applied sciences Article
Development of Dual-Axis MEMS Accelerometers for Machine Tools Vibration Monitoring Chih-Yung Huang * and Jian-Hao Chen Department of Mechanical Engineering, National Chin-Yi University of Technology, Taichung 41170, Taiwan;
[email protected] * Correspondence:
[email protected]; Tel.: +886-4-2392-4505 (ext. 6703); Fax: +886-4-2393-0681 Academic Editor: César M. A. Vasques Received: 30 April 2016; Accepted: 27 June 2016; Published: 12 July 2016
Abstract: With the development of intelligent machine tools, monitoring the vibration by the accelerometer is an important issue. Accelerometers used for measuring vibration signals during milling processes require the characteristics of high sensitivity, high resolution, and high bandwidth. A commonly used accelerometer is the lead zirconate titanate (PZT) type; however, integrating it into intelligent modules is excessively expensive and difficult. Therefore, the micro electro mechanical systems (MEMS) accelerometer is an alternative with the advantages of lower price and superior integration. In the present study, we integrated two MEMS accelerometer chips into a low-pass filter and housing to develop a low-cost dual-axis accelerometer with a bandwidth of 5 kHz and a full scale range of ˘50 g for measuring machine tool vibration. In addition, a platform for measuring the linearity, cross-axis sensitivity and frequency response of the MEMS accelerometer by using the back-to-back calibration method was also developed. Finally, cutting experiments with steady and chatter cutting were performed to verify the results of comparing the MEMS accelerometer with the PZT accelerometer in the time and frequency domains. The results demonstrated that the dual-axis MEMS accelerometer is suitable for monitoring the vibration of machine tools at low cost. Keywords: Dual-Axis micro electro mechanical systems (MEMS) accelerometer; low cost; vibration of machine tool
1. Introduction With the trend of industry 4.0 and intelligent production, many experts have devoted efforts to incorporate intelligent technology into machine tools [1–8]. The core technology of intelligent machine tools can detect temperature, vibration, and displacement, and can be controlled and compensated through algorithms for enhancing the processing performance [9,10]. Therefore, numerous additional sensors are necessary to provide real-time measurement while minimally increasing costs [11–14]. In particular, lead zirconate titanate (PZT)-type accelerometers are regularly used to monitor the vibration and chatter during cutting processes, thereby satisfying the specifications of a 5 kHz bandwidth and a full-scale range of ˘40 g. However, such accelerometers are too expensive ($500–$1000) to integrate into intelligent modules. By contrast, micro electro mechanical systems (MEMS)-type accelerometers are less expensive but typically exhibit the disadvantages of high noise and a low bandwidth [15]. With the upgrading of MEMS technology, the aforementioned disadvantages can be improved through advanced design and process methods. In this study, a differential capacitance ADXL001 MEMS accelerometer (Analog Devices, Inc., Norwood, MA, USA) was used. This accelerometer has a bandwidth of 22 kHz, a full-scale range of ˘70 g, and a sensitivity of 24.2 mV/g, thereby providing a fully differential sensor structure and circuit path for excellent resistance to electromagnetic interference (EMI) and radio frequency interference (RFI). The performance and frequency response are shown in Appl. Sci. 2016, 6, 201; doi:10.3390/app6070201
www.mdpi.com/journal/applsci
Appl. Sci. 2016, 6, 201
2 of 9
interference (EMI) and radio frequency interference (RFI). The performance and frequency response are shown in Figure 1 [16]. Measuring the vibration of machine tools generally requires dual‐axis Appl. Sci. 2016, 6, 201 2 of 9 accelerometers, sufficient rigidity housing, and close adhesion with the machine. Otherwise, the accuracy and effective frequency range of measurement can be compromised. Because an ADXL001 Figure 1is [16]. the vibration of machine tools generally dual-axis accelerometers, accelerometer a Measuring chip form of a uniaxial accelerometer, we requires combined two accelerometers and sufficient rigidity housing, and close adhesion with the machine. Otherwise, the accuracy and effective designed a filter circuit with housing and a fixed magnetic structure to satisfy the measurement frequency range of measurement can be compromised. Because an ADXL001 accelerometer is a requirements. In addition, we also developed a platform for evaluating the sensitivity of the MEMS chip form of a uniaxial accelerometer, we combined two accelerometers and designed a filter circuit accelerometer based on the ISO‐16063‐21 back‐to‐back calibration method [17,18]. After testing the with housing and a fixed magnetic structure to satisfy the measurement requirements. In addition, we also developed a platform for evaluating the sensitivity of the MEMS accelerometer based on sensitivity of the MEMS accelerometer, we designed the package of the MEMS accelerometer and the ISO-16063-21 back-to-back calibration method [17,18]. After testing the sensitivity of the MEMS analyzed the heat and resonance frequency. Finally, a milling experiment was performed to verify accelerometer, we designed the package of the MEMS accelerometer and analyzed the heat and the results of comparing the MEMS accelerometer with the PZT accelerometer in the time and resonance frequency. Finally, a milling experiment was performed to verify the results of comparing frequency domains. the MEMS accelerometer with the PZT accelerometer in the time and frequency domains.
Figure 1. The frequency response of the ADXL001 sensor [16]. Figure 1. The frequency response of the ADXL001 sensor [16]. 2. Development of Dual-Axis Micro Electro Mechanical Systems (MEMS) Accelerometers 2. Development of Dual‐Axis Micro Electro Mechanical Systems (MEMS) Accelerometers 2.1. Low-Pass Filter Circuit
2.1. Low‐Pass Filter Circuit
Vibration signals greater than 5 kHz are regarded as noise during the cutting processes of machine
Vibration signals than kHz are regarded as noise during the cutting processes of tools. Because thegreater bandwidth of 5 the ADXL001 accelerometer is 22 kHz, we designed a passive low-pass resistor–capacitor (RC) obtain an effective measurement signal. Thewe values machine first-order tools. Because the bandwidth of filter the to ADXL001 accelerometer is 22 kHz, designed a of R and C are evaluated using Equation (1): passive first‐order low‐pass resistor–capacitor (RC) filter to obtain an effective measurement signal. The values of R and C are evaluated using Equation (1): 2π f 0 “ 1{RC (1) 2π
1⁄
(1)
where f 0 : cut-off frequency = 5 kHz; in this case, C = 20 nF, R = 1.6 kΩ. The design of the circuit layout the related components were mounted on a printed circuit board (PCB) (15 mm ˆ 15 mm), as where f0and : cut‐off frequency = 5 kHz; in this case, C = 20 nF, R = 1.6 kΩ. The design of the circuit layout shown in Figure 2.
and the related components were mounted on a printed circuit board (PCB) (15 mm × 15 mm), as shown in Figure 2.
Appl. Sci. 2016, 6, 201
3 of 9
Appl. Sci. 2016, 6, 201
3 of 9
Appl. Sci. 2016, 6, 201
3 of 9
Figure 2. The circuit layout of the low‐pass filter. DNC: Do Not Connect; ST: Self Test. Figure 2. The circuit layout of the low-pass filter. DNC: Do Not Connect; ST: Self Test.
2.2. Housing and Fixed Magnetic Structure 2.2. Housing and Fixed Magnetic Structure Figure 2. The circuit layout of the low‐pass filter. DNC: Do Not Connect; ST: Self Test. The housing design should be small, lightweight, and structurally rigid. Moreover, the sensitive The2.2. Housing and Fixed Magnetic Structure housing design should be small, lightweight, and structurally rigid. Moreover, the sensitive axis of the ADXL001 accelerometer is perpendicular to the surface of the spindle. Therefore, we axis of the ADXL001 accelerometer is perpendicular to the surface of the spindle. Therefore, we utilized AL7075 materials to design housing that was internally rectangular but externally cylindrical The housing design should be small, lightweight, and structurally rigid. Moreover, the sensitive utilizedaxis AL7075 materials to design housing that was internally rectangular but externally cylindrical of the ADXL001 accelerometer is perpendicular to the surface of the spindle. Therefore, we (φ20 mm × H30 mm). The geometric design and dimension of the accelerometer housing are shown (ϕ20 mm ˆ H30 mm). The geometric design and dimension of the accelerometer housing are shown utilized AL7075 materials to design housing that was internally rectangular but externally cylindrical in Figure 3a. In the process of assembly, the ADXL001 was attached on each side of the rectangular in Figure 3a. In the process of assembly, the ADXL001 was attached on each side of the rectangular (φ20 mm × H30 mm). The geometric design and dimension of the accelerometer housing are shown structure, which is sensitive to vibration on both the x‐ and y‐axes, as shown in Figure 3b. in Figure 3a. In the process of assembly, the ADXL001 was attached on each side of the rectangular structure, which is sensitive to vibration on both the x- and y-axes, as shown in Figure 3b. The fixed condition between the accelerometer and the machine affects the effective frequency structure, which is sensitive to vibration on both the x‐ and y‐axes, as shown in Figure 3b. The fixed condition between the accelerometer and the machine affects the effective frequency range of measurement. For close adhesion with the machine, we utilized a magnetic structure on the The fixed condition between the accelerometer and the machine affects the effective frequency range of measurement. For close adhesion with the machine, we utilized a magnetic structure on the bottom of the housing, as shown in Figure 3c. range of measurement. For close adhesion with the machine, we utilized a magnetic structure on the bottom bottom of the housing, as shown in Figure 3c. of the housing, as shown in Figure 3c.
Figure 3. (a) The geometric design and dimension of the accelerometer housing; (b)The assembly of
Figure 3. (a) The geometric design and dimension of the accelerometer housing; (b) The assembly of the housing and micro electro mechanical systems (MEMS) accelerometer; (c) The structure of fixed the housing and micro electro mechanical systems (MEMS) accelerometer; (c) The structure of fixed magnetic base. Figure 3. (a) The geometric design and dimension of the accelerometer housing; (b)The assembly of magnetic base. the housing and micro electro mechanical systems (MEMS) accelerometer; (c) The structure of fixed 2.3. The Modal Analysis of Housing magnetic base.
The Analysis bottom of housing is set and fixed to disregard the external load. The SolidWorks 2.3. The Modal of the Housing
simulation software (SolidWorks Inc., SolidWorks 2014 SP0, Waltham, MA, USA, 2014) was utilized
2.3. The Modal Analysis of Housing The bottom of the housing is set and fixed to disregard the external load. The SolidWorks to perform the finite element method (FEM) analysis and determine the natural mode shapes and simulation software (SolidWorks Inc., 2014 SP0, MA, USA, 2014) frequencies. results of is model analysis the Waltham, minimum natural frequency was utilized The bottom of The the housing set SolidWorks and fixed revealed to disregard the external load. The was SolidWorks approximately 12.31 kHz, which had a mode shape as shown in Figure 4. An effective vibration signal to perform the finite element method (FEM) analysis and determine the natural mode shapes and simulation software (SolidWorks Inc., SolidWorks 2014 SP0, Waltham, MA, USA, 2014) was utilized of approximately 5 kHz does not disturb the resonance of the housing during the cutting process. frequencies. The results of model analysis revealed the minimum natural frequency was approximately to perform the finite element method (FEM) analysis and determine the natural mode shapes and 12.31 kHz, which a mode as shown in Figure 4. Anthe effective vibration signal of approximately frequencies. The had results of shape model analysis revealed minimum natural frequency was 5 kHz does not disturb the resonance of the housing during the cutting process. approximately 12.31 kHz, which had a mode shape as shown in Figure 4. An effective vibration signal of approximately 5 kHz does not disturb the resonance of the housing during the cutting process.
Appl. Sci. 2016, 6, 201 Appl. Sci. 2016, 6, 201
4 of 9 4 of 9
Appl. Sci. 2016, 6, 201
4 of 9
Figure 4. The first resonant frequency is 12.31 kHz and the related mode shape. Figure 4. The first resonant frequency is 12.31 kHz and the related mode shape.
3. Calibration Methods and Performance Testing 3. Calibration Methods and Performance Testing 3.1. Back‐to‐Back Calibration Method 3.1. Back-to-Back Calibration Method Figure 4. The first resonant frequency is 12.31 kHz and the related mode shape.
According to ISO‐16063‐21 [17], comparison methods typically entail performing back‐to‐back According to ISO-16063-21 [17], comparison methods typically entail performing back-to-back 3. Calibration Methods and Performance Testing measurements according to a reference standard for determining sensitivity, linearity, and frequency measurements according to a reference standard for determining sensitivity, linearity, and frequency Back-to-Back Calibration Method response. MEMS sensor is in response. The The testing testing 3.1. MEMS sensor is mounted mounted in a a back‐to‐back back-to-back arrangement arrangement with with a a standard standard According to ISO-16063-21 [17], comparison methods typically entail performing back-to-back reference PZT accelerometer, as shown in Figure 5. Because the motion inputs are the same for both reference PZT accelerometer, as shown in Figure 5. Because the motion inputs are the same for both measurements according to a reference standard for determining sensitivity, linearity, and frequency devices, the ratio ratio ofof their outputs is also of their sensitivities; the sensitivity of the devices, the their outputs is also thethe ratioratio of their sensitivities; thus, thus, the sensitivity of the MEMS response. The testing MEMS sensor is mounted in a back-to-back arrangement with a standard MEMS accelerometer can be calculated. Both sensors can be mounted on an electrodynamic shaker reference PZT accelerometer, as shown 5. Because thean motion inputs are the sameshaker for both driven accelerometer can be calculated. Both sensors can inbeFigure mounted on electrodynamic devices, the ratio of their outputs is alsothe the ratio of theirrange sensitivities; thus, the sensitivity the driven by sinusoidal vibration sweeping through desired of frequencies, to aofgenerate a by sinusoidal vibration sweeping through the desired range of frequencies, to generate frequency MEMS accelerometer can be calculated. Both sensors can be mounted on an electrodynamic shaker frequency response curve for the MEMS accelerometer. response curve for the MEMS accelerometer. driven by sinusoidal vibration sweeping through the desired range of frequencies, to generate a frequency response curve for the MEMS accelerometer.
Figure 5. The back-to-back calibration method. PZT: lead zirconate titanate; VMEMS: the output voltage
Figure 5. The back-to-back calibration method. zirconate VMEMS : the output voltage of MEMS accelerometer; Vref: the PZT: outputlead voltage of referencetitanate; PZT accelerometer. of MEMS accelerometer; Vref : the output voltage of reference PZT accelerometer. 3.2. Testing of Linearity and Frequency Response
As mentioned in the previous section, the PCB Model 353B15 was used as a standard reference
3.2. Testing of Linearity and Frequency Response PZT accelerometer. The test platform was fixed on the shaker (PCB type: 4810, New York, NY, USA),
which is driven by a function generator (INSTEK AFG-2105, Taipei, Taiwan) and power amplifier
As mentioned in the section, the PCB 353B15 was as standard reference PZT Figure 5. The back‐to‐back calibration method. PZT: lead zirconate titanate; V MEMS : the output voltage (HPprevious MT-1000, Palo Alto, CA, USA). TheModel voltage output signals areused recorded inaLABVIEW auto-sweep programs bywas usingfixed a dataon acquisition card (NI 9234). The linearity and frequency response of thewhich is accelerometer. The test platform the shaker (PCB type: 4810, New York, NY, USA), of MEMS accelerometer; V ref: the output voltage of reference PZT accelerometer. packaged MEMS accelerometer can be measured using the back-to-back calibration system. The
driven by a function generator (INSTEK AFG-2105, Taipei, Taiwan) and power amplifier (HP MT-1000, linearity and cross-axis sensitivity characteristics of the MEMS accelerometer at 500 Hz are shown in 3.2. Testing of Linearity and Frequency Response Palo Alto, CA, USA). The voltage output signals are recorded in LABVIEW auto-sweep programs by usingAs mentioned in the previous section, the PCB Model 353B15 was used as a standard reference a data acquisition card (NI 9234). The linearity and frequency response of the packaged MEMS accelerometer can be measured using the back-to-back calibration system. The linearity and cross-axis PZT accelerometer. The test platform was fixed on the shaker (PCB type: 4810, New York, NY, USA), sensitivity characteristics of the MEMS accelerometer at 500 Hz are shown in Figure 6, where the slope which is driven by a function generator (INSTEK AFG‐2105, Taipei, Taiwan) and power amplifier denotes the measured sensitivity. As shown in Figure 6, the slope is 24.7 mV/g, which is close to the (HP MT‐1000, Palo Alto, CA, USA). The voltage output signals are recorded in LABVIEW auto‐sweep
programs by using a data acquisition card (NI 9234). The linearity and frequency response of the packaged MEMS accelerometer can be measured using the back‐to‐back calibration system. The
Appl. Sci. 2016, 6, 201 Appl. Sci. 2016, 6, 201 Appl. Sci. 2016, 6, 201
5 of 9 5 of 9 5 of 9
Vout(V) Vout(V)
linearity and cross‐axis sensitivity characteristics of the MEMS accelerometer at 500 Hz are shown in linearity and cross‐axis sensitivity characteristics of the MEMS accelerometer at 500 Hz are shown in Figure 6, where the slope denotes the measured sensitivity. As shown in Figure 6, the slope is 24.7 Figure 6, where the slope denotes the measured sensitivity. As shown in Figure 6, the slope is 24.7 sensitivity of the ADXL001 accelerometer, 24.5 mV/g, listed in the data sheet [16], with the maximum mV/g, which is close to the sensitivity of the ADXL001 accelerometer, 24.5 mV/g, listed in the data mV/g, which is close to the sensitivity of the ADXL001 accelerometer, 24.5 mV/g, listed in the data deviation of 0.003. The result of the frequency response is shown in Figure 7. Compared with that in sheet [16], with the maximum deviation of 0.003. The result of the frequency response is shown in sheet [16], with the maximum deviation of 0.003. The result of the frequency response is shown in Figure 1, the frequency response ranging from 10 Hz to 10 kHz is flatter because of the addition of a Figure 7. Compared with that in Figure 1, the frequency response ranging from 10 Hz to 10 kHz is Figure 7. Compared with that in Figure 1, the frequency response ranging from 10 Hz to 10 kHz is low-pass RC filter. flatter because of the addition of a low‐pass RC filter. flatter because of the addition of a low‐pass RC filter. Cross-Axis Sensitivity(500Hz) Cross-Axis Sensitivity(500Hz)
0.26 0.26 0.24 0.24 0.22 0.22 0.2 0.2 0.18 0.18 0.16 0.16 0.14 0.14 0.12 0.12 0.1 0.1 0.08 0.08 0.06 0.06 0.04 0.04 0.02 0.02 0 00 0
2 2
4 4
6 6 Acceleration(g) Acceleration(g)
8 8
10 10
12 12
Figure 6. The linearity character and cross‐axis sensitivity of MEMS accelerometers at 500 Hz. Figure 6. The linearity character and cross-axis sensitivity of MEMS accelerometers at 500 Hz. Figure 6. The linearity character and cross‐axis sensitivity of MEMS accelerometers at 500 Hz.
RESPONSE(dB) (dB) RESPONSE
15 15 12 12 9 9 6 6 3 3 0 0 -3 -3 -6 -6 -9 -9 -12 -12 -15 0 -15 10 0 10
1
10 1 10
2
10 2 10 FREQUENCY (Hz) FREQUENCY (Hz)
3
10 3 10
4
10 4 10
Figure 7. The frequency response of the MEMS accelerometer. Figure 7. The frequency response of the MEMS accelerometer. Figure 7. The frequency response of the MEMS accelerometer.
4. Results and Discussion of the Cutting Experiment 4. Results and Discussion of the Cutting Experiment 4. Results and Discussion of the Cutting Experiment To verify the performance of the MEMS accelerometers, in addition to calibration methods, a To verify the performance of the MEMS accelerometers, in addition to calibration methods, a To verify the performance of the MEMS accelerometers, in addition to calibration methods, a three‐axis milling machine was used to perform the cutting experiment for comparing the differences three‐axis milling machine was used to perform the cutting experiment for comparing the differences three-axis milling machine was used to perform the cutting experiment for comparing the differences between the MEMS‐ and PZT‐type accelerometers. The cutting tool was a four‐flute tungsten steel between the MEMS‐ and PZT‐type accelerometers. The cutting tool was a four‐flute tungsten steel between the MEMSand PZT-type accelerometers. Thewas cutting tool wasof a four-flute tungsten steel end end mill with diameter of 16 mm. The workpiece comprised aluminum alloy 6061. The end mill with diameter of 16 mm. The workpiece was comprised of aluminum alloy 6061. The mill with diameter of 16PZT mm.(PCB The workpiece was comprised of aluminum 6061. The packaged packaged MEMS and 353B15) accelerometers were pasted to alloy the spindle. The output packaged MEMS and PZT (PCB 353B15) accelerometers were pasted to the spindle. The output MEMS and PZT (PCB 353B15) accelerometers were pasted to the spindle. The output signals were signals were recorded in the time and frequency domains by using LABVIEW programs and a data signals were recorded in the time and frequency domains by using LABVIEW programs and a data recorded in the time and frequency domains by using LABVIEW programs and a data acquisition card acquisition card (NI 9234) with a sample rate of 20 kHz. The arrangement of the cutting experiment acquisition card (NI 9234) with a sample rate of 20 kHz. The arrangement of the cutting experiment (NI 9234) a sample ratethe of cutting 20 kHz. experiment, The arrangement the cutting experiment is shown in Figure 8. is shown with in Figure 8. In two of conditions were tested: steady cutting, and is shown in Figure 8. In the cutting experiment, two conditions were tested: steady cutting, and In the cutting experiment, two conditions were tested: steady cutting, and chatter-generated cutting. chatter‐generated cutting. chatter‐generated cutting.
Appl. Sci. 2016, 6, 201 Appl. Sci. 2016, 6, 201
6 of 9 6 of 9
Appl. Sci. 2016, 6, 201
6 of 9
Figure 8. The arrangement of cutting experiment, including the dual‐axis MEMS accelerometer, two Figure 8. The arrangement of cutting experiment, including the dual-axis MEMS accelerometer, two PZT (PCB 353B15) accelerometers, the data acquisition card (NI 9234) and the Labview programs for PZT (PCB 353B15) accelerometers, the data acquisition card (NI 9234) and the Labview programs for signal process. signal process. Figure 8. The arrangement of cutting experiment, including the dual‐axis MEMS accelerometer, two PZT (PCB 353B15) accelerometers, the data acquisition card (NI 9234) and the Labview programs for signal process. The conditions of steady cutting were as follows: rotational speed of 6100 rpm, feed rate of 2400 The conditions of steady cutting were as follows: rotational speed of 6100 rpm, feed rate of mm/min, cutting depth of 10 and tooth‐passing frequency (TPF) of The conditions of steady cutting were as follows: rotational speed of 6100 rpm, feed rate of 2400 2400 mm/min, cutting depth ofmm 10 mm and tooth-passing frequency (TPF)of of406.67 406.67Hz. Hz. The The result result of steady cutting is shown in Figure 9. In the time domain, the real cutting processes started with 5.1 s mm/min, cutting depth of 10 mm and tooth‐passing frequency (TPF) of 406.67 Hz. The result of steady cutting is shown in Figure 9. In the time domain, the real cutting processes started with 5.1 s and steady cutting is shown in Figure 9. In the time domain, the real cutting processes started with 5.1 s and stopped with 11.2 s. The acceleration of the PZT and MEMS accelerometers were shown in Figure stopped with 11.2 s. The acceleration of the PZT and MEMS accelerometers were shown in Figure 9a,b, and stopped with 11.2 s. The acceleration of the PZT and MEMS accelerometers were shown in Figure 9a,b, the average amplitudes of acceleration were approximately 8 g. The results of the and the average amplitudes acceleration were approximately 8 g.8 The results thePZT PZT andPZT MEMS 9a,b, the average of amplitudes of acceleration were approximately g. The results of of the and MEMS accelerometers in the frequency domain were shown in Figure 9c,d. In order to facilitate MEMS in accelerometers in the frequency domain were in shown in Figure In order facilitate observed accelerometers the frequency domain were shown Figure 9c,d. 9c,d. In order to to facilitate observed characteristics, the X‐axes tickets were presented with tooth‐pass frequencies. observed characteristics, the X‐axes tickets and and grids grids were presented with tooth‐pass frequencies. characteristics, the X-axes tickets and grids were presented with tooth-pass frequencies. The PZT and The PZT and MEMS accelerometers produced the same peak values with matching the tooth‐pass The PZT and MEMS accelerometers produced the same peak values with matching the tooth‐pass MEMS accelerometers produced the same peak values with matching the tooth-pass frequencies. frequencies. frequencies.
Figure 9. The results of steady cutting process by using PZT and MEMS accelerometers. (a) Time domain response of PZT type; (b) Time domain response of MEMS type; (c) Frequency response of PZT type; (d) Frequency response of MEMS type.
Appl. Sci. 2016, 6, 201 Appl. Sci. 2016, 6, 201
7 of 9 7 of 9
Figure 9. The results of steady cutting process by using PZT and MEMS accelerometers. (a) Time
The conditions of chatter-generated cutting were as followed: rotational speed of 5700 rpm, feed domain response of PZT type; (b) Time domain response of MEMS type; (c) Frequency response of rate of 2280 mm/min, cutting depth of 10 mm and tooth passing frequency of 380 Hz. The result PZT type; (d) Frequency response of MEMS type. of chatter-generated cutting is shown in Figure 10. In the time domain, the real cutting processes The conditions of chatter‐generated cutting were as followed: rotational speed of 5700 rpm, feed started with 8 s, the chatter-generated with 8.2 s, and finished with 14.3 s. The acceleration of the rate of 2280 mm/min, cutting depth of 10 mm and tooth passing frequency of 380 Hz. The result of PZT and MEMS accelerometers was shown in Figure 10a,b. The average amplitudes of acceleration chatter‐generated cutting is shown in Figure 10. In the time domain, the real cutting processes started with 8 s, the chatter‐generated with 8.2 s, and finished with 14.3 s. The acceleration of the PZT and during chatter processes were approximately 19 g, higher than that of the steady cutting. The results was shown Figure 10a,b. The average amplitudes of acceleration during of the PZTMEMS accelerometers and MEMS accelerometers inin the frequency domain were shown in Figure 10c,d; the X-axes chatter processes were approximately 19 g, higher than that of the steady cutting. The results of the tickets and grids were also presented with tooth-pass frequencies. In the frequency domain, the PZT and MEMS accelerometers in the frequency domain were shown in Figure 10c,d; the X‐axes MEMS and PZT accelerometers produced the same peakfrequencies. frequencies. Besides tooth-pass frequencies, tickets and grids were also presented with tooth‐pass In the frequency domain, the MEMS and PZT accelerometers produced the same peak frequencies. Besides tooth‐pass frequencies, chatter frequencies were also monitored. Notably, in the process of chatter-generated cutting, chatter chatter frequencies were also monitored. Notably, in the process of chatter‐generated cutting, chatter frequencies increased as the vibration was raised, not the tooth-pass frequencies. In addition, in this frequencies increased as the vibration was raised, not the tooth‐pass frequencies. In addition, in this case, the detected major frequency of chatter was approximately 2890 Hz. case, the detected major frequency of chatter was approximately 2890 Hz.
Figure 10. The results of chatter cutting process by using PZT and MEMS accelerometers. (a) Time Figure 10.domain response of PZT type; (b) Time domain response of MEMS type; (c) Frequency response of The results of chatter cutting process by using PZT and MEMS accelerometers. (a) Time PZT type (■: the main chatter frequency); (d) Frequency response of MEMS type (■: the main chatter domain response of PZT type; (b) Time domain response of MEMS type; (c) Frequency response frequency).
of PZT type (: the main chatter frequency); (d) Frequency response of MEMS type (: the main chatter frequency). Table 1 is shown to compare the measurements of the cutting experiment according to time and
frequency domain between the PTZ and MEMS accelerometers. As shown in Table 1, the Tablemeasurement values in the time domain of the MEMS accelerometers are larger than those of PZT 1 is shown to compare the measurements of the cutting experiment according to time and accelerometers with a variation of less than 6%. This variation may result from the different frequency attachment location of the spindle. Nonetheless, the peak values in the frequency domain of these domain between the PTZ and MEMS accelerometers. As shown in Table 1, the measurement values in the time domain of the MEMS accelerometers are larger than those of PZT accelerometers two accelerometers are the same.
with a variation of less than 6%. This variation may result from the different attachment location of the spindle. Nonetheless, the peak values in the frequency domain of these two accelerometers are the same. In the above cutting experiment, the performance levels of the MEMS and PZT (PCB 353B15) accelerometers were highly similar in time and frequency response, under steady cutting or chatter. The PCB 353B15 is a uniaxial accelerometer with a bandwidth of 10 kHz, a full-scale range of ˘500 g, a sensitivity of 10.83 mV/g, and a cost of about $800. In general, accelerometers are regularly used to monitor the vibration and chatter during cutting processes, thereby satisfying the specifications of a 5 kHz bandwidth and a full-scale range of ˘40 g. In this study, we developed a dual-axis accelerometer
Appl. Sci. 2016, 6, 201
8 of 9
with a bandwidth of 5 kHz, a full-scale range of ˘50 g, a sensitivity of 24.8 mV/g, and a cost of only about $80. Table 1. The comparison of measurements in time and frequency domain between piezoelectric and MEMS accelerometers in cutting experiment. PZT: lead zirconate titanate; MEMS: micro electro mechanical systems; TPF: tooth-passing frequency. Accelerometers Types and Error
PZT Accelerometers
MEMS Accelerometers
Error
Cutting condition
Steady cutting
Chatter cutting
Steady cutting
Chatter cutting
Steady cutting
Chatter cutting
The root mean square (RMS) of acceleration in Time Domain
2.68 g
9.38 g
2.71 g
9.89 g
1.12%
5.44%
The first four peak values in frequency domain (Hz)
406.6 (TPF) 813.3 (2 ˆ TPF) 1220 (3 ˆ TPF) 2033 (5 ˆ TPF)
380 (TPF) 1140 (3 ˆ TPF) 2890 (chatter) 3270 (chatter)
406.6 (TPF) 813.3 (2 ˆ TPF) 1220 (3 ˆ TPF) 2033 (5 ˆ TPF)
380 (TPF) 1140 (3 ˆ TPF) 2890 (chatter) 3270 (chatter)
0% 0% 0% 0%
0% 0% 0% 0%
5. Conclusions Dual-axis MEMS accelerometers were successfully developed by considering low-pass filter circuits and housing design. The feasibility was validated using calibration and cutting experiments. In the calibration test, the characteristics of linearity, cross-axis sensitivity and frequency response of the MEMS accelerometer were proved to be excellent. In the process of the cutting experiment, the performance levels of the MEMS- and PZT-type accelerometers were highly similar in time and frequency response, under steady cutting or chatter. The advantage of the newly designed dual-axis MEMS accelerometer is the low cost, which is approximately one-tenth of that of the PZT-type accelerometer. In the future, we can integrate MEMS accelerometers and embed a system for implementing a module of online intelligent vibration detection. Acknowledgments: The authors would like to acknowledge the support of FAIR FRIEND ENTERPRISE GROUP, Taiwan. Author Contributions: Chih-Yung Huang contributed to the organization of the research work, including the experimental configuration, compensation module and manuscript preparation. Jian-Hao Chen contributed to the experiment measurements and data analysis. Conflicts of Interest: The authors declare no conflict of interest.
References 1. 2. 3. 4. 5. 6. 7.
Sarhan, A.A.D.; Matsubara, A. Investigation about the characterization of machine tool spindle stiffness for intelligent CNC end milling. Robot. Comput.-Integr. Manuf. 2015, 34, 133–139. [CrossRef] Du, Z.C.; Zhang, S.J.; Hong, M.S. Development of a multi-step measuring method for motion accuracy of NC machine tools based on cross grid encoder. Int. J. Mach. Tools Manuf. 2009, 49, 99–108. [CrossRef] Chen, J.-S. Intelligent machine tool technology. ROC Autom. Technol. Soc. J. 2008, 34, 66–72. Gao, R.; Zhang, L. Micromachined microsensors for manufacturing. IEEE Instrum. Meas. Mag. 2004, 7, 20–26. [CrossRef] Mitsuishi, M.; Warisawa, S.; Hanayama, R. Development of an intelligent high-speed machining center. Ann. CIRP 2001, 50, 275–280. [CrossRef] Vijayaraghavan, A.; Dornfeld, D. Automated energy monitoring of machine tools. CIRP Ann. Manuf. Technol. 2010, 59, 21–24. [CrossRef] Bhattacharyya, K.; Pal, S.K.; Patra, K. Artificial neural network based prediction of drill flank wear from motor current signals. Appl. Soft Comput. 2007, 7, 929–935.
Appl. Sci. 2016, 6, 201
8.
9. 10.
11. 12. 13. 14. 15. 16. 17.
18.
9 of 9
Bhattacharyya, P.; Mukhopadhyay, S.; Sengupta, D. Cutting force-based real-time estimation of tool wear in face milling using a combination of signal processing techniques. Mech. Syst. Signal Process. 2007, 21, 2665–2683. [CrossRef] Ramesh, R.; Mannan, M.A.; Poo, A.N. Error compensation in machine tools—A review part I: Geometric, cutting-force induced and fixture dependent errors. Int. J. Mach. Tools Manuf. 2000, 40, 1235–1256. [CrossRef] Jerard, R.B.; Xu, M.; Fussell, B.K. Cutting Power Model-Sensor Integration for Tool Condition Monitoring. In Proceedings of the International Conference on Smart Machining Systems, NIST, Gaithersburg, MD, USA, 13–15 March 2007. Teti, R.; Jemielniak, K.; O’Donnell, G.; Dornfeld, D. Advanced monitoring of machine operations. CIRP Ann. Manuf. Technol. 2010, 50, 717–739. [CrossRef] Dimla, E.; Dimla, S. Sensor signals for tool-wear monitoring in metal cutting operations—A review of methods. Int. J. Mach.Tools Manuf. 2000, 40, 1073–1098. [CrossRef] Kuljanic, E.; Sortino, M.; Totis, G. Development of an intelligent multisensory chatter detection system in milling. Mech. Syst. Signal Process. 2009, 2, 1704–1718. [CrossRef] Cus, F.; Zuperl, U. Tool cutting force modelling in ball-end milling using multilevel perceptron. J. Mater. Process. Technol. 2004, 153–154, 268–275. Yao, Z.; Mei, D.; Chen, Z. On-line chatter detection and identification based on wavelet and support vector machine. J. Mater. Process. Technol. 2010, 210, 713–719. [CrossRef] Analog Devices. ADXL001 Data Sheet; Analog Devices Inc.: Norwood, MA, USA, 2008. ISO 16063-21, Methods for the Calibration of Vibration and Shock Transducers-Part 21: Vibration Calibration by Comparison to a Reference Transducer. Available online: http://www.iso.org/iso/iso_catalogue/ catalogue_tc/catalogue_detail.htm?csnumber=27053 (accessed on 7 July 2016). ISO 16063-1, Methods for the Calibration of Vibration and Shock Transducers, Part 1: Basic Concepts. Available online: http://www.iso.org/iso/catalogue_detail.htm?csnumber=25043 (accessed on 7 July 2016). © 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
