On-line detection method and system for tool wear state in large die steel machining process

Abstract

This invention discloses an online detection method and system for tool wear condition during the machining of large mold steel, belonging to the field of cutting process monitoring technology. The detection steps of the online detection method for tool wear condition during the machining of large mold steel are as follows: S1: Collect characteristic spectra of several tool materials with different wear degrees and perform threshold calibration; S2: Initialize the detection and collect the reference spectrum of the new tool; S3: After the tool participates in machining, when the tool is in the non-cutting time stage, collect and process the X-ray fluorescence signal of the tool cutting edge area; S4: Compare the X-ray fluorescence signal processed in step S3 with the threshold calibration to determine whether it has worn through. If it has not worn through, repeat steps S3 and S4 until the coating is worn through. If it has worn through, continue to the next step; S5: Send alarm and stop signals to the CNC system. It can realize automated monitoring of the wear condition of coated cemented carbide tools without interfering with the normal machining process.

Description

Technical Field

[0001] This invention relates to the field of cutting process monitoring technology, and more specifically, to an online detection method and system for the wear condition of coated carbide cutting tools during the machining of large mold steel. Background Technology

[0002] Large mold steels (such as P20 and H13) are widely used in the manufacture of high-precision, high-load workpieces such as plastic molds, stamping dies, and die-casting molds due to their high strength, high hardness (HRC 30~60), and excellent thermal stability. However, the high hardness and low thermal conductivity (typically 20~30 W / (m·K)) of these materials significantly increase the cutting temperature and mechanical load during the cutting process, making them typical difficult-to-machine materials. Under high-speed milling conditions, the instantaneous temperature in the cutting zone of the tool can reach 800~1000°C, and the peak cutting force can exceed 800 N, resulting in the tool being subjected to severe thermo-mechanical alternating loads, and its wear and failure process is complex and has a high rate.

[0003] To improve the wear resistance and service life of cutting tools, coated cemented carbide tools are commonly used in industry. For example, wear-resistant coatings such as TiAlN, AlCrN, or TiCN (with a hardness of HV 2800-3300 and a thickness of approximately 2-10 μm) are deposited on a WC-Co substrate (hardness approximately HV 1500-1800). These composite tools can typically increase tool life by more than 30% and effectively slow down abrasive and diffusion wear. However, during prolonged cutting, the surface coating will gradually thin and eventually wear through. When the coating thickness drops to approximately 0.2 μm or partially peels off, exposing the WC-Co substrate, the tool's coefficient of friction increases, the cutting temperature may rise by approximately 100-150 °C, and the wear rate accelerates significantly. At this point, the tool is prone to adhesive wear, plastic deformation, and even chipping, causing a rapid deterioration of the workpiece surface roughness (up to 3 μm or more), and in severe cases, even leading to workpiece scrap or machine tool downtime.

[0004] Currently, most commonly used methods for monitoring tool wear in industry are indirect methods, mainly including the following categories: (1) Cutting force monitoring method: The tool wear state can be inferred by analyzing the trend of cutting force signal changes. Although wear will cause the root mean square value of cutting force to increase by about 10% to 30%, the signal is easily affected by various factors such as feed rate, cutting speed, workpiece material inhomogeneity and machine tool rigidity. The data fluctuates greatly and it is difficult to accurately identify the critical state of coating wear through.

[0005] (2) Vibration and acoustic emission monitoring method: mainly identifies tool abnormalities by analyzing high-frequency vibration or acoustic emission signals generated during the processing. It is more sensitive to sudden failures (such as chipping), but it does not respond significantly to the gradual process of coating wear to the exposure of the substrate. In addition, the signal-to-noise ratio is low in strong noise environment, which can easily cause false alarms or missed alarms.

[0006] (3) Machine vision inspection method: The tool surface is directly observed by an industrial camera to assess the wear condition. Although it can intuitively reflect the wear morphology, this method requires a complex lighting and field calibration system and is easily blocked by cutting fluid, oil mist and chips. The detection error in the field environment often exceeds 20%, making it difficult to achieve stable online monitoring in actual processing.

[0007] In summary, existing tool wear detection methods generally suffer from problems such as strong indirectness, poor real-time performance, and susceptibility to interference. They are unable to directly reflect the true changes in the chemical and physical state of the tool surface, and in particular, they cannot achieve direct and accurate online identification and early warning at the critical stage of "coating wear through and substrate exposure," which leads to a sharp deterioration in tool performance.

[0008] Therefore, there is an urgent need for an online monitoring method that can directly capture fundamental changes in the material composition of the tool surface, identify substrate exposure in real time, and has strong anti-interference capabilities, in order to improve the stability, safety, and intelligence level of the machining process for large mold steel. Summary of the Invention

[0009] To address the problems existing in the prior art, the purpose of this invention is to provide an online detection method and system for the wear condition of coated cemented carbide tools during the machining of large mold steel. It can achieve automated monitoring of the wear condition of coated cemented carbide tools without interfering with the normal machining process, and issue an alarm signal in the early stage when the coating is worn through to expose the substrate, thereby effectively preventing workpiece surface damage and equipment accidents caused by tool failure.

[0010] To solve the above problems, the present invention adopts the following technical solution.

[0011] A method for online detection of tool wear during the machining of large mold steel, the detection steps are as follows: S1: Collect feature maps of several tool materials with different wear levels and perform threshold calibration; S2: Initialize the detection and acquire the reference spectrum of the new tool; S3: After the tool participates in machining, when the tool is in the non-cutting time stage, the X-ray fluorescence signal of the tool cutting edge area is collected and processed; S4: Compare the X-ray fluorescence signal processed in step S3 with the threshold calibration to determine whether it has been worn through. If it has not been worn through, repeat steps S3 and S4 until the coating is worn through. If it is worn through, proceed to the next step. S5: Send alarm and stop signals to the CNC system.

[0012] Furthermore, in step S1, the cutting tool is a cemented carbide indexable insert with a wear-resistant coating of TiAlN, AlCrN, or TiCN, and its base material is mainly composed of tungsten carbide-cobalt.

[0013] Furthermore, the step of determining the threshold in step S1 is as follows: A1: Select several coated carbide inserts of the same model, including new inserts and insert samples with different wear levels; A2: Activate the X-ray fluorescence module to detect the blade sample in step A1, obtain the fluorescence spectrum signal on the blade surface, process the fluorescence spectrum data and extract the characteristic peak intensities of coating elements and matrix elements; A3: Statistical analysis of the characteristic peak intensity of tool samples under different wear conditions is performed to determine the characteristic signal of coating wear-through, and the threshold for determining tool wear condition is determined accordingly.

[0014] Furthermore, in step A3, the specific details of determining the characteristics and threshold for coating wear are as follows: extract the characteristic peak intensity of each characteristic element, establish the correspondence between the tool wear state and the changes in the characteristic element signal, and identify the turning point where the matrix element and / or coating element signal shows a significant enhancement relative to the new tool state; use the turning point where the signal shows a significant enhancement as a characteristic marker of coating wear; and use the corresponding signal intensity critical point as the threshold for determining coating wear.

[0015] Furthermore, the wear condition can be the coating thickness.

[0016] Furthermore, the signal intensity is the ratio of the characteristic peak intensity of the coating element to that of the matrix element, the characteristic peak intensity of the coating element, or the characteristic peak intensity of the matrix element.

[0017] Furthermore, when the signal intensity is the characteristic peak intensity of a single element, the coating element and the matrix element can be selected based on the characteristic peak intensity that changes the most with the stage. When the signal intensity is the ratio of the characteristic peak intensity of the coating element to that of the matrix element, the ratio of the characteristic peak intensity of the coating element to that of the matrix element with the largest change in intensity with the stage is selected.

[0018] Furthermore, when the signal intensity is the characteristic peak intensity of a single element, the element is preferably a matrix element.

[0019] Furthermore, in step S3, the method for processing the X-ray fluorescence signal specifically involves converting the X-ray fluorescence data into spectral data and then normalizing the spectral data.

[0020] Furthermore, the normalization process can be expressed as the ratio of the characteristic peak intensities of the matrix element to those of the coating element, or as the relative percentage of the characteristic peak intensities of each element to the total intensity, thereby obtaining stable relative intensity or relative content parameters.

[0021] Furthermore, in step S4, the calculated characteristic peak intensity is compared with the judgment threshold determined in step S1. The specific determination of whether wear has occurred is as follows: When the threshold When the characteristic peak intensity is a matrix element or coating element, the currently detected characteristic peak intensity is greater than the threshold. If the coating wears through, it is determined that the tool has not worn through the coating; otherwise, it is determined that the tool has not worn through the coating. When the threshold When the ratio of the characteristic peak intensities of coating elements to matrix elements is used, if the currently detected ratio is less than the threshold... If the coating wears through, the tool is considered to have been worn through; otherwise, the tool is considered to have not had its coating worn through.

[0022] Furthermore, when the threshold When the ratio of the characteristic peak intensity of the coating element to that of the matrix element is used, a warning threshold can also be defined. , with threshold Together they form the wear determination range When the ratio is less than the warning threshold However, it is greater than the threshold. When the ratio is less than a threshold, it is determined that the tool is in an accelerated wear stage, and an alarm is issued indicating coating instability requiring tool replacement; If the coating of the tool is worn through, it is determined that the substrate is exposed; otherwise, it is determined that the coating of the tool has not been worn through.

[0023] Furthermore, the warning threshold It should be greater than the threshold. .

[0024] Furthermore, step S4 also includes a repeated detection mechanism. When the detection indicates a wear-through state, to ensure the accuracy of the detection results, the wear state is only confirmed when two or more consecutive detection results exceed a threshold.

[0025] The present invention also provides a system for online detection of tool wear condition during the machining of large mold steel, the system comprising the following modules: X-ray fluorescence detection module: used to acquire elemental fluorescence signals on the surface of the cutting tool, so as to obtain X-ray photons with characteristic energies corresponding to different elements; Information acquisition and analysis module: After receiving and processing fluorescence signals, it generates an energy spectrum, then automatically extracts the peak intensity of characteristic elements and compares it with a preset threshold, and transmits the detection results to the machine tool control system. Communication interface and machine tool control: used to realize the timing control and wear signal feedback of the X-ray fluorescence detection module; when the tool wear-through warning is received from the wear information acquisition and analysis module, the corresponding alarm or stop command is triggered.

[0026] Furthermore, the X-ray fluorescence detection module is arranged in an embedded manner within the blade or an integrated manner with the blade handle.

[0027] Furthermore, the X-ray fluorescence detection module (XRF detection module) includes a miniature X-ray tube and an energy dispersive detector; When the cutting tool is a coated carbide indexable insert, a detection cavity is pre-set in the tool body. A high-transmittance and high-temperature resistant X-ray window material is set at the front end of the cavity. The window is aligned with the area near the cutting edge of the insert along the radial direction of the tool. The miniature X-ray tube and the energy dispersive detector are respectively fixed to the transmitting end and receiving end in the detection cavity. When the tool is a modular tool, an independent mounting chamber is opened in the tool holder. The miniature X-ray tube, energy dispersive detector and information acquisition and analysis module are integrated and installed in the mounting chamber. The mounting chamber has a metal waveguide channel or reflector structure on the side facing the tool body, which is used to guide the X-ray excitation beam to the detection window area at the end of the tool.

[0028] Furthermore, the XRF detection module is preferably embedded within the tool body. Its advantages include a detection area close to the actual wear area, resulting in higher signal response sensitivity, while avoiding the calibration complexity during tool changes. This structure is particularly suitable for machining scenarios such as face milling and end milling of large mold steel, enabling rapid qualitative identification and wear alarm of the tool coating wear state within the detection window allowed by the machine tool control system.

[0029] Compared with the prior art, the advantages of this invention are: This solution can automatically monitor the wear condition of coated carbide tools without interfering with the normal machining process, and issue an alarm signal when the coating is worn through to the exposed substrate, thereby effectively preventing workpiece surface damage and equipment accidents caused by tool failure. Attached Figure Description

[0030] Figure 1 This is a flowchart of the detection method in Example 1; Figure 2 Here is a flowchart of the threshold calibration process for Example 1; Figure 3 This is a schematic diagram of the system composition in Example 2. Detailed Implementation

[0031] Example 1:

[0032] An online detection method for tool wear during the machining of large mold steel (e.g.) Figures 1-2 As shown below: Step 1: Threshold Calibration Before the system is put into use, the characteristic spectrum of the tool material is first acquired and the threshold is calibrated (e.g., Figure 2 (As shown). Several coated carbide cutting tools of the same model were selected, including unused new tools and tool samples with different degrees of wear. X-ray fluorescence spectra were acquired under the same detection conditions, including X-ray excitation voltage, excitation current, sampling time, and detection distance. These conditions were designed to effectively excite the characteristic fluorescence signals of coating and matrix elements, while ensuring sufficient signal-to-noise ratio and stability to guarantee comparability of test results between different tool samples.

[0033] In some embodiments, the threshold calibration can be performed under conditions close to the actual machining environment, that is, in a machine tool or simulated machining device, under the same or equivalent installation method and detection parameters as the online detection stage, the X-ray fluorescence spectrum signal of the tool is collected.

[0034] The acquired fluorescence spectral data were processed as follows: To eliminate the influence of continuous background radiation and scattering signals, background subtraction and peak identification were first performed on the spectral signals to extract the characteristic peaks of the tool coating (such as Ti, Al, or Cr) and the matrix (such as W or Co). Subsequently, the characteristic peak intensities of each peak were calculated, and statistical analysis was performed on the characteristic peak intensities of tool samples under different wear conditions to obtain the changing trends of the signals of each characteristic element during tool wear.

[0035] In some embodiments, the intensity of a characteristic peak can be characterized by the peak height or the peak area integral.

[0036] As the machining process progresses, the tool coating gradually wears down, and the fluorescence signal intensity of the coating's characteristic elements gradually weakens, while the fluorescence signal intensity of the matrix's characteristic elements gradually strengthens. By comparing and analyzing the characteristic peak intensities of tool samples with different wear levels, a correspondence between the tool wear state and the changes in characteristic element signals can be established, and the turning point where the matrix element or coating element signals show a significant enhancement relative to the new tool state can be identified.

[0037] The inflection point where the signal is significantly enhanced is used as a characteristic marker that the coating is close to wear through, and the characteristic peak intensity or characteristic peak intensity ratio corresponding to the inflection point is used as the judgment threshold or preset range for coating wear through, which is used to determine whether the tool coating has worn through during subsequent online detection.

[0038] The specific method for determining the threshold is as follows: 1. When selecting the characteristic peak intensity as the judgment threshold, the characteristic peak intensity of the matrix element or coating element (preferably the matrix element) with the largest change in intensity with the stage is used as the judgment criterion. Subsequently, a characteristic peak intensity-wear process curve of the matrix element or coating element is established and analyzed. Based on this, the growth trend is quantitatively characterized by calculating the signal increment, relative growth rate, or first derivative change rate of adjacent sampling points, thereby determining whether the intensity value has entered a rapid growth stage. The specific judgment criteria are detailed below: (1) When the signal increment between adjacent acquisition points is used as the criterion, the characteristic peak intensity of the matrix element corresponding to the maximum increment is used as the threshold. .

[0039] (2) When the relative growth rate is used as the criterion, the characteristic peak intensity of the matrix element corresponding to the maximum value of the relative growth rate is used as the threshold. .

[0040] (3) When the rate of change of the first derivative is used as the criterion, the characteristic peak intensity of the matrix element corresponding to the local maximum of the first derivative is used as the threshold. .

[0041] In some embodiments, the change in the sign of the second derivative of the curve or its curvature can also be used as an auxiliary method to improve the stability and accuracy of inflection point identification. The auxiliary method described here is existing technology and will not be described in detail.

[0042] 2. When the characteristic peak intensity ratio is selected as the judgment threshold, the threshold can be the ratio of the characteristic peak intensity of the coating element to that of the matrix element. The ratio of the characteristic peak intensity of the coating element to that of the matrix element with the largest change with the stage is used as the judgment basis.

[0043] Subsequently, the evolution curve of the ratio R of the characteristic peak intensities of the coating elements to those of the matrix elements as a function of the coating thickness t was established; its definition is shown below: Where I represents the characteristic peak intensity of the corresponding element; t is the coating thickness.

[0044] The evolution curve was then analyzed: The R-value corresponding to the minimum of the first derivative of the curve (i.e., the ratio of the characteristic peak intensities of the coating element to the matrix element corresponding to the incremental minimum) is defined as the safety lower limit. ;Will The R-value corresponding to the stage where the absolute value of the first derivative of the curve increases rapidly and the sign of the second derivative changes abruptly (i.e., the curve reaches an inflection point) is defined as the warning threshold. Therefore, the wear judgment range of the cutting tool can be determined as follows: It is important to note that the validity of this interval is based on... > This premise.

[0045] Step 2: Initialization Detection Phase Before the cutting tool is put into operation, the system activates the XRF detection module to perform an initial scan of the cutting edge surface of the new tool, obtain the complete spectral distribution of the coating, and record the peak intensity of the coating elements as a "reference spectrum". This spectrum is used for comparison and correction in subsequent inspections to ensure the stability and consistency of the inspection results.

[0046] Step 3: Periodic detection trigger During machining, the machine tool control system automatically triggers detection commands according to a preset detection interval. This detection interval can be set based on cumulative cutting time, cumulative cutting length, or the number of machining cycles. The cumulative cutting time or cutting length can be calculated or statistically obtained by the machine tool control system based on tool feed rate, spindle speed, and machining trajectory information. When the cumulative machining parameters reach the preset detection interval, the machine tool control system automatically issues a detection trigger signal. The detection timing is preferably set during the non-cutting phase of the machine tool, i.e., during the tool's movement away from the workpiece or during tool feed / retraction.

[0047] When in the non-cutting stage, the X-ray fluorescence detection module performs short-term excitation and simultaneously acquires the X-ray fluorescence signal of the tool cutting edge area. The excitation time is usually 2-5 seconds to obtain the elemental fluorescence information of the current tool surface.

[0048] Step 4: Spectral Acquisition and Feature Recognition After the collected X-ray fluorescence signal is converted into spectral data by the energy dispersion analysis circuit, the spectral data is first processed by background subtraction and peak identification, and the characteristic peaks corresponding to the coating elements and matrix elements are extracted.

[0049] After obtaining the characteristic peaks of each characteristic element, the intensity of the characteristic peak is calculated, and based on the calibration results established in step one, the relationship between the intensity of the characteristic peak and the content of the corresponding element is mapped to obtain the relative content information of each element.

[0050] In some embodiments, to reduce the impact of changes in detection angle, fluctuations in detection distance, or environmental factors during the detection process, the system normalizes the intensity of characteristic peaks. The normalization can be expressed as a ratio of the characteristic peak intensities of matrix elements to coating elements, or as a relative percentage of the characteristic peak intensity of each element to the total intensity, thereby obtaining stable relative intensity or relative content parameters.

[0051] Step 5: Wear Condition Determination The current detection result is compared in real time with the judgment threshold obtained in step one. The judgment parameters include the characteristic peak intensity of matrix characteristic elements (such as W, Co) and the ratio of the characteristic peak intensity of coating elements to that of matrix elements. There are two judgment methods, as detailed below: (1) When the characteristic peak intensity of a certain matrix element is selected as the threshold, the characteristic peak intensity of the currently detected matrix element is calculated. ; and compare it with the threshold The comparison determines whether the tool coating has worn through; the details are as follows: when At that time, it was determined that the coating of the tool was intact and not worn through; when If the tool is determined to be worn through, an alarm or stop signal will be immediately sent to the CNC control system of the machine tool.

[0052] (2) When the characteristic peak intensity of a certain coating element is selected as the threshold, the characteristic peak intensity of the currently detected coating element is calculated. ; and compare it with the threshold The comparison determines whether the tool coating has worn through; the details are as follows: when At that time, it was determined that the coating of the tool was intact and not worn through; when If the tool is determined to be worn through, an alarm or stop signal will be immediately sent to the CNC control system of the machine tool.

[0053] (3) When the ratio of the characteristic peak intensity of a coating element to that of the matrix element is selected as the threshold, the ratio between the two characteristic peaks is calculated. ; when At that time, it was determined that the coating of the tool was intact and not worn through; when When the tool is determined to be in the accelerated wear stage, a pre-alarm is sent to the CNC control system to remind that the coating is beginning to become unstable and that preparations should be made to change the tool. when If the coating of the cutting tool is worn through and the substrate is exposed, an alarm or stop signal will be immediately sent to the CNC control system.

[0054] In some embodiments, to improve the reliability of the judgment results, the system may also set a repeated detection confirmation mechanism. When the detection result exceeds the judgment threshold or exceeds the ratio range for the first time, the detection interval is shortened, and the detection result is obtained again in at least one or more subsequent detections; only when multiple consecutive detection results meet the condition of exceeding the threshold or exceeding the range is it confirmed that the tool coating has been worn through; otherwise, the original detection interval is restored and monitoring continues.

[0055] Step Six: Alarm and Tool Stop Response Once the tool coating is confirmed to be worn through, an alarm or stop signal is immediately sent to the machine tool's CNC control system via the machine tool communication interface, enabling audible and visual alerts, tool stop, or automatic tool change. This function can also be linked with the machine tool management module to ensure the safety and stability of the machining process.

[0056] Example 2:

[0057] like Figure 3 As shown, a system for online detection of tool wear during the machining of large mold steel includes the following modules: The X-ray fluorescence detection module (XRF detection module) mainly consists of a miniature X-ray tube and an energy-dispersive detector. This module enables real-time elemental analysis of the cutting tool surface using the miniature X-ray tube without damaging the tool or affecting the machining process. By irradiating the tool surface with X-rays, surface atoms are excited to produce characteristic fluorescence signals; different elements correspond to X-ray photons of characteristic energies. This module can collect the fluorescence signals and output them to subsequent analysis modules.

[0058] Information Acquisition and Analysis Module: After the signal acquisition circuit receives the fluorescence signal from the X-ray fluorescence detection module, the energy spectrum analysis module performs energy resolution, signal amplification, and digital processing on the fluorescence signal output by the detector. The energy spectrum analysis module can generate a real-time fluorescence energy spectrum of the tool surface and automatically extract the peak intensity of characteristic elements, comparing it with preset thresholds. By calculating the relative intensity changes of these characteristic peaks, the wear degree of the coating can be quantified. When the system triggers a preset threshold alarm, it transmits the alarm or tool stop response to the automatic CNC control system, thereby alerting the operator that the tool has reached a critical failure state, or automatically sending a tool stop command to the machine tool control system.

[0059] Communication Interface and Machine Tool Control: The energy spectrum analysis module communicates with the machine tool CNC control system to realize the timing control of XRF detection and wear signal feedback; when it receives the tool wear warning from the information acquisition and analysis module, it triggers the corresponding alarm or stop command.

[0060] When the tool is in a non-cutting phase of the machine tool (e.g., during tool detachment from the workpiece or tool feed / retraction), the system automatically activates the XRF detection module to quickly scan the current tool surface, avoiding machining interference. The detection results are processed and fed back to the CNC system to determine whether to continue machining, execute tool change commands, or record tool life data.

[0061] Example 3:

[0062] For milling cutters using indexable inserts: the X-ray fluorescence detection module includes a miniature X-ray tube and an energy-dispersive detector. The miniature X-ray tube and energy-dispersive detector can be embedded in the cutter body near the insert mounting position. A detection cavity corresponding to the miniature X-ray tube is pre-fabricated inside the cutter body. A high-transmittance, high-temperature-resistant X-ray window is provided at the front end of the cavity, and this window is aligned radially with the area near the cutting edge of the insert.

[0063] In this system, a miniature X-ray tube serves as the excitation source, positioned on the side of the detection chamber facing the blade, to emit an X-ray excitation beam onto the blade surface. The X-ray excitation beam passes through an X-ray window and irradiates the blade. An energy-dispersive detector is positioned relative to the blade (preferably around the X-ray excitation beam or at the non-emitting end of the miniature X-ray tube) to receive the X-ray fluorescence signal generated on the blade surface under excitation, thus forming the emitting and receiving ends respectively.

[0064] In some embodiments, the transmitter and receiver are arranged opposite each other or at a certain angle along both sides of the detection area to balance excitation efficiency and signal reception efficiency. The miniature X-ray tube and the energy-dispersive detector are fixed at corresponding positions within the detection cavity, and the detection area is defined by a collimation structure used to limit the X-ray divergence angle. This arrangement allows for short-term scanning of the cutting tool during non-cutting stages (including tool rotation gaps or when the tool leaves the workpiece surface), enabling periodic detection of the tool coating wear condition without requiring additional changes to the tool structure or machining path.

[0065] Example 4:

[0066] For modular tooling systems: the X-ray fluorescence detection module includes a miniature X-ray tube and an energy-dispersive detector. The miniature X-ray tube, energy-dispersive detector, and information acquisition and analysis module are integrated into a single package and installed inside the tool holder. The miniature X-ray tube generates the X-ray excitation beam, constituting the emitting end; the energy-dispersive detector receives the characteristic X-ray signals generated by the tool surface, constituting the receiving end. To achieve effective X-ray transmission, a metal waveguide channel or reflector structure can be used to guide the X-ray excitation beam to the detection window area at the tool tip. A coaxial or near-coaxial arrangement ensures that the excitation path and signal receiving path are spatially nearly coincident, thereby improving the efficiency of signal recovery.

Claims

1. A method for online detection of tool wear condition during the machining of large mold steel, characterized in that: The detection steps are as follows: S1: Collect feature maps of several tool materials with different wear levels and perform threshold calibration; S2: Initialize the detection and acquire the reference spectrum of the new tool; S3: After the tool participates in machining, when the tool is in the non-cutting time stage, the X-ray fluorescence signal of the tool cutting edge area is collected and processed; S4: Compare the X-ray fluorescence signal processed in step S3 with the threshold calibration to determine whether it has been worn through. If it has not been worn through, repeat steps S3 and S4 until the coating is worn through. If it is worn through, proceed to the next step. S5: Send alarm and stop signals to the CNC system.

2. The method for online detection of tool wear condition during the machining of large mold steel according to claim 1, characterized in that: In step S1, the cutting tool is a cemented carbide indexable insert with a wear-resistant coating of TiAlN, AlCrN, or TiCN, and its base material is mainly composed of tungsten carbide-cobalt.

3. The method for online detection of tool wear condition during the machining of large mold steel according to claim 1, characterized in that: The steps for determining the threshold in step S1 are as follows: A1: Select several coated carbide inserts of the same model, including new inserts and insert samples with different wear levels; A2: Detect the blade sample from step A1, obtain the fluorescence spectrum signal on the blade surface, process the fluorescence spectrum data and extract the characteristic peak intensities of coating elements and matrix elements; A3: Statistical analysis of the characteristic peak intensity of tool samples under different wear conditions is performed to determine the characteristic signal of coating wear-through, and the threshold for determining tool wear condition is determined accordingly.

4. The method for online detection of tool wear condition during the machining of large mold steel according to claim 3, characterized in that: In step A3, the specific details of determining the characteristics and threshold for coating wear-through are as follows: extract the characteristic peak intensity of each characteristic element; establish the correspondence between the tool wear state and the changes in the characteristic element signal, and identify the turning point where the matrix element and / or coating element signal shows a significant enhancement relative to the new tool state; use the turning point where the signal shows a significant enhancement as a characteristic marker that the coating is close to wear-through; and use the corresponding signal intensity critical point as the threshold for determining coating wear-through.

5. The method for online detection of tool wear condition during the machining of large mold steel according to claim 4, characterized in that: The signal strength is the ratio of the characteristic peak intensity of the coating element to that of the substrate element, the characteristic peak intensity of the coating element, or the characteristic peak intensity of the substrate element; the wear state is the coating thickness.

6. The method for online detection of tool wear condition during the machining of large mold steel according to claim 1, characterized in that: In step S3, the method for processing the X-ray fluorescence signal is as follows: after converting the X-ray fluorescence data into spectral data, the spectral data is normalized. Step S4 also includes a repeated detection mechanism, where the wear state is confirmed only when the detection result exceeds the threshold for two or more consecutive detection results.

7. The method for online detection of tool wear condition during the machining of large mold steel according to claim 5, characterized in that: In step S4, the calculated characteristic peak intensity is compared with the judgment threshold determined in step S1. The specific determination of whether the wear has penetrated is as follows: When the threshold When the intensity of the characteristic peak of the matrix element is greater than the threshold, the intensity of the currently detected characteristic peak is greater than the threshold. If the coating wears through, it is determined that the tool has not worn through the coating; otherwise, it is determined that the tool has not worn through the coating. When the threshold When the ratio of the characteristic peak intensity of the coating element to that of the matrix element, or the characteristic peak intensity of the coating element, is less than the threshold, the currently detected ratio is less than the threshold value. If the coating wears through, the tool is considered to have been worn through; otherwise, the tool is considered to have not had its coating worn through.

8. The method for online detection of tool wear condition during the machining of large mold steel according to claim 7, characterized in that: When the threshold When the ratio of the characteristic peak intensity of the coating element to that of the matrix element is used, a warning threshold can also be defined. , with threshold Together they form the wear determination range ; When the ratio is less than the warning threshold However, it is greater than the threshold. When the tool is in the accelerated wear stage, an alarm is issued indicating that the coating is unstable and the tool needs to be replaced. When the ratio is less than the threshold If the coating of the tool is worn through, it is determined that the substrate is exposed; otherwise, it is determined that the coating of the tool has not been worn through.

9. A system for online detection of tool wear condition during the machining of large mold steel as described in any one of 1-8, characterized in that: The system includes the following modules: X-ray fluorescence detection module: used to acquire elemental fluorescence signals on the surface of the cutting tool, so as to obtain X-ray photons with characteristic energies corresponding to different elements; Information acquisition and analysis module: After receiving and processing fluorescence signals, it generates an energy spectrum, then automatically extracts the peak intensity of characteristic elements and compares it with a preset threshold, and transmits the detection results to the machine tool control system. Communication interface and machine tool control: used to realize the timing control and wear signal feedback of the X-ray fluorescence detection module; when the tool wear warning is received from the information acquisition and analysis module, the corresponding alarm or stop command is triggered.

10. The system for online detection of tool wear condition during the machining of large mold steel according to claim 8, characterized in that: The X-ray fluorescence detection module is arranged either embedded in the blade or integrated within the blade handle.

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