WO2023092311A1 - 加工机高解析监控系统及方法 - Google Patents
加工机高解析监控系统及方法 Download PDFInfo
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- 238000012545 processing Methods 0.000 title claims abstract description 188
- 238000012544 monitoring process Methods 0.000 title claims abstract description 42
- 238000000034 method Methods 0.000 title claims abstract description 39
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
- B23Q—DETAILS, COMPONENTS, OR ACCESSORIES FOR MACHINE TOOLS, e.g. ARRANGEMENTS FOR COPYING OR CONTROLLING; MACHINE TOOLS IN GENERAL CHARACTERISED BY THE CONSTRUCTION OF PARTICULAR DETAILS OR COMPONENTS; COMBINATIONS OR ASSOCIATIONS OF METAL-WORKING MACHINES, NOT DIRECTED TO A PARTICULAR RESULT
- B23Q17/00—Arrangements for observing, indicating or measuring on machine tools
- B23Q17/09—Arrangements for observing, indicating or measuring on machine tools for indicating or measuring cutting pressure or for determining cutting-tool condition, e.g. cutting ability, load on tool
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
- B23Q—DETAILS, COMPONENTS, OR ACCESSORIES FOR MACHINE TOOLS, e.g. ARRANGEMENTS FOR COPYING OR CONTROLLING; MACHINE TOOLS IN GENERAL CHARACTERISED BY THE CONSTRUCTION OF PARTICULAR DETAILS OR COMPONENTS; COMBINATIONS OR ASSOCIATIONS OF METAL-WORKING MACHINES, NOT DIRECTED TO A PARTICULAR RESULT
- B23Q17/00—Arrangements for observing, indicating or measuring on machine tools
- B23Q17/12—Arrangements for observing, indicating or measuring on machine tools for indicating or measuring vibration
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01H—MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
- G01H1/00—Measuring characteristics of vibrations in solids by using direct conduction to the detector
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01H—MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
- G01H17/00—Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves, not provided for in the preceding groups
Definitions
- the invention belongs to the field of processing process analysis and diagnosis, in particular to a high-resolution monitoring system and method for a processing machine.
- Processing machine is an indispensable mechanical equipment in the manufacturing industry, especially for cutting, turning, milling, grinding and drilling, etc., it needs the assistance of processing machine. However, like all mechanical equipment, processing tools, Consumables, etc., all have their service conditions and life performance.
- Taiwan Patent No. I738935 provides a waveform analysis method that uses fast Fourier transform immediately after the amplitude meter signal is collected. Transformation (Fast Fourier Transform, FFT) method converts the time domain signal into a frequency domain signal, and observes the signal change mode of a specific frequency, so as to achieve the purpose of machine control processing machine.
- FFT Fast Fourier Transform
- the present invention provides a processing high-resolution monitoring and analysis system and method, the purpose of which is to provide a relatively simple amplitude, but the instantaneous high-resolution time-domain variation is used as the basis for judgment, and the processing machine can be monitored quickly and in real time.
- the current processing situation breaks the technical prejudice that the time domain signal cannot judge the health status of precision processing machines in the previous technology, and proposes a set of state monitoring solutions suitable for various processing machines.
- the processing machine high-resolution monitoring system of the present invention includes an inertial device and an analysis device, wherein the inertial device further includes a micro-electromechanical component and a communication component, and the micro-electromechanical component further includes an inertial unit and a processing unit, wherein the inertial unit is used to be installed in an external processing unit
- the processing unit selects the highest peak value of the amplitude per unit time from the original signal as the value point per unit time, and then uses The communication component transmits to the analysis device.
- the analysis device includes a setting interface, a waveform module and a comparison module.
- the user can set the unit time through the setting interface and transmit it to the inertial device.
- the waveform module receives the value points of each unit time and converts each Value points are connected to draw a processed waveform pattern, and then the comparison module compares the processed waveform pattern with the standard waveform pattern by fuzzy analysis to judge the similarity between the two, and use the similarity to judge whether the tool of the processing machine has been Wear and tear, or changes in processing conditions, for example, whether there are variations in the material of the workpiece being processed such as cutting corners and materials.
- the standard waveform pattern is obtained by installing the inertial device on a brand new processing machine, and using the drawn processed waveform pattern as the standard waveform pattern.
- the transmission period of the communication component is between 0.02 second and 0.25 second, and the unit time is between 0.02 second and 0.25 second.
- the present invention also provides a high-resolution monitoring method for processing, which is to set the unit time first, and then use the inertial device to detect the vibration of the processing machine that is performing the processing action, so as to obtain the original signal of the processing machine, and then add the original signal,
- the peak values of the amplitude values per unit time are set as value points, and finally the value points are connected to draw a processed waveform pattern.
- the user can compare the current processed waveform pattern with the standard industrial waveform pattern, and judge the stability of the current processing according to the similarity between the two patterns.
- the user can judge the stability of the processing according to the trend line slope of the processing waveform pattern.
- the user can judge the stability of the processing according to the peak-to-valley difference of the processed waveform pattern.
- the stability may be the uniformity of the material properties of the workpiece.
- stability can be the state of cutting force and lubricating oil during processing.
- the stability may be the durability or wear rate of the machining tool.
- processing machines include CNC processing machines, robotic arms, handling devices, punch grinders, glass cutting machines, injection molding equipment, and optoelectronic semiconductor cutting and grinding equipment.
- the present invention can be applied to processing operations such as turning, milling, grinding, drilling, etc. of CNC processing machines, or technologies such as drilling of PCBs, glass cutting, or wafer cutting and grinding.
- the present invention also provides a method for selecting processing tools, including installing the tools in batches on the processing machine, drawing the processing waveform patterns of each tool by using the processing high-resolution monitoring method, and then selecting the tool with the lowest trend line.
- the present invention also provides another processing tool selection method comprising:
- Step S51 providing a time interval
- Step S52 Provide unit time, and the unit time is less than 0.1 second;
- Step S53 Detecting the vibration of the processing machine to generate an original signal, the original signal includes complex amplitude values
- Step S54 Set the peak value of the amplitude value per unit time as the value point per unit time;
- Step S55 Draw each value point into a processed waveform pattern in time sequence
- Step S56 Set the value points in the time zone into one group every interval of the time interval, and count the value points of each group to obtain statistical indicators;
- Step S57 Comparing the statistical indexes of each group with the previous group to obtain the change value of the statistical index, if the change exceeds a threshold, it is judged that the stability of the processing machine is not good.
- the statistical index is one of maximum value, minimum value, average value, median or standard deviation, and the threshold is 15%.
- the present invention also provides another optimal method for selecting processing tools, which includes installing the tools in batches on the processing machine, drawing the processing waveform pattern and long-term trend processing waveform pattern of each tool by using the processing high-resolution monitoring method, and then selecting the amplitude
- the tool with a lower trend and the lowest peak value of the waveform pattern means that the tool can be processed with the lowest vibration, that is, the lowest cutting resistance, and the best cutting force performance. In this way, the finest cutting marks on the surface of the workpiece can be obtained to ensure the smoothness of the processed surface.
- the present invention utilizes a communication component with a transmission cycle between 0.02 seconds and 0.25 seconds, and sets a unit time between 0.02 seconds and 0.25 seconds to obtain a high-resolution processed waveform pattern, and then process the waveform pattern
- the peak-to-valley difference and the slope change of the overall processing amplitude trend line, as well as the similarity between the processing waveform pattern and the standard waveform pattern can judge the processing status of the processing machine, or select a suitable tool, and even detect and judge the wear and tear of the tool.
- the timely feedback system informs the change phenomenon so that the user can detect and avoid mistakes in real time.
- Fig. 1 is the block diagram of the high-resolution monitoring system of the processing machine of the present invention
- Fig. 2 is a step diagram of the processing high-resolution monitoring method of the present invention.
- Fig. 3 is a step diagram of the first processing tool selection method
- Fig. 4 is a step diagram of the first tool selection method
- FIG. 5A is a schematic diagram of a second signal of the present invention.
- 5B is a schematic diagram of a second signal of the present invention.
- FIG. 5C is a schematic diagram of a third signal of the present invention.
- Figure 6 is a long-term trend processing waveform pattern
- Fig. 7A is the pre-processing waveform pattern
- Fig. 7B is post-processing waveform pattern
- Fig. 8 is the processing waveform pattern of multi-cutter
- Fig. 9 is a schematic diagram of the processing procedure
- Fig. 10 is processing waveform pattern
- Figure 11 is a schematic diagram of waveform comparison.
- Fig. 12 is a step diagram of the processing high-resolution monitoring method of the present invention.
- FIG. 1 is a block diagram of a high-resolution monitoring system for a processing machine of the present invention.
- the processing machine high-resolution monitoring system of the present invention includes an inertial device 1, an analysis device 2, and a display device 3, wherein the inertial device 1 includes a micro-electromechanical component 11 and a communication component 12, and the analysis device 2 includes a setting interface 21 , a waveform module 22 and a comparison module 23.
- the analysis device 2 is a computer, and the analysis device 2 includes a setting interface 21, a waveform module 22 and a comparison module 23, and the user can adjust the operating parameters of the inertial device 1 through the setting interface 21, especially the setting of the unit time .
- the MEMS assembly 11 comprises an inertial unit 111, a memory unit 112 and a processing unit 113
- the inertial unit 111 is an accelerometer, which is used to detect the vibration of the processing machine to generate an original inertial signal
- the processing unit 113 is a processor for The peak value of the amplitude value per unit time is set as the value point per unit time, and then the value point is transmitted to the analysis device 2 by the communication component 12 using high-resolution transmission technology.
- the communication component 12 is 802.11b /g/n 2.4GHz Wi-Fi Bluetooth module.
- the memory unit 112 is a memory, which is used to temporarily store the original signal, or as a temporary storage space in an offline state.
- the waveform module 22 and the comparison module 23 are program modules.
- the waveform module 22 is used to draw the value points into a processed waveform pattern in time sequence
- the comparison module 23 is used to judge the difference between the processed waveform pattern and the standard waveform pattern. Similarity, and judge the stability of the processing machine according to the similarity.
- the display device 3 is used for displaying the processing waveform pattern and presenting the setting interface 21 for user operation.
- the user can also observe the processing waveform pattern through the display device 3 and judge the status of the processing machine in real time.
- FIG. 2 is a step diagram of the processing high-resolution monitoring method of the present invention, and the processing high-resolution monitoring method of the present invention includes:
- Step S21 Provide unit time, and the unit time is less than 0.1 second;
- Step S22 Detecting the vibration of the processing machine to generate an original signal, the original signal includes complex amplitude values
- Step S23 set the peak value (peak value) of the amplitude value per unit time as the value point per unit time;
- Step S24 Draw each value point into a processed waveform pattern in time sequence.
- the user can also provide a brand-new processing machine and install a brand-new tool on the processing machine, use steps S21-S24 to obtain a processing wave pattern for a period of time (for example: three minutes), and use this
- the processed wave pattern is a standard wave pattern.
- the material is defective, so it achieves the purpose of monitoring the status of the processing machine, and reminding the processing industry to replace the tool in time or check whether the incoming material of the processed product has the purpose of cutting corners.
- the user can judge the durability of the tool installed on the processing machine according to the rising slope of the trend line by observing the trend line of the processing wave pattern.
- the user can also judge whether the tool installed in the process is about to be damaged according to the change of the peak-to-valley difference by observing the trend line of the processing waveform pattern, and thus prevent the tool from breaking suddenly.
- Figure 3 is a step diagram of the first processing tool selection method, including:
- Step S31 providing plural tools
- Step S32 installing one of the cutters on the processing machine
- Step S33 using steps S21-S24 to obtain a processed waveform pattern
- Step S34 Repeat step S33 until the processing waveform patterns of all tools are obtained
- Step S35 Comparing the waveform patterns and selecting the tool with the lowest slope of the trend line.
- Figure 4 is a step diagram of the first tool selection method, including:
- Step S41 providing plural tools
- Step S42 installing one of the cutters on the processing machine
- Step S43 using steps S21-S24 to obtain a processed waveform pattern
- Step S44 Repeat step S43 until the processing waveform patterns of all tools are obtained
- Step S45 Compare the waveform diagrams, and select the tool with the lowest peak-to-valley difference.
- FIG. 5A to FIG. 5C are schematic diagrams of the first to third signals of the present invention.
- the original inertial signal 4 detected by the inertial unit 111 includes a complex amplitude value 41;
- step S21 after the user sets an appropriate unit time length through the setting interface 21, the processing unit 11 cuts the original signal 4 into a plurality of unit times 42;
- step S22 the processing unit 11 sets the peak value of the amplitude value 41 within the unit time 42 as the value point 43;
- step S23 the waveform module 22 connects each value point 43 to form a processed waveform pattern 5 .
- Figure 6 is a long-term trend processing waveform pattern.
- the processing waveform pattern 5 has an X-axis trend line 51 and a Y-axis trend line 52. It can be found through observation that whether it is an X-axis trend line 51 or a Y-axis trend line
- the slopes of the axis trend lines 52 are all greater than zero, that is to say, the vibration of the processing machine will increase with time. Therefore, the user can judge the durability of the consumables of the processing machine by observing the slopes of the trend lines. The durability of processing machine tools is most notable.
- Fig. 7A and 7B are the waveform pattern of pre-processing and the waveform pattern of post-processing.
- Fig. 7A when the processing machine and its cutting tools are still in a brand-new state, the peak-to-valley difference of the Y-axis trend line 52 is different.
- Figure 7B after 15 minutes of use, as shown in Figure 7B, the processing machine and its tools are worn out, so the peak-to-valley difference of the Y-axis trend line 52 approaches 3, and the trend line ratio of Figure 7B
- the trend line of 7A is more chaotic.
- the user can use the processing high-speed instantaneous monitoring method to draw the processing waveform pattern and long-term trend graph of a tool, and then select the tool with a lower amplitude trend and the lowest peak value of the waveform pattern, which means that the tool can be processed with the lowest value.
- the amount of vibration is the lowest, that is, the lowest cutting resistance, and the best cutting force performance, so as to obtain the smallest cutting marks on the surface of the workpiece to ensure the smoothness of the processed surface.
- Figure 8 is a multi-tool processing waveform pattern.
- Figure 8 draws the processing waveform pattern of six tools executing the same processing program on the same processing machine, which lasted 16.5 minutes in total.
- /DE tool, SD tool, SDGH tool, SDGMR tool and SDG tool the user can select the most suitable tool for this processing machine and processing program by comparing the peak-to-valley difference and the slope of the trend line of the six tools.
- the user can also provide various lubricating oils or processing parameters, imitate steps S32-S35 or steps S42-S45, and select the most appropriate lubricating oil or processing parameters.
- Figure 9 is a schematic diagram of the processing program. As shown in the figure, the processing machine continues to cut the reciprocating action of the block 6 back and forth. We can divide the action of cutting the block 6 into two decompositions: entering the knife 71 and exiting the knife 72. step.
- Fig. 10 is a processing waveform pattern.
- the processing waveform pattern 5 presents a plurality of regular peaks and troughs, and in each round, the deepest part of the trough It is the knife exit point 82, and after the knife entry point 81 is the knife exit point 82.
- the machining waveform pattern 5 is a regular pattern in which the knife entry point 81 and the knife exit point 82 appear continuously.
- Figure 11 is a schematic diagram of waveform comparison. As shown in the figure, if the standard waveform pattern and the processed waveform pattern are superimposed, you can judge whether the processing machine follows the law by comparing the similarity between the processed waveform pattern and the standard waveform pattern. Different peaks and troughs appear periodically, and then the state of the processing machine can be judged.
- the user can set a section of the processed waveform pattern 5 as a standard waveform pattern, and then judge the similarity between the processed waveform pattern and the standard waveform pattern in real time by means of fuzzy analysis and comparison. If the similarity between the two does not meet the standard, it is judged that the stability of the processing machine is not up to the standard.
- the stability can be to check the material characteristics of the processed object.
- stability can be the state of cutting force and lubricating oil during processing.
- the stability may be the durability or wear rate of the machining tool.
- FIG. 12 is a step diagram of the high-resolution processing monitoring method of the present invention.
- the high-resolution processing monitoring method of the present invention includes:
- Step S51 providing a time interval
- Step S52 Provide unit time, and the unit time is less than 0.1 second;
- Step S53 Detecting the vibration of the processing machine to generate an original signal, the original signal includes complex amplitude values
- Step S54 Set the peak value of the amplitude value per unit time as the value point per unit time;
- Step S55 Set the value points in the time zone into one group at each interval of the time interval, and count the value points of each group to obtain statistical indicators;
- Step S56 Comparing the statistical indicators of each group with the previous group to obtain the change value of the statistical indicators
- Step S57 Observe the change value, and when the change exceeds a threshold, it is judged that the stability of the processing machine is not good.
- the statistical index is one of maximum value, minimum value, average value, median or standard deviation, and the threshold is 15%.
- steps S21-S24 and steps S51-S57 can be run simultaneously, thus increasing the ability of the present invention to judge the stability of the processing machine.
- the high-resolution monitoring system of the processing machine of the present invention obtains the high-resolution signal of the vibration of the processing machine through the micro-electromechanical component, and uses the communication component with high-resolution transmission speed to transmit the signal to the analysis device quickly and in real time, and then High-resolution processed waveform patterns are produced by the analysis device, or statistics are made on the signal.
- the present invention provides a variety of application methods for processing waveform patterns. Through the high-resolution information provided by processing waveform patterns, those skilled in the art can judge the state of the processing machine, the state of the tool or the quality of the processed object .
- the present invention provides users with a real-time status analysis solution for processing machines, assists users in optimizing processing conditions, and gives real-time feedback. Users can rely on the reproducibility of processing waveform patterns, vibration peak The overall trend line slope, the deformation mode of the waveform pattern and the peak-to-valley difference can be used to judge the processing status.
- the present invention utilizes the time-domain signal measured by the accelerometer to draw a high-resolution processing waveform pattern that can reflect the state of the processing machine through the high-resolution processing of the analysis device.
- the frequency domain analysis is also simple, real-time, accurate and more versatile. Even in the future, the pattern can be confirmed by fuzzy analysis and comparison or AI comparison during machine processing.
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Abstract
一种加工机高解析监控系统及方法,可进行加工条件的优化,并给予实时地回馈,包含微机电组件(11)及分析装置(2),其中微机电组件(11)侦测加工中所发生的振动后,将短时间的振动变化的峰值设为值点,并将值点即时传输至分析装置(2),分析装置(2)再将各值点绘制成高解析加工波形图案,并计算各时间段中的数值及整体线性状况,最后依据加工波形图案的再现性、振动峰值的整体趋势线斜率、波形图案的变形方式及峰谷差值判断加工的状态,有别于先前技术的频域分析,该方法原理虽然简单,但具有更佳的泛用性。
Description
本发明为加工制程分析诊断领域,尤其是一种加工机高解析监控系统及方法。
加工机为制造业中,一项不可缺少的机械设备,尤其是对于切割、车削、铣削、研磨及钻孔等加工动作,更是需要加工机的协助,然而如同所有的机械设备,加工刀具、耗材等,皆有其使用条件以及寿命表现。
传统上使用者须要持续监控加工机的加工状态,避免加工变异造成工件受损,或是因为加工机状态的不同,而生产出质量不同的产品,此种方式需要使用者的长期经验以及时间,来确保加工质量及生产结果。
在加工监控领域中,观察加工动作时所产生的震度、晃动或声音为主流的监控方式,传统上是借助有经验的工程师或技师,以其肉眼及听觉观察,并依经验判断当前的加工状态,然后须等到耗费一定时间,待该加工工件完成,再取下加工工件,并检查该工件外观尺寸表面状态之后,才能确认此工件的加工质量,因此执行上仰赖人员的经验,并且造成时间跟材料损失浪费,又无法得到任何数值做为后续参考。
发展至今,加工机的监控已标准化,国际标准化组织提出ISO 10816-3标准,并搭配震动计作为加工机健康评估的判断依据,然而上述监控方式,主要是通过长期监测,并以期间内的平均振动值作为判定基准,较适用于大型加工机,但难以适用于现代化地精密加工设备。
现有振动精密加工的监控的技术,大部分舍弃以时域振幅数值变化为判断基础,也就是说,在本领域具有通常知识者的认知上,时域分析讯号在一般加工中,表现杂乱无序难以分析,因此难以作为精密加工的监控判断基础。
[根据细则26改正03.12.2021]
如中国台湾第I738935号专利所揭示的先前技术,其即是现代舍弃时域分 析的振幅波形图案的一个范例,该专利提供一种波形解析方法,在收集振幅计的讯号后,立即以快速傅立叶变换(Fast Fourier Transform,FFT)的方式,将时域讯号转换为频域讯号,并观察特定频率的讯号变化方式,而达到机控加工机的目的。
如中国台湾第I738935号专利所揭示的先前技术,其即是现代舍弃时域分 析的振幅波形图案的一个范例,该专利提供一种波形解析方法,在收集振幅计的讯号后,立即以快速傅立叶变换(Fast Fourier Transform,FFT)的方式,将时域讯号转换为频域讯号,并观察特定频率的讯号变化方式,而达到机控加工机的目的。
然而上述以频域讯号作为分析的方式,其运算过程较为繁杂,讯号处理时间漫长,频率的变化也伴随不同地加工机、加工动作、加工刀具及被加工物的选择而有所不同,以上条件参数皆会影响频域讯号的判读方式,并没有一个固定地通则。造成现今业界还无法有一简便的方式解读加工变化并优化。
本案发明人鉴于上述先前技术所衍生的各项缺点,乃亟思加以改良创新,并经多年苦心孤诣潜心研究后,终于成功研发完成本件加工机高解析监控系统及方法,并可实时反馈加工系统,预防检知加工状态并对其进行分析。
发明内容
为解决上述先期技术的问题,本发明提供加工高解析监控分析系统及方法,其目的在于提供较单纯的振幅大小,但瞬时高分辨率的时域变化量为判断基础,快速实时地监控加工机当前加工状况,破除先前技术认为时域讯号无法判断精密加工机健康状态的技术偏见,同时提出一套适用于各种加工机的状态监控方案。
本发明的加工机高解析监控系统包含惯性装置及分析装置,其中惯性装置又包含微机电组件及通讯组件,而微机电组件更包含惯性单元及处理单元,其中惯性单元系用于安装于外界加工机上,通过侦测加工机于加工动作中所产生的振动,并将振动转换成原始讯号,处理单元则由原始讯号中,挑选单位时间内振幅直最高的峰值为单位时间的值点,然后利用通讯组件传输至分析装置。
其中,分析装置包含设定接口、波形模块及比对模块,用户可以透过设定接口设定单位时间,并传输给惯性装置,其中波形模块则系接受各单位时间的值点后,将各值点连接而绘制成加工波形图案,然后比对模块再将加工 波形图案与标准波形图案以模糊分析比较的方式,判断二者之间的相似度,并利用相似度判断加工机的刀具是否已经耗损,或是加工条件发生变化,例如,被加工的工件的材质是否有偷工减料等变异产生。
其中,标准波形图案的获得是将惯性装置安装于全新地加工机,并将绘制出来的加工波形图案当作标准波形图案。
其中,通讯组件的传输周期介于0.02秒至0.25秒,且单位时间介于0.02秒至0.25秒。
本发明还提供一种加工高解析监控方法,其系先设定单位时间,然后利用惯性装置侦测正在执行加工动作的加工机的振动,而获得加工机的原始讯号,再将原始讯号中,单位时内的振幅值的峰值设为值点,最后将值点连接而绘制成加工波形图案。
其中,用户可以将目前的加工波形图案与标准工波形图案比对,并依据二图案的相似度判断目前加工的稳定性。
其中,用户可以依据加工波形图案的趋势线斜,判断加工的稳定性。
其中,用户可以依据加工波形图案的峰谷差值,判断加工的稳定性。
其中,稳定性可以是被加工物的材质特性的均一性。
其中,稳定性可以是加工中切削力及润滑油的状态。
其中,稳定性可以是加工刀具的耐久性或耗损率。
其中,加工机包含CNC加工机、机械手臂、搬运装置、冲床磨床、玻璃切割机、射出成形设备以及光电半导体切割研磨设备。
其中,本发明可应用于CNC加工机的车削、铣削、研磨、钻孔等加工动作,或是PCB的钻孔、玻璃切割或晶圆切割研磨等技术。
本发明还提供一种加工刀具挑选方法,包含将刀具分批安装于加工机,并利用加工高解析监控方法绘制出个刀具的加工波形图案,然后选择趋势线最低的刀具。
本发明还提供另一种加工刀具挑选方法包含:
步骤S51:提供时间区间;
步骤S52:提供单位时间,且单位时间低于0.1秒;
步骤S53:侦测加工机的振动而产生原始讯号,原始讯号包含复数振幅值;
步骤S54:将单位时间内的振幅值的峰值设为单位时间的值点;
步骤S55:将各值点依时序绘制成加工波形图案;
步骤S56:每间隔该时间区间,将时间区内的值点设成一组,并统计各组的值点而获得统计指标;
步骤S57:比较各组与其前一组的统计指标,而获得统计指标的变化值,若变化超过阈值,则判断加工机的稳定性不佳。
其中,统计指标为最大值、最小值、平均值、中位数或标准偏差的其中之一,阈值为15%。
本发明还提供另一种最佳的加工刀具挑选方法,包含将刀具分批安装于加工机,并利用加工高解析监控方法绘制出个刀具的加工波形图案及长期趋势加工波形图案,然后选择振幅趋势较低且波形图案的峰值最低的刀具,即表示使用该刀具加工,可以得到最低的振动量,也就是有最低的切削阻力,和最好的切削力表现。以此获得被加工物的表面最细微的切削痕迹,确保加工面的光滑度。
综上所述,本发明利用传输周期介于0.02秒至0.25秒的通讯组件,并设定介于0.02秒至0.25秒的单位时间,获得高分辨率的加工波形图案,再通过加工波形图案的峰谷差值及整体加工振幅趋势线斜率变化,以及加工波形图案与标准波形图案之间的相似度,判断加工机的加工的状态,或是挑选合适刀具,甚至可以察觉判断刀具的耗损状况,以及被加工物的材料特性及质量,并及时反馈系统告知该变化现象让使用者实时发觉避免错误。
图1为本发明加工机高解析监控系统的方块图;
图2为本发明的加工高解析监控方法的步骤图;
图3为第一种加工刀具挑选方法的步骤图;
图4为第一种刀具挑选方法的步骤图;
图5A为本发明的第二讯号示意图;
图5B为本发明的第二讯号示意图;
图5C为本发明的第三讯号示意图;
图6为长期趋势加工波形图案;
图7A为前期加工波形图案;
图7B为后期加工波形图案;
图8为多刀具的加工波形图案;
图9为加工程序示意图;
图10为加工波形图案;
图11为波形比较示意图。
[根据细则91更正 16.12.2021]
图12为本发明的加工高解析监控方法的步骤图。
图12为本发明的加工高解析监控方法的步骤图。
符号的简单说明:
1:惯性装置
11:微机电组件
111:惯性单元
112:记忆单元
113:处理单元
12:通讯组件
2:分析装置
21:设定接口
22:波形模块
23:比对模块
3:显示设备
4:原始讯号
41:内振幅值
42:单位时间
43:值点
5:加工波形图案
51:X轴趋势线
52:Y轴趋势线
53:Y轴趋势线
6:块材
71:入刀
72:出刀
81:入刀点
82:出刀点
S21-S24:步骤
S31-S35:步骤
S41-S45:步骤
S51-S57:步骤
为利本领域具有通常知识者了解本发明的技术特征、内容与优点及其所能达到的功效,兹将本创作配合附图,并以实施例的表达形式详细说明如下,而其中所使用的图式,其主旨仅为示意及辅助说明书使用,未必为本发明实施后的真实比例与精准配置,故不应就所附的图式的比例与配置关系解读、局限本发明于实际实施上的权利范围,在这里先进行说明。
请参阅图1,其系为本发明加工机高解析监控系统的方块图。如图所示,本发明的加工机高解析监控系统包含惯性装置1、分析装置2及显示设备3,其中惯性装置1包含微机电组件11及通讯组件12,其中分析装置2包含设定接口21、波形模块22及比对模块23。
其中,分析装置2为计算机,且分析装置2包含设定接口21、波形模块22及比对模块23,用户可透过设定接口21调整惯性装置1的操作参数,尤其是单位时间的设定。
其中,微机电组件11包含惯性单元111、记忆单元112及处理单元113,惯性单元111为加速规,系用于侦测加工机的振动而产生原始惯性讯号,处理单元113为处理器,系用于将单位时间内的振幅值的峰值设为单位时间的值点,然后由通讯组件12以高解析传输技术,将值点传输给分析装置2,在一实施例中,通讯组件12为802.11 b/g/n 2.4GHz Wi-Fi蓝牙模块。
其中,记忆单元112为内存,系用于暂存原始讯号,或是作为脱机状态时的暂存空间。
其中,波形模块22及比对模块23为程序模块,波形模块22系用于将值点依时序绘制成加工波形图案,比对模块23则系用于判断加工波形图案与标准波形图案之间的相似度,并依据相似度判断加工机的稳定性。
其中,显示设备3则系用于显示加工波形图案,以及呈现设定接口21方便用户操作,使用者亦可透过显示设备3观察加工波形图案,实时判断加工机的状态。
请参阅图2,其系为本发明的加工高解析监控方法的步骤图,本发明的加工高解析监控方法包含:
步骤S21:提供单位时间,且单位时间低于0.1秒;
步骤S22:侦测加工机的振动而产生原始讯号,原始讯号包含复数振幅值;
步骤S23:将单位时间内的振幅值的峰值(peak value)设为单位时间的值点;
步骤S24:将各值点依时序绘制成加工波形图案。
在一实施例中,使用者还可以提供一台全新地加工机,并在加工机上安装全新地刀具,利用步骤S21-S24,获得一段时间(例如:三分钟)的加工波形图案,并以此加工波形图案为标准波形图案。
然后,再以模糊分析比较的方式,实时地判断加工波形图案与标准波形图案的相似度,若判断二者的相似度未达到标准,则判断加工机的刀具需要更换,或是被加工物的材料有缺陷,因此达到监控加工机状态,并提醒加工业者适时更换刀具或检查加工物的来材料是否有偷工减料的目的。
在一实施例中,使用者可以通过观察加工波形图案的趋势线,依据趋势线的上升斜率判断安装于加工机上的刀具的耐久性。
在一实施例中,使用者亦可通过观察加工波形图案的趋势线,依据峰谷差值的变化判断安装于加工的刀具是否即将损坏,并因此达到预防刀具突发性地断裂。
请参阅图3,其系为第一种加工刀具挑选方法的步骤图,包含:
步骤S31:提供复数刀具;
步骤S32:将其中一个刀具安装于加工机;
步骤S33:利用步骤S21-S24,获得加工波形图案;
步骤S34:重复步骤S33,直到获得所有刀具的加工波形图案;
步骤S35:比较各波形图案,并选择趋势线斜率最低的刀具。
请参阅图4,其系为第一种刀具挑选方法的步骤图,包含:
步骤S41:提供复数刀具;
步骤S42:将其中一个刀具安装于加工机;
步骤S43:利用步骤S21-S24,获得加工波形图案;
步骤S44:重复步骤S43,直到获得所有刀具的加工波形图案;
步骤S45:比较各波形图,并选择峰谷差异最低的刀具。
请参阅图5A至图5C,其系为本发明的第一至第三讯号示意图,如图所示,惯性单元111所侦测的原始惯性讯号4中包含复数振幅值41;
在步骤S21中,用户透过设定接口21设定适当的单位时间长度后,处理单元11将原始讯号4切割成复数个单位时间42;
在步骤S22中,处理单元11将单位时间42内振幅值41的峰值设为值点43;
在步骤S23中,波形模块22将各值点43联机而形成加工波形图案5。
请参阅图6,其系为长期趋势加工波形图案,如图所示,加工波形图案5有X轴趋势线51与Y轴趋势线52,通过观察可发现,不论是X轴趋势线51或Y轴趋势线52的斜率皆大于零,也就是说,加工机的振动会随着时间而增加,因此,使用者可以通过观察趋势线的斜率而判断加工机的耗材的耐用性,其中又以观察加工机刀具的耐用性最为显著。
请参阅图7A及7B,其系为前期加工波形图案及后期加工波形图案,如图7A所示,在加工机及其刀具还在全新的状态时,Y轴趋势线52的峰谷差值不超过2,然而经过15分钟的使用后,如图7B所示,加工机及其刀具有所耗损,因此Y轴趋势线52的峰谷差值趋近于3,且图7B的趋势线比图7A的趋势线更显杂乱,透过上述观察,使用者可以依据加工波形图案的峰谷差值及其杂乱度而判断刀具的耗损率。
进一步说明,使用者可以利用加工高速瞬时监控方法绘制出个刀具的加工波形图案及长期趋势图,然后选择振幅趋势较低且波形图案的峰值最低的刀具,即表示使用该刀具加工,可以得到最低的振动量,也就是有最低的切 削阻力,和最好的切削力表现,以此获得被加工物的表面最细微的切削痕迹,确保加工面的光滑度。
请参阅图8,其系为多刀具的加工波形图案,图8绘制了六种刀具在同一台加工机上执行同一加工程序,总共历时16.5分钟的加工波形图案,六种刀具分别为WXS刀具、WXS/DE刀具、SD刀具、SDGH刀具、SDGMR刀具及SDG刀具,使用者可通过比较六种刀具的峰谷差值及趋势线斜率,而挑选最适合此加工机及加工程序的刀具。
承上的挑选刀具的方法,使用者亦可以提供多种润滑油或加工参数,仿造步骤S32-S35或步骤S42-S45,而挑选出最恰当地润滑油或加工参数。
请参阅图9,其系为加工程序示意图,如图所示,加工机持续来回切割块材6的往复动作,我们可以将切割块材6的动作分为入刀71及出刀72二个分解步骤。
请参阅图10,其系为加工波形图案,如图所示,随着加工机的往复动作,加工波形图案5呈现复数个具规律性的波峰及波谷,其中每一回合中,波谷最深的处即为出刀点82,而在入刀点81之后则为出刀点82,换句话说,加工波形图案5是一张连续出现入刀点81及出刀点82的规律图形。
请参阅图11,其系为波形比较示意图,如图所示,若将标准波形图案及加工波形图案迭加,则可以通过比较加工波形图案与标准波形图案的相似度,判断加工机是否依照规律性地出现不同地波峰及波谷,进而判断加工机的状态。
在一实施例中,使用者可以将加工波形图案5中的一个区段设为标准波型图案,再以模糊分析比较的方式,实时地判断加工波形图案与标准波形图案的相似度,若判断二者的相似度未达到标准,则判断加工机的稳定性未达标准。
其中,稳定性可以是检验被加工物的材质特性。
其中,稳定性可以是加工中切削力及润滑油的状态。
其中,稳定性可以是加工刀具的耐久性或耗损率。
请参阅图12,其系为本发明的加工高解析监控方法的步骤图,本发明的加工高解析监控方法包含:
步骤S51:提供时间区间;
步骤S52:提供单位时间,且单位时间低于0.1秒;
步骤S53:侦测加工机的振动而产生原始讯号,原始讯号包含复数振幅值;
步骤S54:将单位时间内的振幅值的峰值设为单位时间的值点;
步骤S55:每间隔该时间区间,将时间区内的值点设成一组,并统计各组的值点而获得统计指标;
步骤S56:比较各组与其前一组的统计指标,而获得统计指标的变化值,
步骤S57:观察变化值,且当变化超过阈值时,判断加工机的稳定性不佳。
其中,统计指标为最大值、最小值、平均值、中位数或标准偏差的其中之一,阈值为15%。
在一实施例中,步骤S21-S24及步骤S51-S57可以同时运行,因此增加本发明判断加工机稳定性的能力。
总上所述,本发明的加工机高解析监控系统通过微机电组件获得加工机振动的高分辨率讯号,并利用具有高解析传输速度的通讯组件将讯号快速且实时地传输至分析装置,再由分析装置会制出高分辨率地加工波形图案,或是对讯号进行统计。
此外,本发明更提供多种加工波形图案的应用方法,通过加工波形图案所提供的高分辨率信息,本领域具有通常知识者可以判断加工机的状态、刀具的状态或是被加工物的质量。
换句话说,本发明提供使用者一种加工机台的实时状态的分析解决方案,协助使用者进行加工条件的优化,并给予实时地回馈,使用者可以依据加工波形图案的再现性、振动峰值的整体趋势线斜率、波形图案的变形方式及峰谷差值判断加工的状态。
据上论结,本发明利用加速规的量测的时域讯号,经分析装置的高解析处理,绘制成可以反应加工机状态的高分辨率加工波形图案,相较于本领域的先前技术采用的频域分析还来得简单、实时、精准且更具泛用性。甚至图案未来可以采用模糊分析比较或是AI比对的方式做机台加工时候的反馈确认。
除此之外,本领域通常知识者普遍认为,时域讯号杂乱不勘,无法代表加工机的状态,故本发明的另一目的在于破除技术偏见,提出另一种分析加工机状态的可行方案。
上列详细说明系针对本发明的可行实施例的具体说明,惟实施例并非用以限制本创作的专利范围,凡未脱离本发明技艺精神所为的等效实施或变更,均应包含于本案的专利范围中。
Claims (13)
- 一种加工机高解析监控系统,其特征在于,包含:一微机电组件,更包含:一惯性单元,系用于侦测一加工机的振动而产生原始讯号,该原始讯号包含复数振幅值;一处理单元,与该惯性单元连接,系用于将一单位时间内的该振幅值的峰值设为该单位时间的值点;一分析装置,与该微机电组件连接,该分析装置更包含:一设定接口,系用于设定该单位时间,该单位时间低于0.25秒;一波形模块,与该分析装置连接,系用于将各该值点依时序绘制成加工波形图案;其中,该微电机组件与该分析装置之间的传输周期低于0.25秒:其中,该振动系因该加工机的加工动作而产生。
- 如权利要求1所述的加工机高解析监控系统,其特征在于,更包含一通讯组件,系用于将该微机电元接件连接至该分析装置,并以低于0.25秒的传输周期,将该值点传输至该分析装置。
- 如权利要求1所述的加工机高解析监控系统,其特征在于,其中该分析装置更包一比对模块,系用于判断一标准波形图案与该加工波形图案的相似度。
- 如权利要求1所述的加工机高解析监控系统,其特征在于,其中该通讯组件的传输周期介于0.02秒至0.25秒,且该单位时间介于0.02秒至0.25秒。
- 一种加工机高解析监控方法,其特征在于,包含:提供一单位时间,且该单位时间低于0.25秒;侦测一加工机的振动而产生原始讯号,该原始讯号包含复数振幅值;将该单位时间内的该振幅值的峰值设为该单位时间的值点;将各该值点依时序绘制成加工波形图案;其中,该振动系因加工机的加工动作而产生。
- 如权利要求5所述的加工机高解析监控方法,其特征在于,其中该单位时间介于0.02秒至0.25秒。
- 如权利要求5所述的加工机高解析监控方法,其特征在于,更包含判断一标准波形图案与该加工波形图案的相似度,并以该相似度判断加工的稳定性。
- 如权利要求5所述的加工机高解析监控方法,其特征在于,更包含依据该加工波形图案的趋势线斜率,判断该加工的稳定性。
- 如权利要求5所述的加工机高解析监控方法,其特征在于,更包含依据该加工波形图案的峰谷差值,判断该加工的稳定性。
- 如权利要求7至9中任一项所述的加工机高速高解析监控方法,其特征在于,其中该稳定性为加工刀的耐久性或加工刀的耗损率。
- 如权利要求7至9中任一项所述的加工机高速高解析监控方法,其特征在于,其中该稳定性为加工中切削力或润滑油的状态。
- 一种加工机高解析监控方法,其特征在于,包含:提供一时间区间;提供一单位时间,且该单位时间低于0.25秒;侦测一加工机的振动而产生原始讯号,该原始讯号包含复数振幅值;将该单位时间内的该振幅值的峰值设为该单位时间的值点;每间隔该时间区间,统计各该时间区间内的值点,并产生一统计指标;计算各该统计指标与其前一个该统计指标之间的变化率;当该变化率超过一阈值时,判断该加工机的稳定性异常。
- 如权利要求12所述的加工机高解析监控方法,其特征在于,其中该统计指标为最大值、最小值、平均值、中位数或标准偏差的其中之一。
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Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN1352586A (zh) * | 1999-05-27 | 2002-06-05 | 三洋电机株式会社 | 检测切削工具异常的装置及其方法 |
JP2008087093A (ja) * | 2006-09-29 | 2008-04-17 | Matsushita Electric Works Ltd | 工作機械の異常検出装置 |
JP2010048758A (ja) * | 2008-08-25 | 2010-03-04 | Jfe Mechanical Co Ltd | 装置の異常診断装置 |
CN102179728A (zh) * | 2011-03-14 | 2011-09-14 | 上海师范大学 | 一种数控刀具磨损智能检测装置 |
CN103760820A (zh) * | 2014-02-15 | 2014-04-30 | 华中科技大学 | 数控铣床加工过程状态信息评价装置 |
CN109732405A (zh) * | 2018-12-30 | 2019-05-10 | 深圳市五湖智联实业有限公司 | 一种数控机床刀具边元计算磨损监测控制系统及方法 |
CN109909804A (zh) * | 2018-12-21 | 2019-06-21 | 北京工业大学 | 基于主轴驱动电流和工步的刀具磨损破损在线监测方法 |
CN110587377A (zh) * | 2019-09-03 | 2019-12-20 | 重庆大学 | 一种在线监测铣削加工刀具缺损的方法 |
-
2021
- 2021-11-24 WO PCT/CN2021/132611 patent/WO2023092311A1/zh unknown
Patent Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN1352586A (zh) * | 1999-05-27 | 2002-06-05 | 三洋电机株式会社 | 检测切削工具异常的装置及其方法 |
JP2008087093A (ja) * | 2006-09-29 | 2008-04-17 | Matsushita Electric Works Ltd | 工作機械の異常検出装置 |
JP2010048758A (ja) * | 2008-08-25 | 2010-03-04 | Jfe Mechanical Co Ltd | 装置の異常診断装置 |
CN102179728A (zh) * | 2011-03-14 | 2011-09-14 | 上海师范大学 | 一种数控刀具磨损智能检测装置 |
CN103760820A (zh) * | 2014-02-15 | 2014-04-30 | 华中科技大学 | 数控铣床加工过程状态信息评价装置 |
CN109909804A (zh) * | 2018-12-21 | 2019-06-21 | 北京工业大学 | 基于主轴驱动电流和工步的刀具磨损破损在线监测方法 |
CN109732405A (zh) * | 2018-12-30 | 2019-05-10 | 深圳市五湖智联实业有限公司 | 一种数控机床刀具边元计算磨损监测控制系统及方法 |
CN110587377A (zh) * | 2019-09-03 | 2019-12-20 | 重庆大学 | 一种在线监测铣削加工刀具缺损的方法 |
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