Microelectrode on-line monitoring device and monitoring method

Abstract

The application relates to an online monitoring device and method for microelectrodes, and belongs to the technical field of special machining.The online monitoring device is composed of a coaxial holographic imaging module, an LED backlight imaging module, a motion control module, an image acquisition card, a laser power controller and an LED brightness controller.The LED backlight imaging module is used for positioning the microelectrode image; the coaxial holographic imaging module is used for holographic interference imaging of the microelectrode; based on a holographic reconstruction algorithm, electrode profile information is obtained, and the electrode loss degree is judged.The coaxial holographic imaging module and the LED backlight imaging module switch the positions of the reflecting mirrors through the motion control module to realize control of different imaging modes; the collected images are input into a PC through the image acquisition card, image algorithm analysis is carried out, and the microelectrode loss degree is judged.The application realizes online monitoring of the microelectrode loss.

Description

Technical Field

[0001] This invention belongs to the field of special processing technology, and in particular relates to an online monitoring device and method for micro-electrodes. Background Technology

[0002] Micro-electrical discharge machining (EDM) technology is widely used in the manufacturing of complex micro-parts such as micro-three-dimensional structural parts and micro-hole machining. During the micro-electrical discharge machining process, electrode wear occurs on the micro-electrodes, which greatly affects the shape and dimensional accuracy of the machined workpiece. Therefore, it is necessary to set electrode compensation amounts or trim the electrodes during machining.

[0003] Setting electrode compensation during machining requires precise measurement of the micro-electrodes. However, current microscopic measurement methods present a trade-off between measurement range and accuracy. Due to the small size of the micro-electrodes, very expensive microscopic measurement equipment is required, while the measurement range is limited. If offline electrode dressing is used, resulting in secondary workpiece clamping, positioning errors inevitably occur, leading to a decrease in machining accuracy.

[0004] Currently, machine vision technology is commonly used for monitoring microelectrodes. However, due to the need for different microscope lenses, imaging and measurement can only be performed on electrodes within a certain size range. Furthermore, high-precision calibration plates are required to calibrate the pixels to correspond to their actual dimensions, making the measurement process cumbersome. Therefore, the proposal of an online monitoring module and method for microelectrodes has significant engineering and practical value. Summary of the Invention

[0005] The purpose of this invention is to provide an online monitoring device and method for micro-electrodes, which can be fully integrated into micro-electrical discharge machining tools to achieve rapid and high-precision monitoring of micro-electrode wear.

[0006] To achieve the above objectives, the specific technical solution of the micro-electrode online monitoring device and monitoring method of the present invention is as follows:

[0007] A micro-electrode online monitoring device includes a coaxial holographic imaging module, an LED backlight imaging module, a motion control module, and an image acquisition card. The image acquisition card is communicatively connected to CMOS camera I and CMOS camera II.

[0008] The coaxial holographic imaging module consists of a low-power laser source, a collimating beam expander, a CMOS camera I, and a laser power controller;

[0009] The LED backlight imaging module consists of an LED light source, a collimating lens group, a CMOS camera II, a low-magnification telecentric lens, and an LED brightness controller.

[0010] The motion control module consists of a motion translation stage I, a motion translation stage II, a reflector I, a reflector II, and a motion controller. Reflector I and reflector II are respectively mounted on motion translation stage I and motion translation stage II, and motion translation stage I and motion translation stage II are electrically connected to the motion controller.

[0011] The motion controller, LED brightness controller, laser power controller, and image acquisition card are all connected to the PC processor.

[0012] When mirror I and mirror II are at positions P0 and Q0 respectively, the coaxial holographic imaging module images the micro-electrodes mounted on the electrode main axis; when mirror I and mirror II are at positions P1 and Q1 respectively, the LED backlight imaging module images the micro-electrodes mounted on the electrode main axis.

[0013] The PC processor sends control signals to the laser power controller, which controls the low-power laser source to emit laser light. The laser light is collimated and expanded by the collimating and beam expander, and then deflected by the reflector I on the motion translation stage I to illuminate the micro electrode. The laser light then continues to propagate and is deflected by the reflector II on the motion translation stage II to enter the CMOS camera I for holographic coaxial interference imaging.

[0014] The PC processor sends control signals to the LED brightness controller, which controls the LED light source to emit an LED beam. The LED beam is collimated by a collimating lens group and deflected by a reflector II on a motion translation stage II, illuminating the micro-electrode. The LED light then continues to propagate and is deflected by a reflector I on a motion translation stage I, before entering the CMOS camera II through a low-magnification telecentric lens for LED backlight imaging.

[0015] Furthermore, protective light windows I and II are distributed on the same optical axis as reflectors I and II.

[0016] Furthermore, the LED light source is connected to the LED brightness controller for communication, and the LED brightness controller adjusts the light intensity of the LED light source, with the LED light source wavelength being in the visible light band.

[0017] This invention also provides an online monitoring method for microelectrodes, including a coarse positioning process for the microelectrodes and a detection process for the microelectrodes:

[0018] The coarse positioning process of the microelectrode includes the following steps, which are performed sequentially:

[0019] Step A1: Control the motion controller via PC to drive the motion control module and enable the LED backlight imaging module to work.

[0020] Step A2: Pre-set the candidate positioning box for the microelectrode imaging image, with the length and width set to half the image size, and the candidate positioning box coincides with the center of the image;

[0021] Step A3: Adjust the X-axis position of the micro-electrode, and the LED backlight imaging module will clearly image the micro-electrode.

[0022] Step A4: Obtain the position of the micro-electrode tip in the image by performing sub-pixel contour extraction;

[0023] Step A5: For the initial microelectrode, determine whether the end position of the microelectrode is at the center of the image. If it is not at the center of the image, repeat the precise adjustment of the electrode spindle position so that the end position of the microelectrode coincides with the center of the image, and record the coordinate value of the electrode spindle. Ensure that the electrode spindle moves to this coordinate value first during the subsequent microelectrode detection process.

[0024] The microelectrode detection process includes the following steps, which are performed sequentially:

[0025] Step B1: Control the motion controller via the PC processor to drive the motion control module and start the coaxial holographic imaging module into working mode;

[0026] Step B2: Acquire a hologram of a microelectrode, and use the candidate localization box size of the microelectrode imaging image from step A2 of the microelectrode coarse localization process to crop the hologram size to be consistent with the candidate localization box size;

[0027] Step B3: Use a super-resolution deep learning model to perform super-resolution reconstruction on the cropped hologram in step A2 to obtain a super-resolution hologram;

[0028] Step B4: Reconstruct the super-resolution hologram obtained in step B3 using the angular spectral method to obtain the reconstructed hologram;

[0029] Step B5: Extract the contour based on the reconstructed hologram from step B4 to obtain the micro-electrode contour;

[0030] Step B6: Based on the micro-electrode profile determination method in steps B1 to B5, obtain the initial and post-use profiles of the electrode, calculate the maximum profile deviation in the horizontal direction, compare it with the preset deviation, and determine the electrode compensation amount.

[0031] Furthermore, in step A3, a variance information entropy-based algorithm is used to determine whether the micro-electrode is in a clear position:

[0032]

[0033] Where σ 2 (i,xj,yj)For the image with (x j ,y j f(x) represents the local variance of the 3×3 neighborhood of the center point, μ represents the average gray level of that neighborhood, and f(x) represents the local variance of the 3×3 neighborhood of the center point. j +a,y j +b) is the image (x j +a,y j +b) Gray value at pixel;

[0034]

[0035] Where P i L represents the probability of each gray level occurring, and L is the total number of gray levels in the image, which is 256.

[0036] By judging H Var When the maximum value is reached, the micro-electrode image f is clearly imaged.

[0037] The online monitoring device and method for micro-electrodes of this invention have the following advantages: Utilizing the interferometric imaging principle of micro-electrodes at their micro-scale, it employs a composite method of telecentric vision micro-electrode image localization and coaxial holographic imaging detection. This enables online monitoring of electrode contour changes and allows for the determination of electrode wear levels. Simultaneously, low-magnification image localization reduces the computational load for holographic reconstruction, and a super-resolution deep learning model improves the resolution accuracy of the hologram. Compared to traditional machine vision and laser measurement methods, this method is easier to deploy on micro-electrical discharge machining tools and allows for easier quantification of micro-electrode wear levels, improving measurement accuracy and reliability. High-precision electrode wear measurement data can provide technical support for ultra-precision micro-electrical discharge machining. Attached Figure Description

[0038] Figure 1 This is a schematic diagram of the structure of an online monitoring device for microelectrodes according to the present invention.

[0039] Figure 2 This is a flowchart illustrating the coarse positioning process of a microelectrode in an online monitoring method for microelectrodes according to the present invention.

[0040] Figure 3 This is a flowchart illustrating the microelectrode detection process of an online microelectrode monitoring method according to the present invention.

[0041] Figure 4 This is a schematic diagram of a microelectrode detection image in an online monitoring method for microelectrodes according to the present invention.

[0042] The markings in the diagram are as follows: 1. Motion translation stage I; 2. Reflector I; 3. Collimating beam expander; 4. Low-power laser source; 5. CMOS camera II; 6. Low-magnification telecentric lens; 7. Protective window I; 8. Microelectrode; 9. Electrode spindle; 10. CMOS camera I; 11. Reflector II; 12. Protective window II; 13. LED light source; 14. Collimating lens group; 15. Motion translation stage II; 16. Laser power controller; 17. LED brightness controller; 18. Motion controller; 19. Image acquisition card; 20. PC processor; 21. Point P0; 22. Point P1; 23. Point Q0; 24. Point Q1; 25. LED backlight coaxial imaging optical path; 26. Laser coaxial holographic imaging optical path. Detailed Implementation

[0043] To better understand the purpose, structure, and function of this invention, the following detailed description of an online monitoring device and method for microelectrodes, in conjunction with the accompanying drawings, is provided.

[0044] This invention combines low-magnification coarse positioning of micro-electrodes with high-precision coaxial holographic measurement to identify electrode wear of micro-electrodes, thereby guiding electrode compensation and avoiding the degradation of processing quality caused by electrode wear during processing. It provides a new technical means for online monitoring of micro-electrodes.

[0045] Example:

[0046] A micro-electrode online monitoring module, such as Figure 1 As shown, it comprises a coaxial holographic imaging module, an LED backlight imaging module, a motion control module, and an image acquisition card 19. The coaxial holographic imaging module consists of a low-power laser source 4, a collimating beam expander 3, a CMOS camera I 10, and a laser power controller 16.

[0047] The coaxial holographic imaging module consists of a low-power laser source 4, a collimating beam expander 3, a CMOS camera I 10, and a laser power controller 16.

[0048] The LED backlight imaging module consists of an LED light source 13, a collimating lens group 14, a low-magnification telecentric lens 6, a CMOS camera II 5, and an LED brightness controller 17.

[0049] The motion control module consists of a motion translation stage I1, a motion translation stage II15, a reflector I2, a reflector II11, and a motion controller 18;

[0050] The motion controller 18, LED brightness controller 17, laser power controller 16, and PC processor 20 are connected in communication.

[0051] Image acquisition card 19 is communicatively connected to CMOS camera I 10, CMOS camera II 5 and PC processor 20;

[0052] The LED brightness controller 17 is connected to the PC processor 20;

[0053] Reflector I2 and reflector II11 are mounted on motion translation stages I1 and II15, respectively. When reflector I2 and reflector II11 are at positions P0 and Q0, respectively, the coaxial holographic imaging module images the micro-electrode 8 mounted on the electrode spindle 9; when reflector I2 and reflector II11 are at positions P1 and Q1, respectively, the LED backlight imaging module images the micro-electrode 8 mounted on the electrode spindle 9.

[0054] PC processor 20 sends control signals to laser power controller 16. Laser power controller 16 controls the low-power laser source 4 to emit laser light. The laser light is collimated and expanded by collimating and beam expander 3, and the optical path is deflected by reflector I2 on motion translation stage I1. The laser light then shines on micro electrode 8 through protective window I7. The laser light then continues to be transmitted to protective window II12, and the optical path is deflected by reflector II11 on motion translation stage II15. The laser light then enters CMOS camera I10 for holographic coaxial interference imaging.

[0055] PC processor 20 sends control signals to LED brightness controller 17. LED brightness controller 17 controls LED light source 13 to emit LED beams. The LED beams are collimated by collimating lens group 14 and deflected by reflector II11 on motion translation stage II15. The beams then illuminate micro-electrode 8 through protective light window II12. The LED light continues to be transmitted to protective light window I7 and then deflected by reflector I2 on motion translation stage I1. The beams then enter CMOS camera II5 through low-magnification telecentric lens 6 for LED backlight imaging.

[0056] In this embodiment, protective light windows I7 and II12 are distributed on the same optical axis as reflectors I2 and II11.

[0057] In this embodiment, the LED light source 13 is communicatively connected to the LED brightness controller 17, and the light intensity of the LED light source 13 is adjusted by the LED brightness controller 17, and the wavelength of the LED light source 13 is in the visible light band.

[0058] In this embodiment, the LED light source 13 is a white light source.

[0059] In this embodiment, the low-power laser source 4 has a wavelength of 635nm, a power of 3mw, and a spot diameter of 8mm.

[0060] In this embodiment, the collimating beam expander 3 has a beam expansion magnification of 2X.

[0061] In this embodiment, both motion translation stage I1 and motion translation stage II15 are micro servo motion platforms with a minimum movement of 0.1 μm.

[0062] In this embodiment, both CMOS camera I10 and CMOS camera II5 are monochrome area array CMOS cameras with global exposure mode, pixel size of 3.45μm, and pixel resolution of 2448x2048.

[0063] In this embodiment, the low-magnification telecentric lens 6 has a magnification of 3X.

[0064] In this embodiment, both the protective light window I7 and the protective light window II12 are made of high-transparency quartz glass.

[0065] In this embodiment, the diameter of the microelectrode 8 is 0.05 mm.

[0066] In this embodiment, the coaxial holographic imaging module, LED backlight imaging module, motion control module, image acquisition card 19 and PC processor 20 are interconnected and communicate with each other. The PC processor 20 issues motion control commands to realize image positioning and holographic image acquisition of the micro-electrode 8. In addition, the PC processor 20 is connected to the machine tool's UMAC control system via a network cable to transmit the movement commands of the electrode spindle 9 to the machine tool.

[0067] A method for online monitoring of a microelectrode 8 includes a coarse positioning process for the microelectrode 8 and a detection process for the microelectrode 8. The coarse positioning process for the microelectrode 8 includes the following steps, which are performed sequentially:

[0068] Step A1: Control the motion controller 18 through the PC processor 20 to drive the motion control module and start the working mode of the LED backlight imaging module.

[0069] Step A2: Pre-set the candidate positioning box for the microelectrode imaging image, with the length and width set to half the image size, and the candidate positioning box coincides with the center of the image.

[0070] Step A3: Adjust the X-axis position of the microelectrode 8. The LED backlight imaging module performs a clear imaging of the microelectrode 8 and uses a variance information entropy-based algorithm to determine whether the image f of the microelectrode 8 within the candidate positioning box is clear.

[0071]

[0072] in For the image with (x j ,y j f(x) represents the local variance of the 3×3 neighborhood of the center point, μ represents the average gray level of that neighborhood, and f(x) represents the local variance of the 3×3 neighborhood of the center point. j +a,y j +b) is the image (x j+a,y j +b) The grayscale value at pixel point.

[0073]

[0074] Where P i Let L be the probability of each gray level occurring, and L be the total number of gray levels in the image, which is 256.

[0075] By judging H Var When the maximum value is reached, the electrode image f is a clear image.

[0076] Step A4: Obtain the position of the end of the micro-electrode 8 in the image by performing sub-pixel contour extraction on the image;

[0077] Step A5: For the initial microelectrode 8, determine whether the end position of the microelectrode 8 is at the center of the image. If it is not at the center of the image, repeat the precise adjustment of the electrode spindle 9 position so that the end position of the electrode coincides with the center of the image, and record the coordinate value of the electrode spindle 9, and ensure that the electrode spindle 9 moves to this coordinate value first during the subsequent microelectrode 8 detection process.

[0078] The detection process of the microelectrode 8 includes the following steps, which are performed sequentially.

[0079] Step B1: The motion controller 18 is controlled by the PC processor 20 to drive the motion control module and start the coaxial holographic imaging module working mode.

[0080] Step B2: Acquire a hologram H0 of the microelectrode 8, and use the candidate positioning box size of the imaging image of the microelectrode 8 in the coarse positioning process of the microelectrode 8 in step A2 above to crop the hologram size to be consistent with the candidate positioning box size. At this time, the size of the cropped hologram H1 is 1224×1024.

[0081] Step B3: The Real-ESRGAN super-resolution deep learning model based on blind image super-resolution reconstruction model is used to perform 4x super-resolution reconstruction on the cropped hologram in step A2 to obtain super-resolution hologram H2. At this time, the size of hologram H2 is the same as that of H0.

[0082] Step B4: The super-resolution hologram obtained in step B3 is reconstructed using the angular spectral method to obtain the reconstructed hologram U;

[0083]

[0084] Where F{} represents the Fourier transform of the image, F -1 {} represents the inverse Fourier transform of the image, λ is the laser wavelength of 635nm, and f x f yis the frequency domain coordinate. z is the reconstruction distance of the microelectrode 8 in the X direction.

[0085] Step B5: Extract the contour based on the reconstructed hologram U from step B4 to obtain the contour map H4 of the microelectrode 8;

[0086] Step B6: Based on the contour determination method of the micro-electrode 8 in steps B1 to B5, obtain the initial and post-use contours of the electrode.

[0087] By horizontally projecting the contour image of the microelectrode 8, the position P of the last pixel row of the microelectrode 8 in the contour image is found, where P is initially and after use, respectively. o and P u Vertically project the contour image of the microelectrode 8 to find the leftmost column position CL and the rightmost column position CR of the microelectrode in the contour image. Between columns CL and CR, with row P as the bottommost point, set horizontal cross-sectional lines k with a spacing of d pixels upwards. Here, d is an integer, at least 1.

[0088] The initial microelectrode profile has pairs of profile points on different horizontal cross-sections, namely {I(i k ,CL),I(j k After the microelectrode is used, the contour point pairs on different horizontal cross-sections are {I(m)}. k ,CL),I(n k Starting from row P, calculate the set A = {|i} of the profile width values ​​of the initial microelectrode on different horizontal cross-sections from bottom to top. k -j k |}, the set of contour width values ​​B on different horizontal cross-sections after the microelectrode is used is B={|m k -n k |}.

[0089] If |AB| exceeds the preset deviation T, it is determined that the wear of the microelectrode exceeds the predetermined level, and the microelectrode 8 needs to be trimmed. Simultaneously, find the row coordinate n of the horizontal cross-section line k where |AB| is less than the minimum preset value Tmin in B. Determine the vertical trimming compensation amount of the microelectrode 8 as |P|. o -P u |+nd.

[0090] It is understood that the present invention has been described through some embodiments, and those skilled in the art will recognize that various changes or equivalent substitutions can be made to these features and embodiments without departing from the spirit and scope of the invention. Furthermore, under the teachings of the present invention, these features and embodiments can be modified to adapt to specific situations and materials without departing from the spirit and scope of the invention. Therefore, the present invention is not limited to the specific embodiments disclosed herein, and all embodiments falling within the scope of the claims of this application are within the protection scope of the present invention.

Claims

1. A microelectrode on-line monitoring device, characterized by, It comprises coaxial holographic imaging module, LED backlight imaging module, motion control module and image acquisition card (19), the image acquisition card (19) is connected with CMOS camera I (10) and CMOS camera II (5) in communication, The coaxial holographic imaging module is composed of low-power laser source (4), collimating and expanding mirror (3), CMOS camera I (10) and laser power controller (16); The LED backlight imaging module is composed of LED light source (13), collimating mirror group (14), CMOS camera II (5), low-power telecentric lens (6) and LED brightness controller (17); The motion control module is composed of motion translation stage I (1), motion translation stage II (15), reflecting mirror I (2), reflecting mirror II (11) and motion controller (18), reflecting mirror I (2) and reflecting mirror II (11) are respectively installed on motion translation stage I (1) and motion translation stage II (15), and motion translation stage I (1) and motion translation stage II (15) are electrically connected with motion controller (18); Motion controller (18), LED brightness controller (17), laser power controller (16) and image acquisition card (19) are connected with PC processor (20) in communication; When reflecting mirror I (2) and reflecting mirror II (11) are respectively located at P0 and Q0 positions, the coaxial holographic imaging module images the microelectrode (8) installed on the electrode main shaft (9); when reflecting mirror I (2) and reflecting mirror II (11) are respectively located at P1 and Q1 positions, the LED backlight imaging module images the microelectrode (8) installed on the electrode main shaft (9); PC processor (20) sends control signal to laser power controller (16), laser power controller (16) controls low-power laser source (4) to emit laser, the laser is collimated and expanded by collimating and expanding mirror (3), and is deflected by reflecting mirror I (2) on motion translation stage I (1), and then is irradiated to microelectrode (8), and then the laser continues to transmit through reflecting mirror II (11) on motion translation stage II (15) to be deflected, and enters CMOS camera I (10) to be holographic coaxial interference imaged; PC processor (20) sends control signal to LED brightness controller (17), LED brightness controller (17) controls LED light source (13) to emit LED light beam, the LED light beam is collimated by collimating mirror group (14), and is deflected by reflecting mirror II (11) on motion translation stage II (15), and then is irradiated to microelectrode (8), and then the LED light continues to transmit through reflecting mirror I (2) on motion translation stage I (1) to be deflected, and enters CMOS camera II (5) through low-power telecentric lens (6) to be LED backlight imaged.

2. The microelectrode on-line monitoring device according to claim 1, wherein Protective light window I (7) and protective light window II (12) are distributed on the same optical axis with reflecting mirror I (2) and reflecting mirror II (11).

3. The microelectrode on-line monitoring device according to claim 1, wherein LED light source (13) is connected with LED brightness controller (17) in communication, the light intensity of LED light source (13) is adjusted by LED brightness controller (17), and the wavelength of LED light source (13) is visible light band.

4. A microelectrode on-line monitoring method, characterized by, The microelectrode (8) rough positioning process includes the following steps, and the following steps are sequentially performed: The microelectrode (8) rough positioning process includes the following steps, and the following steps are sequentially performed: Step A1, control the motion controller (18) to drive the motion control module by the PC processor (20), and start the LED backlight imaging module working mode; Step A2, pre-set the microelectrode imaging image candidate positioning frame, set the length and width as half of the image size, and the candidate positioning frame coincides with the image center; Step A3, adjust the X direction position of the microelectrode (8), and the LED backlight imaging module clearly images the microelectrode (8); Step A4, obtain the position of the microelectrode (8) tip in the image by sub-pixel contour extraction on the image; Step A5, for the initial microelectrode (8), judge whether the position of the microelectrode (8) tip is in the image center, if not, repeat the precise adjustment of the electrode spindle (9) position, so that the microelectrode (8) tip position and the image center coincide, and record the coordinate value of the electrode spindle (9), and ensure that the electrode spindle (9) moves to this coordinate value in the subsequent microelectrode (8) detection process; The microelectrode (8) detection process includes the following steps, and the following steps are sequentially performed: Step B1, control the motion controller (18) to drive the motion control module by the PC processor (20), and start the coaxial holographic imaging module working mode; Step B2, collect a hologram of the microelectrode (8), and use the microelectrode (8) imaging image candidate positioning frame size in step A2 of the microelectrode (8) rough positioning process to crop the hologram size to be consistent with the candidate positioning frame size; Step B3, use a super-resolution deep learning model to perform super-resolution reconstruction on the cropped hologram in step A2 to obtain a super-resolution hologram; Step B4, use angular spectrum method to reconstruct the super-resolution hologram obtained in step B3 to obtain a reconstructed hologram; Step B5, according to the reconstructed hologram of step B4, the contour is extracted to obtain the microelectrode contour; Step B6, according to the microelectrode (8) contour determination method in steps B1 to B5, the initial electrode and the electrode after use are obtained, and the maximum contour deviation in the horizontal direction of the contour is calculated, compared with the preset deviation, and the electrode compensation amount is determined.

5. The microelectrode on-line monitoring method according to claim 4, wherein In step A3, the variance information entropy algorithm is used to determine whether the microelectrode (8) is in a clear position: wherein is the local variance of the image centered at (x j ,y j ) with a 3x3 neighborhood, μ is the average intensity of the neighborhood, and f(x j +a,y j +b) is the intensity value at the pixel (x j +a,y j +b) of the image. where P i is the probability of occurrence of each gray level, L is the total number of image gray levels 256; By discriminating H Var At the time of reaching the maximum value, the fine electrode (8) image f is clearly imaged.

6. The microelectrode on-line monitoring method according to claim 4, wherein In step B4, the hologram U: where F{} is a Fourier transform of the image, F -1 {} is an inverse Fourier transform of the image, λ is a laser wavelength 635 nm, f x , f y is a frequency domain coordinate; z is a reconstructed distance of the microelectrode 8 in the X direction.

7. The microelectrode on-line monitoring method according to claim 4, wherein Step B6 specifically includes: The profile image of the microelectrode (8) is horizontally projected to find the last end pixel row position P of the microelectrode (8) in the profile image, wherein P is P o and P u The profile image of the microelectrode (8) is vertically projected to find the leftmost column position CL and the rightmost column position CR of the microelectrode in the profile image, and between the column CL and the column CR, the horizontal section line k is set upward with a distance of d pixels, wherein d is an integer and at least 1, with the P row position being the lowermost. The profile point pairs of the initial microelectrode profile on different horizontal section lines are {I(i k ,CL),I(j k ,CR)} and the profile point pairs of the microelectrode profile after use on different horizontal section lines are {I(m k ,CL),I(n k ,CR)}; taking the P row position as the start, the profile width value sets A of the initial microelectrode on different horizontal section lines are calculated from bottom to top respectively, A = {|i k -j k |}, and the profile width value sets B of the microelectrode on different horizontal section lines after use are B = {|m k -n k |}. If |A-B| exceeds the preset deviation T, it is determined that the microelectrode wear exceeds the predetermined level, and the microelectrode (8) needs to be trimmed; meanwhile, the row coordinate n of the level section line k where |A-B| is less than the minimum preset value Tmin is found in B; and the vertical trimming compensation amount of the microelectrode (8) is determined as |P o -P u |+nd.

Images