Vibration Test and Analysis of a Working Tunnel Boring Machine (TBM) in Underground Mine

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1 rd International Conference on Engineering Technology and Application (ICETA 2016) ISBN: Vibration Test and Analysis of a Working Tunnel Boring Machine (TBM) in Underground Mine Yang Yang School of Mechanical Electronic & Information Engineering, China University of Mining and Technology, Beijing, China Shijiazhuang Coal Mining Machinery Co., Ltd., Shijiazhuang, Hebei, China Yuanyuan Qu*, Xiushan Tang, Yang Chu & Miao Wu School of Mechanical Electronic & Information Engineering, China University of Mining and Technology, Beijing, China ABSTRACT: For mechanical equipment including the tunnel boring machine (TBM), vibration analysis is one of the mainstream methods to release its working properties, to study its reliability, and hopefully to optimize the design of its structure. Vibration test of a working TMB in underground mine was carried out and introduced briefly, followed by explanation of the vibration strength and the frequency structure of the vibration at different critical components of the machine, i.e., the cutting arm and its supporting turntable. Furthermore, based on time-frequency analysis of the signals, several typical instantaneous frequencies are picked out beyond the theoretical operation frequencies of the machine. These highlighted frequencies are treated as special instantaneous response frequencies and are expected to be used in the research on the impact workload over the components, as well as to research on the operational vibration modal identification of the critical components of TBM. Keywords: tunnel boring machine; vibration test and analysis; instantaneous response frequency; workload; operational vibration modal identification 1 INTRODUCTION Tunnel boring machine (TBM) is one of the indispensable mechanical equipment in complex coal lane driving underground. The development of complex driving technique in Chinese mining industry increasingly demands high efficiency and reliability on TBMs (Hou, 2008, Yang & Ji, 2014) while the healthy dynamic features, specifically vibration characteristics during operation, always attract people s attention to monitor and even improve the TBMs performance. It is valuable in engineering to test and analysis the vibration signals of a working TBM: First of all, there apparently exist many mechanical failures because of vibration. To name two: 1) the vibration stimulated by the instantaneous tremendous oil pressure inside the hydraulic cylinder brings the risk of oil leakage; 2) the connection between pins and *Corresponding author: quyuanyuan2014@cumtb.edu.cn pinholes is losing while the local vibration is intense, which might dismantle small structure units and make them out of use (Hu &Yang, 2015). Vibration monitoring and analysis can help to preview this kind of risk and draw a kind of red line to prevent further damages. Theoretically, vibration analysis is one of the mainstream techniques to detect and diagnose faults of machines (He & Chen 2010). For a TBM underground, except the damage of the picks over the cutting head, there are other invisible failures, like: 1) the pitting on the gears; 2) the damages around the connect areas on both the cutting arm and the turntable that locates between the arm and the body of the machine (Che, 2012). These kinds of damages are crucial faults that lag the progress of complex coal lane driving, resulting to time and economic lost (Lu & Wu, 2000, Zhang, 2012). Researchers never give up figuring out useful regular messages among the vibration signals to diagnose and prevent damages. 710

2 Figure 1. Illustration of the TBM and the test points over the machine. It also has to point out that the vibration mode identification, which is a conventional and useful strategy to study a certain mechanical structure, cannot be conducted without real vibration data (Cao & Zhang, 2014). Last but not least, since the working environment in underground mine lanes is poor and the operation conditions are usually complicated, in addition, with the high electrical explosion proof standards for any equipment underground, the vibration monitoring and acquisition for TBMs, which is an easy job on the ground, becomes difficult underground. There are many vibration acquisitions of TBMs or road-headers working underground, but based on those data, not so many references give further conclusions other than the analysis of vibration strength and its frequency structure (Huang & Wu, 2002, Zhang 2011, Zhao & Tian, 2013). Under the background presented above, our research group designed and carried out several vibration tests of the working TBMs underground. Using the collected vibration signals, this paper analyzed the vibration strength and the frequency structure on different critical components of the machine, which are the cutting arm and its supporting turntable on the main body of the machine. Through applying time-frequency analysis, several typical instantaneous frequencies are highlighted beyond the theoretical operation frequencies of the machine. It is believed that those picked out frequencies could be treated as special instantaneous response frequency against certain load on the components. Discussion are presented at the end to propose the ideas to use these instantaneous response frequencies, together with the subsequent ones by time-frequency analysis over the other huge vibration signals, to research on the impact workload on the components, as well as to research on the operational vibration modal identification of the critical components of TBM. 2 VIBRATION TEST UNDERGROUND The fore-mentioned vibration acquisition was carried out on the complex driving worksite in the underground coal lane which locates in Xingdong and belongs to Jizhong Energy Co., Ltd.. The test object is a working cantilever TBM which composes of cutting arm, loading section, transportation section, main body, walking unit and rear stabilizer. The operations of this TBM are supported by hydraulic system, water spray system, lubrication system and electrical system as well. There are only a few points over the machine could be configured with transducers because of space limitation and for the sake of safety for the sensors. As shown in Figure 1, the chosen locations for vibration acquisitions are: on the middle of the cutting arm (two points for two transducers respectively, marked by 1 and 2 in the figure); around the connecting area between the arm and hydraulic cylinder for arm lifting (on the arm, marked by 3 and 4 in the figure); around the connecting area between the arm and the turntable (on the arm, 5 and 6); around the connecting area between the turntable and hydraulic cylinder for cutting arm lifting (on the turntable, 7 and 8); on the up-top of the turntable (9 and 10); around the connecting area between the turntable and the main body (on the main body, 11 and 12); the main frame of the body (13 and 14); on the electric control case (15,16). The sensors for vibration acquisitions are mainly accelerometers of the same type. A pair of accelerometers sticks orthogonally on each test point, for vertical and horizontal vibration signals of the same phase. The sensitivity of the used accelerometers is 5.1 mv/(m/s 2 ). The data cables are bundled along with the hydraulic pipelines going to the driver cab, and are plugged into the portable vibration recorder, which is specially produced for testing in underground mining by our research group previously, for data acquisition (Yang & Xue, 2013). The recorded data are LSB code of voltage values; it needs to be transformed to acceleration values when used. There are different operations for the TBM, typical ones are drilling and cutting. When drilling, the TBM is also drawn forward by caterpillar during the rotation of the cutting head. When cutting, the arm also sways left and right, or up and down, by the turntable, as the cutting head is rotating. 3 VIBRATION DATA ANALYSIS In the test, the monitor was sustained as long as possible, to obtain as much data that involve different operations (empty loading, drilling, cutting) of the machine. 711

3 Figure 2 illustrates three pieces of vibration lasting around 20s respectively, from the same accelerometer on test point No. 4 as marked in Figure 1. the vibration in general. It also shows that the dominant frequencies contained in different pieces of vibrations on the same test point are almost the same. Figure 3. The frequency spectrum of the vibration that shown in Figure 2. Figure 2. The varying data from the same accelerometer on the test point No. 4 in Figure Vibration intensity The vibration intensity is inspected counting the amplitude of the accelerations along the time label. The data are divided into two groups, one for the cutting arm (represented by the test point No.4) and one for the turntable (represented by the test point No. 6). Each group considered three different operations of the machine, like rotating under empty load, drilling, and cutting. (1) The acceleration amplitude from the cutting arm is higher than that from the turntable, since the arm bears the impact load directly from the cutting head, and the work situation of the arm is similar with the model of beam cantilever, of which the vibration amplitude is much obvious compared to mass construction on ground. (2) The variance of the acceleration from turntable is higher than that form the arm. It indicates that the force on turntable owns higher volatility globally. It is reasonable if we look at the position and function of the turntable: it is mounted on the main body to support and control the whole cutting arm by two pairs of hydraulic cylinders; it bears forces from two sides. Consequently, the inner stress of turntable varies complicatedly. (3) The acceleration amplitude when drilling is much higher than the other operation conditions. Probably it is because during drilling, the machine is also moving forward, with both the front ramp plate and the rear supporting section suspend all the time. 3.2 Frequency structure To figure out the frequency structure of the collected vibration, and to avoid frequency information missing, the data in time domain were transformed into frequency domain without noise-reduction. Take the three pieces of vibration presented in Figure 2 for example, Figure 3 shows the frequency structure of The dominant frequencies in Figure 3 are listed as following: 23.87Hz, 122.4Hz, 377.5Hz, 573.6Hz, 751.8Hz, and 1220Hz. To figure out if the vibration signals from other test point contain the similar dominant frequencies over the time, Figure 4 presents the frequency spectrum of another three pieces of signals from test point No. 10 (on the turntable). It is obvious that the dominant frequencies in Figure 4 are 13.09Hz, 27.03Hz, 102Hz, 375.9Hz, 574.7Hz, 751.9Hz, 1221Hz, and 1787Hz, most of which are close to the dominant ones shown in Figure 3. The visible difference between two figures is the frequency spectrum distribution. Figure 4. The frequency spectrum of the vibration around test point No.8. Test point No. 4 is on the cutting arm, where the unpredictable impact load on the cutting head might stimulate abundant response frequencies on the arm. Therefore, the frequency spectrum distribution corresponding to the frequencies other than those dominant ones are even. Differently, the frequency spectrum distribution corresponding to the frequencies other than the dominant ones in Figure4 focused under 500Hz over the time. According to the analysis of the source of those dominant frequencies, it is necessary to have a look at the operating frequencies. The motor in the body of TBM under test has a rated high rotation speed at 1483 r/min and a rated low speed at 733r/min. The rotation transmission is executed by the gearbox with two grades. The related parameters are presented in Table 1. Since the TBM was working on high speed most of the time, the possible theoretical operating frequencies might be included in the vibration are estimated as 712

4 Table 1. The may concerned parameters about the gearbox on the TBM. Parameters The 1st grade gear set The 2nd grade gear set Sun gear Planetary gear Ring gear Sun gear Planetary gear Ring gear Modulu Number of teeth Reduction ratio 1/ /4.259 Rotation speed 1483 / / 0 Rotation freq / / 0 Meshing freq Rated input Rotation speed 1483/733 r/min Rotation freq /12.22 Hz Output Rotation speed 47.8/23.6 r/min Rotation freq. 0.80/0.39 Hz follow: the rotation frequencies 0.80Hz, 3.39Hz, 24.72Hz, meshing frequencies 92Hz, 346Hz; as well as the mixing and multiplying of them. For example, the dominant frequency 23.87Hz (or 27.03Hz) in Figure 3 and 4 may correspond to the rotation frequency 24.72Hz; 102Hz, may to be the theoretical meshing frequency 92Hz; 375.9Hz, may to be the theoretical meshing frequency 346Hz; 751.9Hz, may to be the double of 346Hz. It is a little far-fetched to relate 1221Hz to the triple of 346Hz. We infer that the high dominant frequency may be produced by the special arrangement of picks on the cutting head. There are totally 38 picks lacing along 3 main spirals over the surface of the cutting head, which acts like a gear with 3~4 teeth and results to 3~4 times of the operating frequencies. So far, there is no clear explanation for the emerged dominant frequency 573.6Hz yet. 3.3 Time-frequency analysis Aiming to excavate more information from the collected vibration data, a nature choice is to apply time-frequency analysis over the pieces of vibration signal. Short Time Fourier Transform (STFT) is a prevailing time-frequency analysis method (He & Chen, 2010), which caters to our purpose to monitor the varying pattern of the instantaneous frequencies of the signal as time goes. Figure 5 plots the STFT results of part of the first piece of vibration signal that is shown in Figure 2. (a) (b) Figure 5. (a) The STFT results of the vibration data during 0~2s; (b) The STFT results of the data during 0~6s. Recall the shape of signal in the first 6s along the top piece of vibration shown in Figure 2, which shows small amplitude (empty load) before 2s, and increasing amplitude (more intense vibration) after 2s. Back to Figure 5(a), all the STFT values at different frequencies except 0.31Hz are even; until at around 1.5s when the STFT values at 28.44Hz, 144.1Hz, 209.7Hz, 375.3Hz, 497.2Hz, 1235Hz are intend to increase slightly. According to the discussion in previous sub-section, 0.31Hz, 28.44Hz, 209.7Hz, 375.3Hz and 1235Hz are related to the operating frequencies of the machine Hz and 497.2Hz are believed to be stimulated by the earlier workload. In addition, the frequency around 375Hz emerges frequently, we infer that it is the actual value of the theoretical operating frequency 346Hz. After 2s, as shown in Figure 5(b), the workload seems to increase and almost allthe STFT values against the frequencies rise up, broken the dominancy of the operating frequencies. It indicates that the structure inside the cover of the cutting arm is complicated; any impact load at any moment may stimulate vibrations at very different frequencies. Notice that there are about three instantaneous frequencies holding bigger STFT values than others: 389.2Hz, 629.8Hz and 767.3Hz. Amongst the three, 389.2Hz is close to the operating frequency 375Hz, while 767.3Hz is close to the doubled of 375Hz, but 629.8Hz shows less connection with any operating frequency. Therefore, we believe 629.8Hz is the 713

5 special instantaneous response frequency of the cutting arm against the impact load at that moment. To make a comparison, Short Time Fourier Transform (STFT) is implemented over the vibration signals from the test point No.8, which locates on the turntable. Similarly, three pieces of vibration signals lasting around 12s respectively are presented in Figure 6(a), and the corresponding STFT values over certain part of the three pieces of data are shown in Figure 6(b), Figure 6(c) and Figure 6(d), respectively. (a) Figure 6 shows that: (1) As time goes, i.e., as the impact load varies, the STFT values is against different frequencies wave obviously. Several instantaneous frequencies outstand by giving absolute larger STFT values over the checking time. (2) The dominant instantaneous frequencies in all the three figures locate in different bands, which is different from the situation in Figure 5(b) that there are no apparent gaps between bands. (3) The mentioned dominant frequency bands are summarized as follow: 0~107Hz (primarily focus on 90Hz~107Hz); 573Hz~577Hz; 1214Hz~ 1224Hz. Except for that, 773.6Hz is also a distinct dominant instantaneous frequency involved in the vibration that presented as the third piece of data in Figure 6(a). (4) 90Hz~107Hz are close to the operating frequency 92Hz; 1214Hz~1224Hz are close to the frequency 1221 Hz, which is believed to be the co-work of operating frequency 375Hz and the special picks lacing over the cutting head. 573Hz~577Hz and 773.6Hz show non-direct relation to any operating frequency, and are considered as the unique instantaneous response frequencies of the turntable against certain impact load at different moments. 4 DISSCUSSION (b) (c) (d) Figure 6. (a) The vibration data from the accelerometer at the test point No.10; (b) The STFT results of the data during2~8s; (c) The STFT results of the data during 4~10s; (d) The STFT results of the data during 6~12s. According to the time-frequency analysis in the previous section, other than the operating frequencies of the machine, several non-ignorable instantaneous frequencies emerge in the collected vibration data as impact load varies during a certain time. For example the 629.8Hz and 767.3Hz for the cutting arm, the 573Hz~577Hz, 773.6Hz for the turntable. Be treated as response frequencies against certain impact load at certain moment, those picked out frequencies are expected to be used in further researches in two aspects: (1) Study on the impact load of the components on the machine Most linear vibration models deal with the relationship between stimulation, system and response. If the system or the transfer function is well hypothesized, theoretically, given any response, the corresponding stimulation could be predicted. For the TBM in this case, if the vibration modal of the critical components like the cutting arm and the turntable are built up by finite element method or experimental model analysis, given any response with certain frequency band and power, the causal impact load at certain position is possible to be figure out approximately. By processing all the collected vibration data and find out a group of response sets, hopefully the workload during the operations can be filed and studied. 714

6 (2) Study on the operational vibration modal identification for the critical components on the machine There are mainly two patterns of vibration modal identification, one is based on processing both the stimulation and the response signals, and the other is based on processing only the response signals (Huang & Wu, 2002). The later pattern is named as the operational vibration modal identification, which is suitable for the cases when the stimulations are hardly to fix and the vibration is a kind of stationary stochastic process. If the workload on the TBM is considered as a stationary stochastic process, then the vibration modal identification for the components on the TBM is belongs to the second pattern. Consequently the popular algorithms for solving the operational vibration modal could be implemented using only the response vibration of the components. The crucial part in operational vibration modal identification is to extract the free vibration response from the collected signals without stimulation information. There are a few references dealing with the operational vibration modal identification for TBMs. Nevertheless, L.C. Freudinger and his group fellow proposed to use Laplace wavelet sets as correlation filters to derive free vibration response from data early in 1998, and this proposal was applied to identify the operational vibration modal of the airfoils (He & Chen, 2010). Qi Keyu and his coworkers applied Empirical Mode Decomposition (EMD) together with correlation filtering using Laplace wavelet sets, figured out the operating vibration modal of the cantilever beam under random stimulations (Qi & Xiang 2007). Those references push the correlation filtering using Laplace wavelet sets in front of us but also explore the disadvantage of this method. Since the Laplace wavelet sets need to be declared by setting a parameter space (usually 3 parameters involved, and therefore a 3-dementional searching space), during correlation filtering, the traversal calculation would be too heavy if it is unable to limit down the parameter space for searching. Well, with the help of those picked response frequencies discussed above, it is possible to reduce the parameter space to 2-dementional in each searching, making this proposal more feasible in the operational vibration modal identification for the critical components on the TBM. In sum, the further work would focus on the two aspects presented above. The conclusion about vibration analysis of the working TBM, as well as the discussions are believed to provide reference material for similar research works. REFERENCES [1] Xiangming Hou The Analysis about the Load on Cutting Head and Vibration of Transverse Roadheader. Huainan: AnHui University of Science and Technology. [2] Zixian Yang, Xiaodong Ji, et al Test and research on vibration characteristics of EBH300(A) roadheader. Applied Mechanics and Materials, 487: [3] Yulong Hu, Yang Yang, Miao Wu Study on vibration intensity distribution of boom-type hard rock roadheader, Industry and Mine Automation, 41(8): [4] Zhengjia He, Jin Chen, Taiyong Wang, Fulei Zhu Theories and Applications of Machinery Fault Diagnostics, Beijing: High Education Press. [5] Xiaohe Che Research on Dynamic Characteristics of Light Roadheader Cutting Unit under Heavy Load. Liaoning Technical University. [6] Dunyong Lu, Miao Wu, Huirong Meng Vibration test and analysis of the roadheader. Coal Mine Machinery, (2): [7] Jianguang Zhang, et.al Experimental study on vibration characteristics of longitudinal boom roadheader. Colliery Mechanical & Electrical Technology, (1): [8] Shuqian Cao, Wende Zhang, Longxiang Xiao Vibration Modal Analysis--Theory, Experiment and Application, Tianjin: Tianjin University Press. [9] Min Huang, Miao Wu, et.al Research on vibration characteristics of horizontal axis tunneller, Chinese Journal of Mechanical Engineering, 38(8): [10] Jianguang Zhang Study on vibration experiment of artificial rock wall cutting with longitudinal shaft type mine roadheader, Coal Science and Technology, (8): [11] Lijuan Zhao, Zhen Tian, et.al Vibration characteristics of a longitudinal roadheader, Journal of Vibration and Shock, 32(11): [12] Jianjian Yang, Guanghui Xue, Guorui Zhao, Miao Wu Research and development on mine intrinsic safe mode vibration sensor, Coal Science and Technology, 41(2): [13] Keyu Qi, Jiawei Xiang, Yanyang Ci, Zhengjia He High precision modal parameter identification based on laplace wavelet correlation filtering, 43(9):

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