Cutter state analysis method and device, electronic equipment and storage medium

Abstract

The invention provides a tool state analysis method and device, electronic equipment and a storage medium, and relates to the technical field of numerical control machining. The method comprises the following steps: firstly, acquiring a cutting vibration signal formed by performing vibration acquisition operation on a target tool in a machining process; secondly, performing image drawing operation based on the cutting vibration signal to form a polar coordinate image; then, performing feature determination operation on the polar coordinate image to form feature identification parameters; and finally, based on the feature identification parameters, determining cutter state data corresponding to the target cutter. On the basis of the content, the problem that in the prior art, the reliability of cutter state analysis is relatively low can be solved.

Description

Technical Field

[0001] The present application relates to the field of CNC machining technology, and in particular to a tool state analysis method and device, electronic equipment, and storage medium. Background Art

[0002] In metal cutting, cutting tools gradually wear out and even break or break over time. Due to direct contact with the workpiece, excessive wear and breakage of the cutting tool will reduce the dimensional accuracy and surface quality of the part, and may even cause the part to be scrapped (for example, a broken blade can cause burns in the part). Therefore, during the machining process, it is necessary to constantly monitor the condition of the cutting tool and replace it promptly when it is worn to a certain extent or breaks. Currently, in the CNC machining of aircraft structural parts, the condition of the cutting tool is mainly judged by the operator through experience. This is greatly influenced by human factors, and it is difficult to respond to some abnormal situations in a timely manner. Therefore, part quality problems caused by excessive wear / breakage of the cutting tool often occur. In other words, the reliability of tool condition analysis in the existing technology is relatively low. Summary of the Invention

[0003] In view of this, the purpose of the present application is to provide a tool state analysis method and device, an electronic device and a storage medium to improve the problem of relatively low reliability of tool state analysis in the prior art.

[0004] To achieve the above objectives, this application adopts the following technical solutions: A tool state analysis method, comprising: Acquire a cutting vibration signal generated by performing a vibration acquisition operation on a target tool during machining; Performing an image rendering operation based on the cutting vibration signal to form a polar coordinate image; performing a feature determination operation on the polar coordinate image to form feature identification parameters, wherein the image rendering operation includes correcting an amount of sampled data within a period in the polar coordinate transformation, and the corrected amount of sampled data is used to determine a polar angle in the polar coordinate image; and / or the feature determination operation includes correcting an area corresponding to each tooth of the target tool, and the corrected area is used to determine the feature identification parameters; Based on the characteristic identification parameters, tool status data corresponding to the target tool is determined, wherein the tool status data is used to indicate whether the target tool is damaged.

[0005] In a preferred embodiment of the present application, in the above-mentioned tool state analysis method, the step of performing an image drawing operation based on the cutting vibration signal to form a polar coordinate image includes: Determining a sampling frequency of the cutting vibration signal and determining a spindle speed corresponding to the target tool, and determining an initial sampling data volume based on the sampling frequency and the spindle speed, wherein the initial sampling data volume and the sampling frequency have a positive correlation, and the initial sampling data volume and the spindle speed have a negative correlation; Based on a pre-configured image transformation correction coefficient, the initial sampling data volume is corrected to form a corrected sampling data volume; For each data point in the cutting vibration signal, determining the polar angle corresponding to the data point based on the corrected sampling data amount, and determining the vibration amplitude corresponding to the data point; An image drawing operation is performed based on the polar angle and vibration amplitude corresponding to each data point in the cutting vibration signal to form a polar coordinate image.

[0006] In a preferred embodiment of the present application, in the above-mentioned tool state analysis method, the corresponding relationship between the sampling frequency, the spindle speed, the image transformation correction coefficient and the corrected sampling data volume is represented by the following formula: ; Wherein, N is the amount of sampled data after correction, a is the image transformation correction coefficient, and f s is the sampling frequency, and n is the spindle speed.

[0007] In a preferred embodiment of the present application, in the above-mentioned tool state analysis method, the step of performing a feature determination operation on the polar coordinate image to form feature identification parameters includes: Obtaining the number of teeth corresponding to the target tool; determining a distribution area of ​​each data point in the polar coordinate image based on the number of the blade teeth; respectively determining the area corresponding to each of the data point distribution areas; Determining the area of ​​the correction area corresponding to each of the cutter teeth based on the area corresponding to each of the data point distribution areas and a pre-configured area correction coefficient; A feature identification parameter is determined based on the area of ​​the correction region corresponding to each of the cutting teeth.

[0008] In a preferred embodiment of the present application, in the above-mentioned tool state analysis method, the step of determining the distribution area of ​​each data point in the polar coordinate image based on the number of the tool teeth includes: Determining the number of data point distribution areas in the polar coordinate image based on the number of the blade teeth and a pre-configured image transformation correction coefficient, wherein the image transformation correction coefficient is equal to the area correction coefficient and is also used to correct the amount of sampled data within a period in the polar coordinate transformation during the image drawing operation, and there is a positive correlation between the number of the blade teeth and the image transformation correction coefficient and the number of data point distribution areas in the polar coordinate image; Each data point distribution area in the polar coordinate image is determined based on the number of data point distribution areas in the polar coordinate image.

[0009] In a preferred embodiment of the present application, in the above-mentioned tool state analysis method, the step of determining the area of ​​the correction area corresponding to each of the cutting teeth based on the area corresponding to each of the data point distribution areas and the pre-configured area correction coefficient includes: Determine a data point distribution region with a minimum area value among the data point distribution regions, and determine the data point distribution region as the first data point distribution region in the target sequence; Starting from the first data point distribution area, traverse the polar coordinate image in a clockwise direction, and based on the order of traversal of each other data point distribution area, determine the arrangement relationship of each other data point distribution area in the target sequence; According to the arrangement relationship of the data point distribution areas in the target sequence, the pre-configured area correction coefficient and the pre-determined averaging calculation formula, the area corresponding to each data point distribution area is processed to obtain the corrected area corresponding to each tooth.

[0010] In a preferred embodiment of the present application, in the above-mentioned tool state analysis method, the averaging calculation formula includes: ; Among them, s_m j is the area of ​​the correction region corresponding to the jth tooth, a is the area correction coefficient, size j It represents the area corresponding to the distribution area of ​​the jth data point, and z0 is the number of teeth.

[0011] In a preferred embodiment of the present application, in the above-mentioned tool state analysis method, the step of determining the characteristic identification parameter based on the area of ​​the correction region corresponding to each of the cutting teeth includes: In the correction region area corresponding to each of the cutter teeth, a first correction region area with a minimum value and a second correction region area with a maximum value are determined; A ratio between the area of ​​the first correction region and the area of ​​the second correction region is determined, and a feature identification parameter is determined based on the ratio, wherein the feature identification parameter and the ratio have a positive correlation.

[0012] In a preferred embodiment of the present application, in the above-mentioned tool state analysis method, the step of determining the tool state data corresponding to the target tool based on the feature identification parameters includes: Comparing the characteristic identification parameter with a pre-configured characteristic identification threshold; If the characteristic identification parameter is less than the characteristic identification threshold, determining the tool status data corresponding to the target tool as being damaged; If the feature identification parameter is not less than the feature identification threshold, the tool status data corresponding to the target tool is determined to be not damaged.

[0013] The present application also provides a tool state analysis device, comprising: A signal acquisition module is used to acquire a cutting vibration signal generated by performing a vibration acquisition operation on a target tool during machining; A polar coordinate image drawing module, configured to perform an image drawing operation based on the cutting vibration signal to form a polar coordinate image; an identification parameter determination module, configured to perform a feature determination operation on the polar coordinate image to form feature identification parameters, wherein the image rendering operation includes correcting an amount of sampled data within a period in the polar coordinate transformation, the corrected amount of sampled data being used to determine a polar angle in the polar coordinate image, and / or the feature determination operation includes correcting an area corresponding to each tooth of the target tool, the corrected area being used to determine the feature identification parameters; The tool state determination module is used to determine the tool state data corresponding to the target tool based on the characteristic identification parameters, wherein the tool state data is used to indicate whether the target tool is damaged.

[0014] Based on the above, the present application further provides an electronic device, including: memory for storing computer programs; The processor connected to the memory is used to execute the computer program stored in the memory to implement the above-mentioned tool state analysis method.

[0015] On the basis of the above, the present application further provides a computer-readable storage medium, in which a computer program is stored. When the computer program is run, each step of the above-mentioned tool state analysis method is executed.

[0016] The tool state analysis method and apparatus, electronic device, and storage medium provided by the present application first obtain a cutting vibration signal generated by performing a vibration acquisition operation on a target tool during machining; secondly, perform an image rendering operation based on the cutting vibration signal to form a polar coordinate image; then, perform a feature determination operation on the polar coordinate image to form feature identification parameters; and finally, determine the tool state data corresponding to the target tool based on the feature identification parameters. Based on the above content, on the one hand, because the tool state data can be determined by analyzing the cutting vibration signal, it can have higher objectivity and higher reliability than conventional technical solutions based on manual detection, and can also improve the efficiency of analysis or detection. On the other hand, because the image rendering operation includes correcting the amount of sampled data within a period in the polar coordinate transformation, and / or the feature determination operation includes correcting the area corresponding to each tooth of the target tool, the correction of the sampled data amount can reduce the interference caused by signal drift to a certain extent, enhance the feature difference caused by tool breakage, thereby improving the accuracy of analysis. In addition, the correction of the area can also improve the influence of signal fluctuation on recognition to a certain extent. Therefore, the problem of relatively low reliability of tool state analysis in the prior art can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings.

[0018] Figure 1 This is a structural block diagram of an electronic device provided in an embodiment of the present application.

[0019] Figure 2 A flow chart of the tool status analysis method provided in an embodiment of the present application.

[0020] Figure 3 This is a polar coordinate image of the cutting vibration signal of the 4-tooth tool provided in an embodiment of the present application.

[0021] Figure 4 This is a polar coordinate image of the cutting vibration signal of the 2-tooth tool provided in an embodiment of the present application.

[0022] Figure 5 A schematic diagram comparing polar coordinate images with and without correction provided in an embodiment of the present application.

[0023] Figure 6 A schematic diagram showing the comparison of characteristic identification parameters for determining whether correction is required or not provided in an embodiment of the present application.

[0024] Figure 7 A block diagram of a tool status analysis device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0025] To make the objectives, technical solutions, and advantages of the embodiments of the present application more clear, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Generally, the components of the embodiments of the present application described and shown in the drawings herein can be arranged and designed in various different configurations.

[0026] Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the present application for protection, but merely represents selected embodiments of the present application. All other embodiments obtained by persons of ordinary skill in the art based on the embodiments in the present application without creative work are within the scope of protection of the present application.

[0027] like Figure 1 As shown, an embodiment of the present application provides an electronic device, wherein the electronic device may include a memory, a processor, and a tool state analysis device.

[0028] Specifically, the memory and the processor are electrically connected, directly or indirectly, to enable data transmission or interaction. For example, the memory and the processor may be electrically connected via one or more communication buses or signal lines. The tool state analysis device includes at least one software function module stored in the memory in the form of software or firmware. The processor is configured to execute an executable computer program stored in the memory, such as the software function module and computer program included in the tool state analysis device, to implement the tool state analysis method provided in the embodiments of the present application.

[0029] Optionally, the memory may be, but is not limited to, random access memory (RAM), read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), etc.

[0030] Furthermore, the processor may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), a system on chip (SoC), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0031] I understand. Figure 1 The structure shown is only for illustration, and the electronic device may also include Figure 1 More or fewer components than shown, or with Figure 1 The different configurations shown, for example, may further include a communication unit for exchanging information with other devices (such as a vibration sensor, etc.).

[0032] Combine Figure 2 The embodiment of the present application also provides a tool state analysis method applicable to the above electronic device. The method steps defined in the process related to the tool state analysis method can be implemented by the electronic device. Figure 2 The specific process shown is explained in detail.

[0033] Step S110 , obtaining a cutting vibration signal generated by performing a vibration acquisition operation on a target tool during a machining process.

[0034] In an embodiment of the present application, the electronic device can acquire a cutting vibration signal generated by performing a vibration acquisition operation on a target tool during machining. For example, the vibration acceleration of the target tool can be measured using an acceleration sensor provided on the target tool. Thus, the cutting vibration signal can be a vibration acceleration signal. In other embodiments, a corresponding cutting vibration signal can also be generated by measuring using a displacement sensor or a velocity sensor.

[0035] Step S120 : performing an image rendering operation based on the cutting vibration signal to form a polar coordinate image.

[0036] In an embodiment of the present application, after acquiring the cutting vibration signal, the electronic device may perform an image rendering operation based on the cutting vibration signal to form a polar coordinate image. The cutting vibration signal is a time domain signal, typically with time as the horizontal coordinate and vibration amplitude as the vertical coordinate. The polar coordinate image is a graph representing the relationship between signal amplitude and angle, i.e., the angle of each point in the polar coordinate image typically represents the phase of the signal, while the amplitude represents the amplitude of the signal.

[0037] Step S130 : performing a feature determination operation on the polar coordinate image to form feature identification parameters.

[0038] In an embodiment of the present application, after forming the polar coordinate image, the electronic device may perform a feature determination operation on the polar coordinate image to generate feature identification parameters. The image rendering operation may include correcting the amount of sampled data within a period of the polar coordinate transformation, where the corrected sampled data is used to determine the polar angle in the polar coordinate image, and / or the feature determination operation may include correcting the determined area corresponding to each tooth of the target tool, where the corrected area is used to determine the feature identification parameters. That is, in one embodiment (correction is required in step S120, but not in step S130, as can be done using related prior art), the amount of sampled data within a period of the polar coordinate transformation may be first determined, then the sampled data is corrected, and the polar angle in the polar coordinate image is determined based on the corrected sampled data, thereby forming the corresponding polar coordinate image. The area corresponding to each tooth in the polar coordinate image is then determined, and finally, the corresponding feature identification parameters are determined based on the area. In a second embodiment (correction is required in step S120 and correction is required in step S130), the amount of sampled data within a period of polar coordinate transformation can be first determined, then the sampled data amount is corrected, and based on the corrected sampled data amount, the polar angle in the polar coordinate image is determined to form a corresponding polar coordinate image, and then the area of ​​the region corresponding to each tooth in the polar coordinate image is determined, and the area of ​​the region is corrected, and finally, the corresponding feature identification parameter is determined based on the corrected area. In a third embodiment (correction is not required in step S120, such as using relevant existing technologies, and correction is required in step S130), the amount of sampled data within a period of polar coordinate transformation can be first determined, then the polar angle in the polar coordinate image is determined based on the sampled data amount to form a corresponding polar coordinate image, and then the area of ​​the region corresponding to each tooth in the polar coordinate image is determined, and the area of ​​the region is corrected, and finally, the corresponding feature identification parameter is determined based on the corrected area.

[0039] Step S140: determining tool status data corresponding to the target tool based on the feature identification parameters.

[0040] In an embodiment of the present application, after forming the characteristic identification parameters, the electronic device can determine the tool status data corresponding to the target tool based on the characteristic identification parameters. The tool status data is used to indicate whether the target tool is damaged. It should be noted that in this embodiment of the present application, damage to the target tool can mean a state different from the initial use state of the target tool, or damage to the extent that it reduces the dimensional accuracy and surface quality of the cut part, or even causes the part to be scrapped.

[0041] Based on the above, on the one hand, since the tool state data can be determined by analyzing the cutting vibration signal, it can have higher objectivity and higher reliability of the results compared to conventional technical solutions based on manual detection, and it can also improve the efficiency of analysis or detection. On the other hand, since the image drawing operation includes correcting the amount of sampled data within the period in the polar coordinate transformation, and / or the feature determination operation includes correcting the area corresponding to each tooth of the determined target tool, and correcting the amount of sampled data can reduce the interference caused by signal drift to a certain extent, enhance the feature difference caused by tool breakage, thereby improving the accuracy of the analysis, and correcting the area can improve the influence of signal fluctuations on recognition to a certain extent, therefore, it can improve the problem of relatively low reliability of tool state analysis in the prior art.

[0042] First, it should be noted that the specific method for obtaining the cutting vibration signal is not limited and can be selected according to actual needs. For example, in an alternative embodiment, the electronic device can be connected to a corresponding vibration sensor for communication, so that the electronic device can obtain the cutting vibration signal in real time. For example, in another alternative embodiment, after the vibration sensor collects and forms the cutting vibration signal, it can first store it in a corresponding storage device. When tool status analysis is required, the electronic device obtains the cutting vibration signal from the storage device.

[0043] Secondly, it should be noted that for step S120 , the specific method of performing the image drawing operation based on the cutting vibration signal is not limited and can be selected accordingly according to actual needs.

[0044] For example, in an alternative embodiment, when correction is not required, relevant existing technologies can be used, and the processing logic can refer to the relevant description above. For another example, in another alternative embodiment, when correction is required to reduce interference caused by vibration signal drift and enhance image feature differences caused by tool breakage, the above-mentioned step S120 can further include steps S121, S122, S123, and S124, as follows.

[0045] Step S121 , determining the sampling frequency of the cutting vibration signal, determining the spindle speed corresponding to the target tool, and determining the initial sampling data volume based on the sampling frequency and the spindle speed.

[0046] In an embodiment of the present application, the sampling frequency of the cutting vibration signal and the spindle speed corresponding to the target tool can be determined. Furthermore, based on the sampling frequency and the spindle speed, the initial sampling data volume is determined, i.e., the number of data points within each 360° range of the cutting vibration signal when performing polar coordinate transformation is determined. The initial sampling data volume and the sampling frequency have a positive correlation, while the initial sampling data volume and the spindle speed have a negative correlation.

[0047] Step S122 : Based on the pre-configured image transformation correction coefficient, the initial sampling data volume is corrected to form a corrected sampling data volume.

[0048] In the embodiment of the present application, after obtaining the initial sampling data volume, the initial sampling data volume can be corrected based on a pre-configured image transformation correction coefficient to form a corrected sampling data volume. Exemplarily, the image transformation correction coefficient can be an even number.

[0049] Step S123 : for each data point in the cutting vibration signal, based on the corrected sampling data amount, determining the polar angle corresponding to the data point and determining the vibration amplitude corresponding to the data point.

[0050] In an embodiment of the present application, after obtaining the corrected sampled data volume, for each data point in the cutting vibration signal, the polar angle corresponding to that data point is determined based on the corrected sampled data volume (the polar angle can be determined using relevant existing techniques and will not be described in detail here; the focus of this application is on correcting the initial sampled data volume), and the vibration amplitude corresponding to that data point is determined. It should be noted that if correction is necessary, the polar angle corresponding to that data point and the vibration amplitude corresponding to that data point can be determined directly based on the initial sampled data volume.

[0051] Step S124 : performing an image drawing operation based on the polar angle and vibration amplitude corresponding to each data point in the cutting vibration signal to form a polar coordinate image.

[0052] In the embodiment of the present application, after obtaining the polar angle and vibration amplitude corresponding to each data point, an image drawing operation can be performed based on the polar angle and vibration amplitude corresponding to each data point in the cutting vibration signal to form a polar coordinate image. Figure 3 As shown in the figure, it is a schematic diagram of the polar coordinate conversion of the cutting vibration signal of a 4-tooth tool, where (a) to (d) are polar coordinate images without using the image transformation correction coefficient. The value of the aspect ratio L / W of the area corresponding to each lobe is smaller than that of images (e) to (f). The data points in the lobe area have a scattered shape in the width direction, and the polar coordinate images of (e) to (f) are formed by using the image transformation correction coefficient (a=2). The value of the aspect ratio L / W of the area corresponding to the lobe in the polar coordinate images of (e) to (f) increases to more than twice that of (a) to (d), and the signal difference between each area caused by tooth damage is more obvious. In addition, as Figure 4 Figure 2 is a schematic diagram of the polar coordinate transformation of the cutting vibration signal of a 2-tooth tool, where (a) to (d) are polar coordinate images without using the image transformation correction coefficient, and (e) to (f) are polar coordinate images formed using the image transformation correction coefficient (a=4). Similarly, the aspect ratio L / W value of the lobe corresponding area of ​​images (e) to (f) obtained using the image transformation correction coefficient is significantly increased compared to (a) to (d).

[0053] It is understandable that, in the above-mentioned step S122, the specific manner of correcting the initial sampling data volume is not limited. For example, in an alternative embodiment, the corresponding relationship between the sampling frequency, the spindle speed, the image transformation correction coefficient, and the corrected sampling data volume is represented by the following formula: ; Wherein, N is the amount of sampled data after correction, a is the image transformation correction coefficient, and f s is the sampling frequency, and n is the spindle speed. That is, the image transformation correction coefficient and the initial sampling data volume can be multiplied to obtain the corrected sampling data volume.

[0054] Thirdly, it should be noted that for step S130 , the specific method of performing the feature determination operation on the polar coordinate image is not limited and can be selected according to actual needs.

[0055] For example, in an alternative embodiment, when correction is not required, relevant existing technologies can be used for implementation, and the processing logic can refer to the relevant description above. For another example, in another alternative embodiment, when correction is required to reduce interference caused by vibration signal fluctuations, the above-mentioned step S130 can further include steps S131, S132, S133, S134, and S135, the specific contents of which are as follows.

[0056] Step S131, obtaining the number of teeth corresponding to the target tool.

[0057] In an embodiment of the present application, the number of teeth corresponding to the target tool can be obtained. As mentioned above, the number can be a value such as 2 or 4.

[0058] Step S132: determining a distribution area of ​​each data point in the polar coordinate image based on the number of the blade teeth.

[0059] In an embodiment of the present application, after the number of blade teeth is obtained, the distribution area of ​​each data point in the polar coordinate image can be determined based on the number of blade teeth. For example, the data point distribution area can be determined based on the relative distribution relationship characteristics of the vibration signals corresponding to different blade tooth areas in the polar coordinate image.

[0060] Step S133: determining the area corresponding to each of the data point distribution areas.

[0061] In an embodiment of the present application, after determining each data point distribution area, the area corresponding to each data point distribution area can be determined respectively, wherein the area can refer to the area of ​​the area covered by the data points.

[0062] Step S134 , determining the area of ​​the correction area corresponding to each of the cutting teeth based on the area corresponding to each of the data point distribution areas and a pre-configured area correction coefficient.

[0063] In an embodiment of the present application, after determining the area corresponding to each of the data point distribution areas, the corrected area corresponding to each of the cutting teeth can be determined based on the area corresponding to each of the data point distribution areas and a pre-configured area correction coefficient.

[0064] Step S135: determining a feature identification parameter based on the area of ​​the correction region corresponding to each of the cutting teeth.

[0065] In the embodiment of the present application, after obtaining the area of ​​the correction region corresponding to each of the cutter teeth, a feature identification parameter can be determined based on the area of ​​the correction region corresponding to each of the cutter teeth.

[0066] It is understood that, in the above step S132, the specific method of determining the distribution area of ​​each data point in the polar coordinate image is not limited. For example, in an alternative embodiment, the above step S132 may further include the following content: First, the number of data point distribution areas in the polar coordinate image can be determined based on the number of tool teeth and a pre-configured image transformation correction coefficient, wherein the image transformation correction coefficient is equal to the area correction coefficient, and the image transformation correction coefficient is also used to correct the amount of sampled data within a period in the polar coordinate transformation during the image drawing operation. The number of tool teeth and the image transformation correction coefficient both have a positive correlation with the number of data point distribution areas in the polar coordinate image; illustratively, the number of data point distribution areas = z0 × a, where z0 is the theoretical number of tool teeth obtained and a is the image transformation correction coefficient; Secondly, each data point distribution area in the polar coordinate image may be determined based on the number of data point distribution areas in the polar coordinate image.

[0067] It is understood that, in the above step S134, the specific method of determining the area of ​​the correction region corresponding to each of the cutting teeth is not limited. For example, in an alternative embodiment, the above step S134 may further include the following content: First, a data point distribution region with a minimum area value can be determined among the data point distribution regions, and the data point distribution region is determined as the first data point distribution region in the target sequence. For example, the corresponding area can be marked as size1; Secondly, the polar coordinate image can be traversed in a clockwise direction starting from the first data point distribution area, and the arrangement relationship of each other data point distribution area in the target sequence can be determined based on the order of traversal of each other data point distribution area. For example, the first other data point distribution area traversed can be used as the second data point distribution area, and the second other data point distribution area traversed can be used as the third data point distribution area. Accordingly, the corresponding area areas can be marked as size2, ..., size n , where n is the number of data point distribution areas; Then, the area corresponding to each data point distribution area can be processed according to the arrangement relationship of the data point distribution areas in the target sequence, the pre-configured area correction coefficient, and the pre-determined averaging calculation formula to obtain the corrected area corresponding to each tooth. For example, in an alternative embodiment, the averaging calculation formula may include the following: ; Among them, s_m j is the area of ​​the correction region corresponding to the jth tooth, a is the area correction coefficient, size j It represents the area corresponding to the distribution area of ​​the jth data point, and z0 is the number of teeth.

[0068] For example: For a 4-tooth tool, the image transformation correction coefficient (i.e., area correction coefficient) a=2, and the obtained correction area areas are s_m1=(size1+size5) / 2, s_m2=(size2+size6) / 2, s_m3=(size3+size7) / 2, and s_m2=(size4+size8) / 2 respectively; For a 2-tooth tool, the image transformation correction coefficient (i.e., area correction coefficient) a=4, and the obtained correction area areas are s_m1=(size1+size3+size5+size7) / 2 and s_m2=(size2+size4+size6+size8) / 2 respectively.

[0069] Among them, the above-mentioned averaging calculation formula is used to achieve the effect of correcting the area. Figure 5 As shown, when the image transformation correction coefficient (i.e., area correction coefficient) is not used, the vibration signals of the continuous time windows at both ends, for example, array 1 and array 2, are transformed into polar coordinates to obtain the vibration signal polar coordinate images. Figure 5 (a) and attached Figure 5 (b) At this time, Figure 5 (a) and Figure 5 The image (b) uses different maximum values ​​A1 and A2 (maximum amplitude values) to set the y-axis range. Due to factors such as signal time drift, the signals of the same tooth in the two images are not in the same angle range, and the shape scaling is not in the same scale range. When using the image transformation correction coefficient (i.e., the area correction coefficient), the data of array 1 and array 2 can be combined and plotted on Figure 5 In the polar coordinate image shown in (c), the data generated by the same tooth cutting are mapped to the symmetrical lobe areas using an interleaved processing method, as shown in Figure 5 The regions at positions 1 and 5 in (c) are scaled using the same maximum vibration amplitude.

[0070] It is understood that, in the above step S135, the specific method of determining the characteristic identification parameter is not limited. For example, in an alternative embodiment, the above step S135 may further include the following contents: First, in the correction area corresponding to each of the teeth, a first correction area with a minimum value and a second correction area with a maximum value can be determined. For example, the first correction area is s_m min , the area of ​​the second correction region is s_m max ; Next, the ratio between the area of ​​the first correction region and the area of ​​the second correction region can be determined (eg, S index =s_m min / s_m max ), and based on the ratio, determining a characteristic identification parameter, wherein the characteristic identification parameter and the ratio have a positive correlation; illustratively, in an alternative embodiment, the ratio can be directly used as the characteristic identification parameter, and in another alternative embodiment, the ratio can be multiplied by a weight coefficient to obtain the characteristic identification parameter. For example, when it is necessary to increase the intensity of damage monitoring, the weight coefficient can be less than 1, and when the sensitivity to damage monitoring is relatively low, the weight coefficient can be greater than 1. In addition, if Figure 6 As shown, by using the solution of correcting both the sampling data volume and the regional area in the embodiment of the present application, compared with the case where both the sampling data volume and the regional area are not corrected, the feature identification parameter can be increased from 0.52 to 0.42, and the image feature difference caused by tool breakage is more obvious.

[0071] Fourthly, it should be noted that for step S140 , the specific method of determining the tool status data corresponding to the target tool is not limited and can be selected according to actual needs.

[0072] For example, in an alternative embodiment, the feature identification parameter can be further processed, such as multiplied by a set weight parameter to achieve weighted update, and then the weighted updated feature identification parameter is compared with a threshold to obtain the prop status data.

[0073] For another example, in another alternative implementation, the above step S140 may further include the following: First, the feature identification parameter can be compared with a pre-configured feature identification threshold; for example, the feature identification threshold can be 0.4, 0.5, 0.6, etc.; Secondly, if the characteristic identification parameter is less than the characteristic identification threshold, the tool status data corresponding to the target tool is determined to be damaged; Then, if the feature identification parameter is not less than the feature identification threshold, the tool status data corresponding to the target tool is determined to be not damaged.

[0074] Combine Figure 7 The present application also provides a tool state analysis device applicable to the above electronic device. The tool state analysis device may include a signal acquisition module, a polar coordinate image drawing module, an identification parameter determination module, and a tool state determination module.

[0075] In detail, the signal acquisition module can be used to acquire the cutting vibration signal generated by the vibration acquisition operation of the target tool during the machining process. Figure 2 As shown in step S110, for the relevant content of the signal acquisition module, reference may be made to the above description of step S110.

[0076] In detail, the polar coordinate image drawing module can be used to perform an image drawing operation based on the cutting vibration signal to form a polar coordinate image. In the embodiment of the present application, the polar coordinate image drawing module can be used to perform Figure 2 Regarding step S120 shown, the relevant contents of the polar coordinate image drawing module can refer to the above description of step S120.

[0077] In detail, the identification parameter determination module can be used to perform a feature determination operation on the polar coordinate image to form a feature identification parameter, wherein the image drawing operation includes correcting the amount of sampled data within a period in the polar coordinate transformation, and the corrected amount of sampled data is used to determine the polar angle in the polar coordinate image, and / or the feature determination operation includes correcting the area corresponding to each tooth of the target tool, and the corrected area is used to determine the feature identification parameter. In an embodiment of the present application, the identification parameter determination module can be used to perform Figure 2 As shown in step S130, for the relevant content of the identification parameter determination module, reference can be made to the above description of step S130.

[0078] In detail, the tool state determination module can be used to determine the tool state data corresponding to the target tool based on the feature identification parameters, wherein the tool state data is used to characterize whether the target tool is damaged. In the embodiment of the present application, the tool state determination module can be used to execute Figure 2 As shown in step S140, for the relevant content of the tool state determination module, reference can be made to the above description of step S140.

[0079] In an embodiment of the present application, corresponding to the above-mentioned tool state analysis method applied to the electronic device, a computer-readable storage medium is also provided, in which a computer program is stored. When the computer program is run, the various steps of the tool state analysis method are executed.

[0080] The steps executed when the aforementioned computer program is running will not be described in detail here, and reference may be made to the above explanation of the tool state analysis method.

[0081] In summary, the tool state analysis method and device, electronic device, and storage medium provided by the present application first obtain a cutting vibration signal formed by performing a vibration acquisition operation on a target tool during the machining process; secondly, an image drawing operation is performed based on the cutting vibration signal to form a polar coordinate image; then, a feature determination operation is performed on the polar coordinate image to form feature identification parameters; finally, based on the feature identification parameters, the tool state data corresponding to the target tool is determined. Based on the above content, on the one hand, since the tool state data can be determined by analyzing the cutting vibration signal, compared with conventional technical solutions based on manual detection, it can have higher objectivity, make the results more reliable, and also improve the efficiency of analysis or detection. On the other hand, since the image drawing operation includes correcting the amount of sampling data within a period in the polar coordinate transformation, and / or the feature determination operation includes correcting the area of ​​the region corresponding to each tooth of the determined target tool, and correcting the amount of sampling data can reduce the interference caused by signal drift to a certain extent, enhance the feature difference caused by tool breakage, thereby improving the accuracy of the analysis, and correcting the area of ​​the region can improve the influence of signal fluctuations on recognition to a certain extent, therefore, the problem of relatively low reliability of tool state analysis in the prior art can be improved.

[0082] In the several embodiments provided in the embodiments of the present application, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device and method embodiments described above are merely schematic. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architectures, functions and operations of the devices, methods and computer program products according to the multiple embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of the code, and the module, program segment or a part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0083] In addition, the functional modules in each embodiment of the present application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0084] If the functions are implemented in the form of software modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the portion that contributes to the prior art, or the portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, electronic device, or network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk. It should be noted that, in this document, the terms "comprise," "include," or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device that includes a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article, or device. Without further constraints, an element defined by the phrase "comprises a..." does not preclude the existence of additional identical elements in the process, method, article or apparatus that includes the element.

[0085] The above description is merely a preferred embodiment of the present application and is not intended to limit the present application. Various modifications and variations are possible for those skilled in the art. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present application shall be included within the scope of protection of the present application.

Claims

1. A tool state analysis method, characterized in that: include: Acquire a cutting vibration signal generated by performing a vibration acquisition operation on a target tool during machining; Performing an image rendering operation based on the cutting vibration signal to form a polar coordinate image; performing a feature determination operation on the polar coordinate image to form feature identification parameters, wherein the image rendering operation includes correcting an amount of sampled data within a period in the polar coordinate transformation, and the corrected amount of sampled data is used to determine a polar angle in the polar coordinate image; and / or the feature determination operation includes correcting an area corresponding to each tooth of the target tool, and the corrected area is used to determine the feature identification parameters; Based on the characteristic identification parameters, tool status data corresponding to the target tool is determined, wherein the tool status data is used to indicate whether the target tool is damaged.

2. The tool state analysis method according to claim 1, characterized in that: The step of performing an image drawing operation based on the cutting vibration signal to form a polar coordinate image includes: Determining a sampling frequency of the cutting vibration signal and determining a spindle speed corresponding to the target tool, and determining an initial sampling data volume based on the sampling frequency and the spindle speed, wherein the initial sampling data volume and the sampling frequency have a positive correlation, and the initial sampling data volume and the spindle speed have a negative correlation; Based on a pre-configured image transformation correction coefficient, the initial sampling data volume is corrected to form a corrected sampling data volume; For each data point in the cutting vibration signal, determining the polar angle corresponding to the data point based on the corrected sampling data amount, and determining the vibration amplitude corresponding to the data point; An image drawing operation is performed based on the polar angle and vibration amplitude corresponding to each data point in the cutting vibration signal to form a polar coordinate image.

3. The tool state analysis method according to claim 2, characterized in that: The corresponding relationship among the sampling frequency, the spindle speed, the image transformation correction coefficient, and the corrected sampling data volume is represented by the following formula: ； Wherein, N is the amount of sampled data after correction, a is the image transformation correction coefficient, and f s is the sampling frequency, and n is the spindle speed.

4. The tool state analysis method according to claim 1, characterized in that: The step of performing a feature determination operation on the polar coordinate image to form feature identification parameters includes: Obtaining the number of teeth corresponding to the target tool; determining a distribution area of ​​each data point in the polar coordinate image based on the number of the blade teeth; respectively determining the area corresponding to each of the data point distribution areas; Determining the area of ​​the correction area corresponding to each of the cutter teeth based on the area corresponding to each of the data point distribution areas and a pre-configured area correction coefficient; A feature identification parameter is determined based on the area of ​​the correction region corresponding to each of the cutting teeth.

5. The tool state analysis method according to claim 4, characterized in that: The step of determining the distribution area of ​​each data point in the polar coordinate image based on the number of the blade teeth includes: Determining the number of data point distribution areas in the polar coordinate image based on the number of the blade teeth and a pre-configured image transformation correction coefficient, wherein the image transformation correction coefficient is equal to the area correction coefficient and is also used to correct the amount of sampled data within a period in the polar coordinate transformation during the image drawing operation, and there is a positive correlation between the number of the blade teeth and the image transformation correction coefficient and the number of data point distribution areas in the polar coordinate image; Each data point distribution area in the polar coordinate image is determined based on the number of data point distribution areas in the polar coordinate image.

6. The tool state analysis method according to claim 4, characterized in that: The step of determining the area of ​​the correction area corresponding to each of the cutting teeth based on the area corresponding to each of the data point distribution areas and a pre-configured area correction coefficient includes: Determine a data point distribution region with a minimum area value among the data point distribution regions, and determine the data point distribution region as the first data point distribution region in the target sequence; Starting from the first data point distribution area, traverse the polar coordinate image in a clockwise direction, and based on the order of traversal of each other data point distribution area, determine the arrangement relationship of each other data point distribution area in the target sequence; According to the arrangement relationship of the data point distribution areas in the target sequence, the pre-configured area correction coefficient and the pre-determined averaging calculation formula, the area corresponding to each data point distribution area is processed to obtain the corrected area corresponding to each tooth.

7. The tool state analysis method according to claim 6, characterized in that: The averaging calculation formula includes: ； Among them, s_m j is the area of ​​the correction region corresponding to the jth tooth, a is the area correction coefficient, size j It represents the area corresponding to the distribution area of ​​the jth data point, and z0 is the number of teeth.

8. The tool state analysis method according to claim 4, characterized in that: The step of determining the characteristic identification parameter based on the area of ​​the correction region corresponding to each of the cutter teeth includes: In the correction region area corresponding to each of the cutter teeth, a first correction region area with a minimum value and a second correction region area with a maximum value are determined; A ratio between the area of ​​the first correction region and the area of ​​the second correction region is determined, and a feature identification parameter is determined based on the ratio, wherein the feature identification parameter and the ratio have a positive correlation.

9. The tool state analysis method according to any one of claims 1 to 8, characterized in that: The step of determining the tool status data corresponding to the target tool based on the characteristic identification parameters includes: Comparing the characteristic identification parameter with a pre-configured characteristic identification threshold; If the characteristic identification parameter is less than the characteristic identification threshold, determining the tool status data corresponding to the target tool as being damaged; If the feature identification parameter is not less than the feature identification threshold, the tool status data corresponding to the target tool is determined to be not damaged.

10. A tool state analysis device, characterized in that: include: A signal acquisition module is used to acquire a cutting vibration signal generated by performing a vibration acquisition operation on a target tool during machining; A polar coordinate image drawing module, configured to perform an image drawing operation based on the cutting vibration signal to form a polar coordinate image; an identification parameter determination module, configured to perform a feature determination operation on the polar coordinate image to form feature identification parameters, wherein the image rendering operation includes correcting an amount of sampled data within a period in the polar coordinate transformation, the corrected amount of sampled data being used to determine a polar angle in the polar coordinate image, and / or the feature determination operation includes correcting an area corresponding to each tooth of the target tool, the corrected area being used to determine the feature identification parameters; The tool state determination module is used to determine the tool state data corresponding to the target tool based on the characteristic identification parameters, wherein the tool state data is used to indicate whether the target tool is damaged.

11. An electronic device, characterized in that: include: memory for storing computer programs; A processor connected to the memory is used to execute the computer program stored in the memory to implement the tool state analysis method according to any one of claims 1 to 9.

12. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which executes the tool state analysis method according to any one of claims 1 to 9 when the computer program is run.

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