Tunnel boring machine jamming monitoring method

Abstract

The invention discloses a method for monitoring blocking of a tunnel boring machine, and relates to the technical field of full-section hard rock tunnel boring machines, and the method is characterized in that the method comprises the steps: installing vibration sensors on the inner surface of a shield and the outer surface of a main beam respectively, installing an industrial personal computer in a TBM control room, and according to vibration signal data collected at the shield and the main beam, determining the blocking of the tunnel boring machine. The vibration signal similarity of the two parts is explained by analyzing the time domain and frequency domain characteristics of the data and the correlation between the Pearson's coefficient and the frequency spectrum coefficient, so that the tunneling state and the jamming position of the TBM are judged, and the target of reducing the jamming risk of the TBM is achieved.

Description

Technical Field

[0001] The invention relates to the technical field of full-section hard rock tunnel boring machines, and more specifically, to a tunnel boring machine jam monitoring method. Background Art

[0002] Tunnel boring machines (TBMs) are gaining more and more attention due to their advantages such as fast construction speed, safety and efficiency, and low density of operators. With the continuous improvement of my country's capabilities in TBM design, research and development, and production, the number of tunnel excavations using full-section rock tunnel boring machines has increased year by year. In recent years, my country's tunnel construction has gradually developed in the direction of special length and deep burial, which has made the TBM method play an important role in such tunnel excavation. However, when TBMs are used to cross deep buried, high ground stress, and soft and broken strata, due to construction factors such as excavation disturbance, the surrounding rock may be significantly deformed, causing the TBM to get stuck. This situation not only threatens the safety of on-site personnel, but may also cause damage to mechanical equipment, thus seriously affecting the construction progress.

[0003] During the shield excavation process of a tunnel boring machine (TBM), shield jamming accidents are the main problem that causes TBM jams. The reason for this frequent occurrence of accidents is that the TBM will disturb the surrounding rock during excavation, causing radial deformations such as local large deformation, creep, and overall convergence of the surrounding rock. If the deformation of the surrounding rock exceeds the over-excavation space reserved during the construction process, the TBM shield will be squeezed by the surrounding rock. This squeezing will increase the frictional resistance of the shield. When the frictional resistance reaches a certain level, it may cause the TBM to jam.

[0004] In order to solve the above problems, a Chinese patent (patent announcement number: CN113008157A) discloses a method for monitoring the inner surface deformation of a tunnel boring machine shield, including: ① marking monitoring points on the inner surface of the shield, which are distributed in multiple groups in the middle and rear part of the shield, each group of monitoring points is arranged circumferentially along the cross section of the shield, and the distribution density of the monitoring points located at the top of the shield is greater than the distribution density of the monitoring points on both sides of the shield; ② installing a group of optical strain gauges at each monitoring point, each group of optical strain gauges includes a first strain gauge arranged along the axial direction of the shield and a second strain gauge arranged along the circumferential direction of the shield; ③ installing a strain data acquisition instrument and a host computer in the shield; ④ installing a data processing machine in the monitoring room at the construction site; ⑤ performing data analysis to infer the magnitude of the force between the surrounding rock and the shield, and predicting the excavation state and jam position of the tunnel boring machine based on this, thereby reducing the risk of jamming.

[0005] The above scheme monitors the deformation of the inner surface of the shield through optical strain gauges, so as to achieve the purpose of predicting the excavation status and jamming position of the TBM and reducing the risk of jamming; however, the method for monitoring the deformation of the inner surface of the tunnel boring machine shield still has some defects: first, the above scheme mainly relies on optical strain gauges to monitor the deformation of the inner surface of the shield, and judges the excavation status by inferring the force between the surrounding rock and the shield. This method mainly monitors the deformation of the shield, and the relationship between deformation and jamming is not always direct, and there may be a risk of misjudgment; second, the above scheme needs to infer the force through data analysis, and indirectly judge the jamming situation based on the force. This process may have a certain delay and requires more complex calculation and analysis processes, and the degree of automation is low. Summary of the invention

[0006] The purpose of the present invention is to provide a tunnel boring machine stuck monitoring method to solve the problems of limitations of monitoring means in the prior art and low real-time performance and automation.

[0007] The above technical objectives of the present invention are achieved through the following technical solutions: A tunnel boring machine jam monitoring method, comprising the following steps:

[0008] S1: Select appropriate monitoring points on the inner surface of the TBM shield and the outer surface of the main beam and mark them;

[0009] S2: Install a vibration sensor at the monitoring point described in step S1, wherein the vibration sensor includes a data acquisition and transmission device;

[0010] S3: The vibration signal data collected in step S2 is transmitted to the industrial computer in the TBM control room, and the vibration signal data in the excavation process is automatically collected and stored in real time;

[0011] S4: Analyze the time domain and frequency domain characteristics and correlation of the vibration signal data obtained in step S3 to determine the excavation status and stuck position of the TBM to reduce the risk of stuck.

[0012] The present invention is further configured as follows: the arrangement of the monitoring points on the shield surface in step S1 is specifically as follows: the monitoring points are arranged circumferentially along the cross-section of the shield, and the number of monitoring points arranged on the top of the shield is greater than the number of monitoring points on both sides of the shield and the bottom of the shield.

[0013] The present invention is further configured as follows: the arrangement of the monitoring points on the outer surface of the main beam in step S1 is specifically as follows: the monitoring points are longitudinally arranged at regular intervals along the outer surface of the TBM main beam.

[0014] The present invention is further configured as follows: the vibration sensor in step S2 is an acceleration vibration sensor.

[0015] By adopting the above technical solution, the present invention can accurately monitor the vibration of key parts of the tunnel boring machine by selecting and marking appropriate monitoring points on the inner surface of the TBM shield and the outer surface of the main beam, and installing acceleration vibration sensors at these points. The optimized layout of the monitoring points, especially the increase of points on the top of the shield, and the strategy of longitudinal layout on the outer surface of the main beam enable the entire monitoring system to capture the vibration changes of the TBM more comprehensively and sensitively, providing high-quality data support for subsequent data analysis, and ensuring the comprehensiveness and representativeness of the data; the present invention also collects vibration signal data in the excavation process in real time through vibration sensors, and transmits it to the industrial computer in the TBM control room by wired or wireless means, ensuring the timeliness and accuracy of the data, and the real-time automated data collection and storage system reduces the need for human intervention and improves the reliability of the data;

[0016] During the analysis phase, the present invention can accurately determine the excavation status and stuck position of the TBM by comprehensively analyzing the time domain and frequency domain characteristics of the vibration signal data and the correlation between the Pearson coefficient and the spectral coefficient, which helps to improve the accuracy of the judgment; and through accurate judgment of the excavation status and stuck position, timely measures can be taken to reduce the risk of the TBM getting stuck during tunnel excavation, thereby improving engineering efficiency and reducing delays and losses caused by stuck machines.

[0017] The present invention is further configured as follows: the specific method for determining the position of the stuck machine in step S4 is to analyze the vibration signal data obtained in step S3, and obtain the vibration signals of the main beam and the shield through time domain signal analysis of mean, standard deviation, root square amplitude, and root mean square, and frequency domain signal analysis of spectrum mean, spectrum variance, spectrum center of gravity, and frequency standard deviation after Fourier transform, and compare the similarities between the two, and judge the excavation status of the TBM, evaluate whether the machine is stuck, and determine the position of the stuck machine based on the correlation results of the Pearson coefficient and the spectrum coefficient, combined with the on-site construction conditions.

[0018] The present invention is further configured as follows: the specific method of the Fourier transform is: sampling the continuous time domain signal to obtain a discrete time domain signal x(n), and then using discrete Fourier transform to convert the discrete time domain signal x(n) into a frequency domain signal f(k), and the specific formula is as follows:

[0019]

[0020] In the above formula, i is an imaginary unit.

[0021] The present invention is further configured as follows: the Pearson coefficient evaluates the correlation of the vibration signals of the main beam and the shield, and the specific formula is as follows:

[0022]

[0023] Cov(X,Y) in the above formula is the covariance of the vibration signals at the monitoring points of the main beam and the shield, σ X , σ Y are the standard deviation of the vibration signals of the main beam and shield, and the Pearson correlation coefficient r pcc The value range is [-1,1].

[0024] The present invention is further configured as follows: the frequency spectrum coefficient evaluates the correlation of the vibration signals of the main beam and the shield, and the specific formula is as follows:

[0025]

[0026] In the above formula are the vibration signal spectrum values ​​at the main beam and shield respectively, is the conjugate complex number of the spectrum value of the vibration signal at the shield, and the spectrum correlation coefficient r scc The value range is [-1,1].

[0027] The present invention is further configured as follows: in step S4, according to the Pearson correlation coefficient r pcc and the spectral correlation coefficient r scc The risk of TBM jamming can be determined by correlation. The specific judgment method is as follows:

[0028] Normal TBM excavation:

[0029] TBM has the risk of jamming:

[0030] TBM has a serious jam:

[0031] By adopting the above technical scheme, the present invention provides a multi-dimensional vibration signal data analysis through a comprehensive analysis of the mean, standard deviation, root square amplitude, root mean square time domain characteristics of the vibration signal and the spectrum mean, spectrum variance, spectrum center of gravity, and frequency standard deviation after Fourier transformation. Such a method can not only capture the overall change trend of the vibration signal, but also deeply understand the change of the frequency component of the signal, and can more accurately identify the vibration signal characteristics of the main beam and the shield; the present invention uses discrete Fourier transform to convert the sampled discrete time domain signal into a frequency domain signal, providing an efficient signal conversion and analysis method. The use of Fourier transform makes the analysis of the frequency component of the vibration signal more intuitive and accurate, thereby better identifying possible abnormal conditions during the excavation process;

[0032] The present invention evaluates the correlation of the vibration signals of the main beam and the shield through the Pearson correlation coefficient and the spectral correlation coefficient, and can effectively quantify the similarity of the vibration signals of the two. The value range of these correlation indicators is clear ([-1,1]), which can intuitively reflect the linear relationship and spectral relationship between the vibration signals, and is helpful to more reliably judge the TBM excavation status and the risk of machine jamming. The present invention compares the similarity of time domain characteristics and spectral characteristics, and combines the correlation of the Pearson coefficient and the spectral coefficient, so as to accurately judge the excavation status, evaluate the risk of machine jamming and determine the location of machine jamming. According to the specific numerical range of the Pearson correlation coefficient and the spectral correlation coefficient, the present invention sets three different risk judgment standards for normal excavation, risk of machine jamming and serious machine jamming, which provides clear judgment basis and operation guidance for on-site construction personnel. This risk level division makes on-site monitoring and emergency decision-making faster and more accurate, reduces human judgment errors, and improves construction safety and efficiency.

[0033] In summary, the present invention has the following beneficial effects:

[0034] The tunnel boring machine stuck monitoring method provided by the present invention comprises the following steps: respectively installing vibration sensors on the inner surface of the shield and the outer surface of the main beam, installing an industrial computer in the TBM control room, and then, based on the vibration signal data collected at the shield and the main beam, analyzing the time domain and frequency domain characteristics of the data and the correlation between the Pearson coefficient and the spectrum coefficient, illustrating the similarity of the vibration signals of the two parts, thereby judging the excavation status and stuck position of the TBM, and achieving the goal of reducing the risk of TBM stuck. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 1 is a vibration signal and correlation coefficient analysis diagram of the TBM top shield and side shield in an embodiment of the present invention;

[0036] Figure 2 Schematic diagram of the layout of vibration signal monitoring points of the TBM main beam and shield in an embodiment of the present invention;

[0037] Figure 3 It is a flow chart of TBM card machine risk determination in an embodiment of the present invention. DETAILED DESCRIPTION

[0038] The following is combined with Figure 1-3 The present invention is described in further detail.

[0039] Embodiment: A method for monitoring a tunnel boring machine jam, comprising the following steps:

[0040] Step S1: Select appropriate vibration monitoring points on the outer surface of the TBM main beam and the inner surface of the shield and mark them.

[0041] The selection of monitoring points is carried out according to the following principles:

[0042] ① The monitoring points should be arranged at locations that do not affect the normal operation of the TBM and should be relatively hidden and not damaged by construction;

[0043] ② In order to accurately collect the vibration signals of each group of monitoring points, it is required that there are no other interference sources on the outer surface of the main beam and the inner surface of the shield near the monitoring points to ensure that the vibration sensor is not affected by factors such as temperature, humidity and electromagnetic interference;

[0044] ③ Since the shield is stuck at the crown and shoulders relatively frequently during TBM excavation, monitoring points should be arranged as much as possible at the crown and left and right shoulders of the upper part of the shield. At the same time, a certain number of monitoring points should also be arranged in the lower part of the shield, and the layout of each group of monitoring points should ensure left-right symmetry about the central axis of the TBM shield cross section.

[0045] Specifically, in the present invention, each group of monitoring points is arranged longitudinally along the cross section of the main beam and circumferentially along the cross section of the shield. The arrangement of the main beam monitoring points and the shield monitoring points is shown in the figure. Figure 2 As shown in the figure, one group of monitoring points on the shield cross section includes a total of 7 vibration monitoring points. Each group of monitoring points is arranged symmetrically about the central axis of the TBM shield cross section, and each group of monitoring points is arranged coaxially with the monitoring points in front of or behind it. Monitoring points ①-⑦ are evenly arranged on the upper semicircle of the shield at an interval of 30°. For TBM shields with extra-large diameters, the number of monitoring points on the shield circumference can be increased according to actual conditions and needs, and each group of monitoring points is arranged coaxially with the monitoring points in front of or behind it.

[0046] Step S2: A group of vibration sensors are arranged at each monitoring point selected in step 1, and each group of vibration sensors is arranged along the longitudinal direction of the main beam and the circumferential direction of the shield.

[0047] The present invention uses an acceleration vibration sensor. The acceleration sensor obtains the vibration characteristics of an object by measuring its acceleration in different directions, and is particularly suitable for vibration monitoring of large mechanical equipment such as TBM. Compared with velocity sensors and displacement sensors, acceleration sensors can more sensitively capture small changes in vibration, and have higher accuracy in identifying the working status of TBM and judging the risk of machine jams.

[0048] Specifically, before installing the vibration sensor, the TBM main beam and shield surface need to be thoroughly cleaned to ensure that the sensor is in close contact with the measured surface and to avoid interference sources that affect the accuracy of the signal. The sensor needs to be inspected in detail before installation to ensure that the appearance is intact, the interface and connecting wires are intact, and the sensitivity and accuracy meet the requirements. During the installation process, the sensor must be firmly fixed in the selected position, and the direction and angle must meet the design requirements to ensure the accuracy and representativeness of the signal acquisition. After the installation is completed, the lines need to be connected correctly to avoid interference and friction. Finally, perform hardware debugging to confirm that the data output is normal, there is no signal interference or loss, and record and confirm all installation and debugging conditions to ensure the normal operation of the system.

[0049] Step 3: Install fixed vibration sensors and supporting data transmission equipment on the outer surface of the TBM main beam and the inner surface of the shield, and install an industrial computer in the TBM control room.

[0050] After vibration sensors are installed on the main beam and shield of the TBM, the collected vibration signals are transmitted to the industrial computer via wired or wireless means to achieve real-time monitoring without human supervision. In this way, the vibration signals of the main beam and shield can be automatically and continuously collected, and the operating status of the TBM can be monitored in real time, and whether a jam will occur can be predicted.

[0051] Specifically, data transmission equipment should be installed in an appropriate location that does not affect the normal construction of the TBM and is easy to maintain. The data transmission equipment should be powered by the TBM's own lighting power supply to ensure that these devices can maintain a stable power supply in harsh construction environments; the signals collected by the vibration sensor are connected to the corresponding data transmission equipment through the data transmission line, and each connection line needs to be clearly marked to ensure that the vibration signal at the monitoring point corresponds to the data acquisition channel one by one to avoid signal confusion or misreading; the signal data collected by the data transmission equipment is transmitted to the industrial computer through the transmission line. During the connection process, it is necessary to ensure that the connection of each line is firm and correct to avoid reverse connection or poor contact; the laying of the data transmission line should avoid the mechanical moving parts of the TBM in operation to avoid line damage or signal interruption due to friction, extrusion, etc.; the layout of the line should be as concealed as possible to prevent accidental contact or damage during construction;

[0052] An industrial computer is installed in the TBM's main control room so that operators can centrally monitor the collection and transmission of vibration signals during construction. The industrial computer should be installed in a convenient location and keep a proper distance from other equipment on the construction site to reduce electromagnetic interference. The industrial computer can remotely control and receive data from vibration sensors and data transmission equipment by connecting to the intranet of the construction site. The intranet connection must ensure the stability and security of data transmission to avoid data loss or external interference.

[0053] Step 4: The collection and monitoring system composed of vibration sensors, data transmission equipment and working condition machines can automatically collect and store the vibration signal data of the main beam and shield in real time.

[0054] After the industrial computer is connected to the construction site intranet, researchers can view the working status of the acquisition and monitoring system through remote operation software.

[0055] Step 5: Researchers can remotely view, download and analyze the collected vibration signal data, and obtain the vibration signals of the main beam and shield through time domain signal analysis of mean, standard deviation, root square amplitude, root mean square, and frequency domain signal analysis of spectrum mean, spectrum variance, spectrum center of gravity, and frequency standard deviation after Fourier transformation, and compare the similarities between the two. Finally, based on the correlation results of the Pearson coefficient and the spectrum coefficient, combined with the on-site construction situation, the excavation status of the TBM is judged, whether the machine is stuck, and the location of the stuck machine is determined.

[0056] Specifically, after the installed vibration sensors collect the acceleration vibration signals on the TBM main beam and shield in the X-axis, Y-axis, and Z-axis directions, in order to simplify data processing and facilitate subsequent analysis, the following formula is used to calculate the acceleration vibration signal synthesized in the X-axis and Y-axis directions. The specific formula is as follows:

[0057]

[0058] Then, the synthesized acceleration vibration signal is transmitted to the industrial computer in the TBM control room through the data transmission equipment. The time domain characteristic index is calculated by combining the vibration signal analysis software on the industrial computer. The specific formula is as follows:

[0059] Maximum value:

[0060] Standard Deviation:

[0061] Square root amplitude:

[0062] RMS:

[0063] Then, the continuous time domain signal is sampled to obtain a discrete time domain signal x(n), and then the discrete time domain signal x(n) is converted into a frequency domain signal f(k) using the discrete Fourier transform (DFT). The specific formula is as follows:

[0064]

[0065] In the above formula, i is an imaginary unit. After the frequency domain signal is converted, the frequency domain characteristic index is calculated by combining the vibration signal analysis software on the industrial computer. The specific formula is as follows:

[0066] Spectral mean:

[0067] Spectral variance:

[0068] Spectrum center of gravity:

[0069] Frequency standard deviation:

[0070] Based on the above time domain characteristic indicators calculated, the Pearson correlation coefficient is used to evaluate the correlation of the vibration signals of the main beam and the shield. The specific formula is as follows:

[0071]

[0072] Cov(X,Y) in the above formula is the covariance of the vibration signals at the monitoring points of the main beam and the shield, σ X , σ Y are the standard deviation of the vibration signals of the main beam and shield, and the Pearson correlation coefficient r pcc The value range is [-1,1].

[0073] Based on the above-mentioned frequency domain characteristic indicators calculated, the spectral correlation coefficient is used to evaluate the correlation of the vibration signals of the main beam and the shield. The specific formula is as follows:

[0074]

[0075] In the above formula are the vibration signal spectrum values ​​at the main beam and shield respectively, is the conjugate complex number of the spectrum value of the vibration signal at the shield, and the spectrum correlation coefficient r scc The value range is [-1,1].

[0076] According to the Pearson correlation coefficient r pcc and the spectral correlation coefficient r scc The correlation between the TBM machine and the risk of machine jam is determined as shown in the attached Figure 3 The specific judgment method is as follows:

[0077] Normal TBM excavation:

[0078] TBM has the risk of jamming:

[0079] TBM has a serious jam:

[0080] The technicians used MATLAB software to extract and process 1000 continuous vibration signals collected from the top shield and side shield of the TBM. Then, based on the vibration signal standard deviation calculation formula and the Pearson correlation coefficient formula, they programmed in MATLAB to calculate the Pearson correlation coefficient of the 1000 continuous vibration signals. Finally, they obtained the correlation change trend of the vibration signals of the top shield and side shield of the TBM. This can be used to determine whether the TBM is stuck and predict its risk of sticking. The Pearson correlation coefficient of the vertical line segment is in the range of (0, 0.7], as shown in the attached figure. Figure 1 As shown, this section is a high-risk area for TBM jam.

[0081] This specific embodiment is merely an explanation of the present invention and is not a limitation of the present invention. After reading this specification, those skilled in the art may make non-creative modifications to the present embodiment as needed. However, as long as they are within the scope of the claims of the present invention, they are protected by the patent law.

Claims

1. A method for monitoring a tunnel boring machine jam, characterized in that: The following steps are involved: S1: Select appropriate monitoring points on the inner surface of the TBM shield and the outer surface of the main beam and mark them; S2: Install a vibration sensor at the monitoring point described in step S1, wherein the vibration sensor includes a data acquisition and transmission device; S3: The vibration signal data collected in step S2 is transmitted to the industrial computer in the TBM control room, and the vibration signal data in the excavation process is automatically collected and stored in real time; S4: Analyze the time domain and frequency domain characteristics and correlation of the vibration signal data obtained in step S3 to determine the excavation status and stuck position of the TBM to reduce the risk of stuck.

2. A tunnel boring machine stuck monitoring method according to claim 1, characterized in that: The arrangement of the monitoring points on the shield surface in step S1 is specifically as follows: the monitoring points are arranged circumferentially along the cross section of the shield, and the number of monitoring points arranged on the top of the shield is greater than the number of monitoring points on both sides of the shield and the bottom of the shield.

3. A tunnel boring machine stuck monitoring method according to claim 1, characterized in that: The arrangement of the monitoring points on the outer surface of the main beam in step S1 is specifically as follows: the monitoring points are longitudinally arranged at regular intervals along the outer surface of the TBM main beam.

4. A tunnel boring machine stuck monitoring method according to claim 1, characterized in that: The vibration sensor in step S2 is an acceleration vibration sensor.

5. A tunnel boring machine stuck monitoring method according to claim 1, characterized in that: The specific method for judging the stuck position in step S4 is to analyze the vibration signal data obtained in step S3, and obtain the vibration signals of the main beam and shield through time domain signal analysis of mean, standard deviation, root amplitude, and root mean square, and frequency domain signal analysis of spectrum mean, spectrum variance, spectrum center of gravity, and frequency standard deviation after Fourier transform, and compare the similarity between the two. Based on the correlation results of the Pearson coefficient and the spectrum coefficient, combined with the on-site construction conditions, the excavation status of the TBM is judged, whether a jam has occurred, and the stuck position is determined.

6. A tunnel boring machine stuck monitoring method according to claim 5, characterized in that: The specific method of the Fourier transform is: sampling the continuous time domain signal to obtain a discrete time domain signal x(n), and then using discrete Fourier transform to convert the discrete time domain signal x(n) into a frequency domain signal f(k). The specific formula is as follows: In the above formula, i is an imaginary unit.

7. A method for monitoring a tunnel boring machine jam according to claim 5, characterized in that: The Pearson coefficient evaluates the correlation of the vibration signals of the main beam and the shield, and the specific formula is as follows: Cov(X,Y) in the above formula is the covariance of the vibration signals at the monitoring points of the main beam and the shield, σ X , σ Y are the standard deviation of the vibration signals of the main beam and shield, and the Pearson correlation coefficient r pcc The value range is [-1,1].

8. A tunnel boring machine stuck monitoring method according to claim 5, characterized in that: The spectral coefficient evaluates the correlation of the vibration signals of the main beam and the shield, and the specific formula is as follows: In the above formula are the vibration signal spectrum values ​​at the main beam and shield respectively, is the conjugate complex number of the spectrum value of the vibration signal at the shield, and the spectrum correlation coefficient r scc The value range is [-1,1].

9. A method for monitoring a tunnel boring machine jam according to claim 5, characterized in that: Step S4 Pearson correlation coefficient r pcc and the spectral correlation coefficient r scc The risk of TBM jamming can be determined by correlation. The specific judgment method is as follows: Normal TBM excavation: TBM has the risk of jamming: TBM has a serious jam:

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