade when it is working through the microphone array, and transmits the acoustic data that has been pre-processed (filtering and amplification processing, removing environmental noise, using algorithms such as short-time Fourier transform, analyzing the frequency and amplitude characteristics of the sound) to the processing and analysis module;

[0009] The vibration detection module monitors the vibration of the milling cutter in real time through an accelerometer installed on the milling cutter, and transmits the pre-processed (the vibration data is subjected to fast Fourier transformation to obtain vibration spectrum information) vibration data to the processing and analysis module;

[0010] The processing and analysis module performs a first analysis and processing on the input initial data including image data, mechanical data, acoustic data, and vibration data, and compares it with a pre-set parameter database, so as to dynamically adjust the detection parameters of each detection module, enabling each detection module to perform matching detection on the current working conditions of the milling insert, and then performs a second analysis and processing on the obtained actual data to obtain the final detection data of the current milling insert.

[0011] As a further preferred technical solution of the above technical solution, the setting of the parameter database is specifically implemented as follows:

[0012] Collect data including images, mechanics, acoustics, and vibrations of different types of milling inserts under various working conditions, establish a data set, and analyze and annotate the data in the data set. On the one hand, clarify the normal data of different types of milling inserts in different usage stages and processing tasks; on the other hand, clarify the abnormal data (including defect types, positions, and degrees) of different types of milling inserts in different usage stages and processing tasks.

[0013] As a further preferred technical solution of the above technical solution, the processing and analysis module learns the specific type, specific usage stage, and specific processing task of the current milling insert according to the initial data, and thus compares it with the normal data, so as to obtain the detection parameters corresponding to the specific working conditions of the milling insert (for different milling inserts under different working conditions, the detection parameters of the detection module are different, such as the exposure time of the camera, the recording ranges of the force sensor, microphone array, and accelerometer, etc.), and adjusts the detection parameters of the optical detection module, mechanical detection module, acoustic detection module, and vibration detection module through feedback from the processing and analysis module;

[0014] Then, the processing and analysis module performs a second analysis and processing on the re-input actual data including image data, mechanical data, acoustic data, and vibration data, and compares it with the abnormal data.

[0015] As a further preferred technical solution of the above technical solution, the second analysis and processing includes comprehensive analysis and processing and dynamic analysis and processing (select the second analysis and processing according to different requirements), where:

[0016] For the comprehensive analysis and processing, input the actual data including image data, mechanical data, acoustic data, and vibration data into a multi-modal data fusion model to perform fusion analysis on the data, set different weights for different data, so as to obtain an actual comprehensive score, and compare it with the abnormal comprehensive score corresponding to the abnormal data. If the actual comprehensive score reaches the abnormal comprehensive score, it indicates that the current milling insert is working abnormally and an alarm is issued. If the actual comprehensive score does not reach the abnormal comprehensive score, it indicates that the current milling insert is working normally;

[0017] For dynamic analysis and processing, the first, second, and third detection processes are set, where:

[0018] For the first detection process, appearance detection is performed through image data, abnormal data (image data therein) is compared, and milling cutters that may have appearance defects are obtained. If not, the first detection continues; if so, the second detection process is executed.

[0019] For the second detection process, acoustic and vibration detections are performed on the milling cutters with appearance defects, abnormal data (acoustic and vibration data therein) is compared, and milling cutters that may have acoustic and vibration defects are obtained. If not, the second detection process continues; if so, the third detection process is executed.

[0020] For the third detection process, for the milling cutters with acoustic and vibration defects, abnormal data (mechanical data therein) is compared, and milling cutters that may have mechanical defects are obtained. If not, the third detection process continues; if so, it indicates that the current milling cutter is working abnormally and an alarm is given.

[0021] As a further preferred technical solution of the above technical solution, the processing and analysis module further includes a display screen. For dynamic analysis and processing, when the first detection process is executed, the display screen displays the first information; when the second detection process is executed, the display screen displays the second information; when the third detection process is executed, the display screen displays the third information (the current detection process being processed can be obtained through different display information). Brief Description of the Drawings

[0022] Figure 1 is a schematic structural diagram of the present invention. Detailed Embodiment

[0023] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art can think of other obvious variations. The basic principles defined in the following description can be applied to other embodiments, variations, improvements, equivalent solutions, and other technical solutions that do not depart from the spirit and scope of the present invention.

[0024] In the preferred embodiment of the present invention, those skilled in the art should note that the milling cutters and the like involved in the present invention can be regarded as the prior art.

[0025] Preferred Embodiment.

[0026] As Figure 1 shown, the present invention discloses a milling cutter detection system, including an optical detection module, a mechanical detection module, an acoustic detection module, a vibration detection module, and a processing and analysis module, where:

[0027] The optical detection module collects images of the milling inserts through an industrial camera and transmits the pre-processed (noise removal, edge feature enhancement) image data to the processing and analysis module;

[0028] The mechanical detection module monitors the force changes of the milling inserts in real time through piezoelectric force sensors installed on the milling inserts and transmits the pre-processed (converting force signals into digital signals) mechanical data to the processing and analysis module;

[0029] The acoustic detection module collects the sound signals generated during the operation of the milling inserts through a microphone array and transmits the pre-processed (filtering and amplification processing, removing ambient noise, using algorithms such as short-time Fourier transform to analyze the frequency and amplitude characteristics of the sound) acoustic data to the processing and analysis module;

[0030] The vibration detection module monitors the vibration of the milling inserts in real time through accelerometers installed on the milling inserts and transmits the pre-processed (performing fast Fourier transform on the vibration data to obtain vibration spectrum information) vibration data to the processing and analysis module;

[0031] The processing and analysis module performs a first analysis and processing on the input initial data including image data, mechanical data, acoustic data, and vibration data, compares it with a pre-set parameter database, and thus dynamically adjusts the detection parameters of each detection module, so that each detection module performs matching detection for the current working conditions of the milling inserts, and then performs a second analysis and processing on the obtained actual data to obtain the final detection data of the current milling inserts.

[0032] Specifically, the setting of the parameter database is specifically implemented as follows:

[0033] Collect data including images, mechanics, acoustics, and vibrations of different types of milling inserts under various working conditions, establish a data set, and analyze and label the data in the data set. On the one hand, clarify the normal data of different types of milling inserts at different usage stages and processing tasks; on the other hand, clarify the abnormal data (including defect types, positions, and degrees) of different types of milling inserts at different usage stages and processing tasks.

[0034] More specifically, the processing and analysis module learns the specific type, specific usage stage, and specific processing task of the current milling insert based on the initial data, and thus compares it with the normal data, so as to obtain the detection parameters corresponding to the specific working conditions of the milling insert (for different milling inserts under different working conditions, the detection parameters of the detection module are different, such as the exposure time of the camera, the recording ranges of the force sensor, microphone array, and accelerometer, etc.), and feedback and adjust the detection parameters of the optical detection module, mechanical detection module, acoustic detection module, and vibration detection module through the processing and analysis module;

[0035] Then, the processing and analysis module performs a second analysis and processing on the actual data including image data, mechanical data, acoustic data, and vibration data that is re-input, and compares it with the abnormal data.

[0036] Furthermore, the second analysis and processing includes comprehensive analysis and dynamic analysis (select the second analysis and processing according to different requirements), where:

[0037] For the comprehensive analysis and processing, the actual data including image data, mechanical data, acoustic data, and vibration data is input into a multi-modal data fusion model to perform fusion analysis on the data, and different weights are set for different data, so as to obtain an actual comprehensive score, and compare it with the abnormal comprehensive score corresponding to the abnormal data. If the actual comprehensive score reaches the abnormal comprehensive score, it indicates that the current milling cutter blade is working abnormally and an alarm is issued. If the actual comprehensive score does not reach the abnormal comprehensive score, it indicates that the current milling cutter blade is working normally;

[0038] For the dynamic analysis and processing, the first, second, and third detection processes are set, where:

[0039] For the first detection process, perform an appearance detection through the image data, compare the abnormal data (the image data in it), and obtain the milling cutter blade that may have an appearance defect. If not, continue the first detection process. If so, execute the second detection process;

[0040] For the second detection process, perform acoustic and vibration detections on the milling cutter blade with an appearance defect, compare the abnormal data (the acoustic and vibration data in it), and obtain the milling cutter blade that may have acoustic and vibration defects. If not, continue the second detection process. If so, execute the third detection process;

[0041] For the third detection process, for the milling cutter blade with acoustic and vibration defects, compare the abnormal data (the mechanical data in it), and obtain the milling cutter blade that may have a mechanical defect. If not, continue the third detection process. If so, it indicates that the current milling cutter blade is working abnormally and an alarm is issued.

[0042] Even further, the processing and analysis module further includes a display screen. For the dynamic analysis and processing, when the first detection process is executed, the display screen displays the first information; when the second detection process is executed, the display screen displays the second information; when the third detection process is executed, the display screen displays the third information (the current detection process can be obtained through different display information).

[0043] It is worth mentioning that technical features such as milling inserts involved in this invention patent application should be regarded as prior art. For the specific structures, working principles, possible control methods, and spatial arrangement methods of these technical features, conventional selections in the art can be adopted, and they should not be regarded as the invention points of this invention patent. This invention patent will not be further specifically elaborated.

[0044] For those skilled in the art, it is still possible to modify the technical solutions described in the foregoing embodiments or make equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included in the protection scope of the present invention.

Claims

1. A milling insert detection system, characterized in that, It includes an optical detection module, a mechanical detection module, an acoustic detection module, a vibration detection module and a processing and analysis module, wherein: The optical detection module collects images of the milling blade through an industrial camera and transmits the pre-processed image data to the processing and analysis module; The mechanical detection module monitors the force change of the milling blade in real time through a piezoelectric force sensor installed on the milling blade, and transmits the pre-processed mechanical data to the processing and analysis module; The acoustic detection module collects the sound signal generated by the milling blade when it is working through the microphone array, and transmits the pre-processed acoustic data to the processing and analysis module; The vibration detection module monitors the vibration of the milling cutter in real time through an accelerometer installed on the milling cutter, and transmits the pre-processed vibration data to the processing and analysis module; The processing and analysis module performs a first analysis on the input initial data including image data, mechanical data, acoustic data and vibration data, and compares it with a preset parameter database, thereby dynamically adjusting the detection parameters of each detection module so that each detection module performs matching detection on the working condition of the current milling cutter blade, and then performs a second analysis on the actual data obtained to obtain the final detection data of the current milling cutter blade.

2. The milling insert detection system according to claim 1, wherein, The specific implementation of setting the parameter database is as follows: Data including images, mechanics, acoustics, and vibrations of different types of milling inserts under various working conditions are collected, a data set is established, and the data in the data set is analyzed and labeled. On the one hand, the normal data of different types of milling inserts in different usage stages and processing tasks are clarified; on the other hand, the abnormal data of different types of milling inserts in different usage stages and processing tasks are clarified.

3. The milling insert detection system according to claim 2, wherein The processing and analysis module obtains the specific type, specific use stage and specific processing task of the current milling blade according to the initial data, and compares it with the normal data to obtain the detection parameters corresponding to the specific working condition of the milling blade, and adjusts the detection parameters of the optical detection module, the mechanical detection module, the acoustic detection module and the vibration detection module through feedback from the processing and analysis module; Then, the processing and analysis module performs a second analysis process on the re-input actual data including image data, mechanical data, acoustic data and vibration data, and compares it with the abnormal data.

4. The milling insert detection system according to claim 3, wherein The second analysis process includes comprehensive analysis process and dynamic analysis process, wherein: For comprehensive analysis and processing, actual data including image data, mechanical data, acoustic data and vibration data are input into the multimodal data fusion model to perform fusion analysis on the data. Different weights are set for different data to obtain the actual comprehensive score, which is compared with the abnormal comprehensive score corresponding to the abnormal data. If the actual comprehensive score reaches the abnormal comprehensive score, it means that the current milling cutter is working abnormally and an alarm is issued. If the actual comprehensive score does not reach the abnormal comprehensive score, it means that the current milling cutter is working normally. For dynamic analysis processing, the first, second and third detection processes are set, where: For the first detection process, perform appearance detection through image data, compare abnormal data, and obtain milling inserts that may have appearance defects. If none are found, continue the first detection process. If any are found, execute the second detection process; For the second detection process, perform acoustic and vibration detection on the milling inserts with appearance defects, compare abnormal data, and obtain milling inserts that may have acoustic and vibration defects. If none are found, continue the second detection process. If any are found, execute the third detection process; For the third detection process, for the milling inserts with acoustic and vibration defects, compare abnormal data and obtain milling inserts that may have mechanical defects. If none are found, continue the third detection process. If any are found, it indicates that the current milling insert is working abnormally and an alarm is issued.

5. A milling insert detection system according to claim 4, characterized in that, The processing and analysis module further includes a display screen. For dynamic analysis and processing, when the first detection process is executed, the display screen shows the first information; when the second detection process is executed, the display screen shows the second information; When the third detection process is executed, the display screen shows the third information.

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