Shield tunneling machine and shield tunneling machine main bearing state monitoring method

Abstract

The invention relates to a shield tunneling machine and a state monitoring method for a main bearing of the shield tunneling machine, and the method comprises the steps: collecting continuous vibration signals of the shield tunneling machine in an operation process, and storing the vibration signals to a dynamic buffer region meeting a preset sampling length according to a first-in first-out principle; calculating a characteristic value according to the vibration signal stored in the dynamic buffer area every first uploading time, and uploading the characteristic value to a monitoring terminal in network connection with the shield tunneling machine; if at least two continuous characteristic values reach the preset alarm values, it is confirmed that the shield tunneling machine is abnormal, vibration signals are continuously collected in the operation process of the shield tunneling machine, calculation and uploading of the characteristic values are periodically conducted, the relation between the characteristic values and the preset alarm values is judged in time, and then the operation state of the shield tunneling machine can be concerned in real time; the state of the shield tunneling machine can be monitored in real time, the problems caused by the fact that vibration signals are not obtained in time and analysis is incomplete are avoided, and the intelligent degree of healthy operation and maintenance of the shield tunneling machine is improved.

Description

Technical Field

[0001] The invention relates to a shield machine and a method for monitoring the status of a main bearing of the shield machine, and belongs to the technical field of shield machine operation and maintenance. Background Art

[0002] The main bearing is the core component of the shield machine's cutter drive system. It has the characteristics of low speed, large load and complex operating conditions. Real-time monitoring of the operating status of the main bearing and correct acquisition of the dynamic operating waveform are important data sources for monitoring and analyzing whether the shield machine has potential faults. Both are of great safety significance to the operation of the shield machine and tunnel construction.

[0003] In the prior art, the traditional sampling method of the main bearing vibration signal is to complete a set of long-period sampling and calculate the vibration value before sending it to the monitoring system. In addition, the main bearing has the characteristic of low operating speed (its speed is usually 1 rpm-3 rpm), which leads to a long sampling time for the vibration signal. For the status monitoring of the main bearing, the real-time monitoring and the user experience are poor. At the same time, it is also impossible to effectively obtain the low-frequency dynamic vibration signal related to the main bearing, which affects the understanding and judgment of the operation status of the shield machine. Summary of the invention

[0004] The purpose of the present invention is to provide a shield machine and a method for monitoring the status of a main bearing of the shield machine, so as to solve the problems of poor real-time status monitoring of the shield machine and incomplete acquisition and analysis of vibration signals.

[0005] To achieve the above object, on the one hand, the present invention proposes a method for monitoring the condition of a main bearing of a shield machine, comprising: Collect continuous vibration signals of the shield machine during operation, and store the vibration signals in a dynamic buffer that meets the preset sampling length according to the first-in-first-out principle; At every first upload time, a characteristic value is calculated according to the vibration signal stored in the dynamic buffer, and the characteristic value is uploaded to a monitoring terminal connected to the shield machine network; If there are at least two consecutive characteristic values ​​that reach the preset alarm value, it is confirmed that the shield machine has an abnormality.

[0006] Furthermore, every second upload time, a vibration waveform is generated according to the vibration signal stored in the dynamic buffer, and uploaded to a monitoring terminal connected to the shield machine network, so that the monitoring terminal can perform remote operation and maintenance, big data collection and analysis, and visualization application according to the vibration waveform; The first upload time is smaller than the second upload time.

[0007] Furthermore, in response to an abnormality of the shield machine, starting from the next time the first upload time is reached, the characteristic value is calculated and the vibration waveform is generated according to the vibration signal stored in the dynamic buffer, and the characteristic value and the vibration waveform are uploaded to the monitoring terminal connected to the shield machine network.

[0008] Furthermore, if the characteristic value calculated by the shield machine that has an abnormality within a preset period reaches a preset alarm value each time the first upload time is reached, uploading of the vibration waveform is stopped.

[0009] Furthermore, the monitoring terminal includes a host monitoring terminal and a remote monitoring terminal, and the characteristic value is uploaded to the host monitoring terminal in the tunnel that establishes a network connection with the shield machine; The vibration waveform is uploaded to a remote monitoring terminal that has a network connection with the shield machine.

[0010] Furthermore, within the second upload time, if there are at least two consecutive characteristic values ​​reaching the preset alarm value, it is confirmed that the shield machine is abnormal.

[0011] Furthermore, a vibration acceleration sensor arranged in the axial direction of the outer ring of the main bearing of the shield machine is used to collect vibration signals.

[0012] Furthermore, the eigenvalues ​​are calculated by the following method: When the first upload time is reached, the stored vibration signal is extracted from the dynamic buffer to generate a target vibration waveform; and the characteristic value is calculated according to the target vibration waveform.

[0013] Furthermore, the characteristic values ​​include: vibration acceleration peak value, acceleration effective value and kurtosis index.

[0014] On the other hand, the present invention further proposes a shield machine, comprising a processor, wherein the processor is used to execute the condition monitoring method of the main bearing of the shield machine as described above.

[0015] The beneficial effects of the present invention are as follows: collecting continuous vibration signals of the shield machine during operation, and storing the vibration signals in a dynamic buffer that meets a preset sampling length according to the first-in-first-out principle; calculating characteristic values ​​according to the vibration signals stored in the dynamic buffer at every first upload time, and uploading the characteristic values ​​to a monitoring terminal connected to the shield machine network; if there are at least two consecutive characteristic values ​​that reach the preset alarm value, it is confirmed that an abnormality has occurred in the shield machine, and vibration signals are continuously collected during the operation of the shield machine, and characteristic values ​​are calculated and uploaded periodically, and the relationship between the characteristic values ​​and the preset alarm values ​​is judged in time, so that the operating status of the shield machine can be paid attention to in real time, and the status of the shield machine can be monitored in real time, avoiding problems caused by untimely acquisition of vibration signals and incomplete analysis, and improving the intelligence level of healthy operation and maintenance of the shield machine. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a control flow chart of vibration signal and vibration waveform sampling in a practical application scenario of a condition monitoring method for a main bearing of a shield machine proposed by the present invention; Figure 2 It is a schematic diagram of signal transmission control of a condition monitoring method for a main bearing of a shield machine proposed by the present invention in an actual application scenario; Figure 3 It is a topological diagram among a main bearing, a vibration acceleration sensor, a dynamic signal collector and a monitoring terminal of a shield machine in an actual application scenario proposed by the present invention. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments.

[0018] The beneficial effects of the present invention are: in order to avoid the problem of uploading vibration signals after collection and untimely collection, during the operation of the shield machine, continuous vibration signals are acquired and stored in real time. At the same time, the vibration signals are analyzed periodically, and the obtained characteristic values ​​are synchronously uploaded to the monitoring terminal, so that the monitoring terminal can monitor the operation of the shield machine in real time, and determine the abnormal state of the shield machine when the characteristic value reaches the preset alarm value.

[0019] Method Example 1: The present invention proposes a method for monitoring the condition of a main bearing of a shield machine, which includes steps S11 to S13, specifically: Step S11, collecting continuous vibration signals of the shield machine during operation, and storing the vibration signals in a dynamic buffer that meets the preset sampling length according to the first-in-first-out principle; it should be noted that the main bearing of the shield machine is usually a rolling bearing with three rows of rollers. When the shield machine is working, it bears a large axial load and is more sensitive to axial vibration. Therefore, a vibration acceleration sensor arranged in the axial direction of the outer ring of the main bearing of the shield machine is used to collect vibration signals. In actual application scenarios, N vibration acceleration sensors will be installed according to monitoring requirements, main bearing shape, shield machine shape, etc.

[0020] The dynamic buffer that meets the preset sampling length means that the dynamic buffer can store vibration signals equal to the sampling length, and the dynamic buffer works in a first-in-first-out manner. For example, if the sampling length is M data points, then the dynamic buffer always guarantees that there are the latest vibration signal data points with a length of M points, so as to prepare for the subsequent steps of extracting the vibration signal.

[0021] Moreover, in actual application, the rotation speed of the cutter head main bearing is about 1 rpm-3 rpm. It is preferred to use a vibration acceleration sensor with a sensitivity of 500mV / g to collect vibration signals, and support long-period sampling. The sampling frequency is preferably set to 256Hz, and when the sampling length is set to 65536 data points, the sampling time is 256 seconds, so as to ensure that when the rotation speed is 1 rpm, each group of dynamic waveforms contains more than 4 rotation cycles of the main bearing; at the same time, the collector for collecting vibration signals supports multi-channel synchronous sampling, and usually each collector can be connected to 8 vibration acceleration sensors.

[0022] A first upload time for extracting vibration signals from a dynamic buffer and calculating characteristic values ​​is preset, and step S12 is executed. At every first upload time, characteristic values ​​are calculated according to the vibration signals stored in the dynamic buffer, and the characteristic values ​​are uploaded to a monitoring terminal connected to the shield machine network. It should be noted that the characteristic values ​​are calculated by the following method: when the first upload time is reached, the stored vibration signals are extracted from the dynamic buffer to generate a target vibration waveform; and according to the target vibration waveform, characteristic values ​​are calculated, wherein the characteristic values ​​include: vibration acceleration peak value, acceleration effective value and kurtosis index; in actual application scenarios, it is preferred to use the MQTT protocol and a data message in JSON format to upload the characteristic values.

[0023] At the same time, because the first upload time may be shorter than the time required to sample M data points, there are some repeated waveforms in the vibration waveform used for the eigenvalue calculated for the i-th time and the vibration waveform used for the (i+1)-th calculation. However, this does not affect the fact that the vibration waveform involved in each calculation is a complete and dynamic vibration waveform formed by the M points in the dynamic buffer starting from the latest moment, so as to ensure the availability and accuracy of the eigenvalue calculation, and realize that in addition to the first set of sampled data, the eigenvalue can be calculated and transmitted in a timely manner at a smaller time interval (the first upload time), so as to ensure the real-time, accuracy and user experience of status monitoring.

[0024] A preset alarm value is preset to determine whether the abnormal characteristic value has been reached, and step S13 is executed. If there are at least two consecutive characteristic values ​​that have reached the preset alarm value, it is confirmed that the shield machine has an abnormality.

[0025] Through the above steps S11 to S13, it is possible to obtain vibration signals in real time, and to perform vibration signal analysis periodically. At the same time, characteristic values ​​obtained by analyzing the vibration signals are uploaded, and each characteristic value is judged, thereby overcoming the shortcomings of being unable to meet real-time requirements and poor main bearing status monitoring.

[0026] Method Example 2: A condition monitoring method for a main bearing of a shield machine provided by the present invention also presets a second upload time for extracting vibration signals from a dynamic buffer and generating a vibration waveform. At every second upload time, a vibration waveform is generated based on the vibration signal stored in the dynamic buffer, and uploaded to a monitoring terminal connected to the shield machine network, so that the monitoring terminal performs remote operation and maintenance, big data collection and analysis, and visualization application based on the vibration waveform; wherein the first upload time is less than the second upload time; and within the second upload time, if there are at least two consecutive characteristic values ​​that reach a preset alarm value, it is confirmed that an abnormality has occurred in the shield machine; in actual application scenarios, it is preferred to use the MQTT protocol and a data message in JSON format to upload the vibration waveform.

[0027] In addition, when uploading data, a dual network port design is adopted, and data can be sent to two host computers at the same time through two network ports. Specifically: the monitoring terminal includes a host monitoring terminal and a remote monitoring terminal, and the characteristic value is uploaded to the host monitoring terminal in the tunnel that has a network connection with the shield machine for on-site monitoring and analysis. The vibration waveform is uploaded to the remote monitoring terminal that has a network connection with the shield machine for remote operation and maintenance, big data mobile phone analysis and visualization applications. At the same time, a strategy of uploading characteristic values ​​and dynamic vibration waveforms separately is adopted. The characteristic value is used for status monitoring and trend prediction, and can be uploaded at a smaller time interval; the vibration waveform is mainly used for vibration analysis and fault diagnosis. The data volume is large, and the network bandwidth and data storage space required are large. It can be performed at a larger time interval to ensure that the shield machine stores waveform standards for determining whether the waveform is normal during normal operation, as well as vibration signals for analyzing and diagnosing whether the alarm continues.

[0028] At the same time, in response to an abnormality of the shield machine, starting from the next time the first upload time is reached, the characteristic value is calculated and the vibration waveform is generated according to the vibration signal stored in the dynamic buffer, and the characteristic value and the vibration waveform are uploaded to the monitoring terminal connected to the shield machine network. If the characteristic value calculated by the shield machine that has an abnormality within the preset period reaches the preset alarm value each time it reaches the first upload time, the uploading of the vibration waveform is stopped (for example, if the characteristic value exceeds the preset alarm value and continues for 3 times, it can be confirmed that there is an abnormality. At this time, in addition to uploading the characteristic value, the vibration dynamic waveform of all measuring points on the main bearing is uploaded at the same time; if it is in an alarm state continuously, after uploading 3 sets of waveforms continuously, the dynamic waveform corresponding to the alarm value will no longer be uploaded when uploading the characteristic value.).

[0029] like Figure 1As shown in the figure, a vibration signal and vibration waveform sampling control flow chart of a shield machine main bearing condition monitoring method proposed by the present invention in an actual application scenario, wherein dynamic signal acquisition: continuous and uninterrupted vibration signal acquisition is performed according to the set sampling parameters such as sampling frequency 256Hz and sampling length 65536 data points. Acquisition data buffer: a first-in-first-out dynamic buffer is opened to temporarily store vibration signals, and 65536 points of data are always stored in the dynamic buffer. Vibration edge calculation: from the start of sampling work when the collector is powered on, a group of waveform data is copied from the dynamic buffer every ∆t (first upload time) time to calculate the characteristic value; the characteristic value includes the vibration acceleration peak value, acceleration effective value, and kurtosis index of each channel; every ∆T (second upload time) time, a group of dynamic waveforms is copied from the dynamic buffer for uploading the vibration waveform; in this way, although a group of vibration waveforms takes 256 seconds, the calculation and uploading of characteristic values ​​can be controlled within a smaller range (such as ∆t=2 seconds), ensuring the real-time monitoring and better user experience.

[0030] Based on the size of the effective value of the vibration acceleration, determine whether the vibration value exceeds the preset alarm value. When it is confirmed that the effective value of the acceleration of any channel exceeds the preset alarm value, in addition to preparing the characteristic value for uploading, vibration waveforms of multiple vibration channels corresponding to the characteristic value are also prepared.

[0031] Method embodiment 3: like Figure 2 As shown in the figure, it is a schematic diagram of signal transmission control of a shield machine main bearing condition monitoring method proposed by the present invention in an actual application scenario, wherein, from the beginning of acquisition, a set of characteristic values ​​is uploaded every ∆t time (i.e., the first upload time, such as ∆t=2 seconds) for condition monitoring and trend analysis; and a set of waveforms is uploaded every ∆T time (i.e., the second upload time, such as ∆T=24 hours). Under the premise of ensuring the real-time monitoring and saving the dynamic waveforms necessary for analysis and diagnosis, the requirements for network transmission bandwidth and storage space are reduced.

[0032] Within the ∆T time interval, if the characteristic value exceeds the alarm value and continues for more than 3 times, it is confirmed that an alarm has occurred; if the vibration characteristic value exceeds the alarm value and continues for less than 3 times, it is considered to be an occasional situation and is not confirmed as an alarm. When an alarm is confirmed, starting from the fourth set of data, the characteristic value and the abnormal data waveform corresponding to the characteristic value are uploaded at the same time, and three sets are uploaded continuously. If it continues to be in an alarm state, the waveform will no longer be uploaded until the ∆T time is up. This setting ensures that there is effective waveform data that can be used for analysis and diagnosis, and does not occupy excessive transmission bandwidth and server storage space.

[0033] If the characteristic value returns to the normal range, the characteristic value and vibration waveform are still transmitted at the ∆t and ∆T time intervals respectively. The vibration waveform under normal conditions is mainly used to determine the signal baseline and for comparative analysis during fault diagnosis.

[0034] Method Example 4: For example, 1) a vibration acceleration sensor is installed in the axial direction of the shield machine main bearing, and the monitoring terminal preferably includes a connection to the host room in the tunnel through the network interface 1, and a connection to the remote data center through the network interface 2; 2) the sampling frequency Fs, sampling length N, characteristic value upload time interval ∆t, dynamic waveform upload time interval ∆T, vibration acceleration alarm threshold Aval, server address and port, etc. are set, where Fs=256Hz, N=65536 data points, ∆t=2 seconds, ∆T=24 hours, Aval=0.5g, etc. The sensor collects and transmits data according to the set configuration. 3) The characteristic value is measured and uploaded at the set time interval ∆t; the dynamic data is uploaded at the set time interval ∆T. 4) The collected vibration signal is transmitted to the host room in the tunnel through the network interface 1; if the external network access conditions are met, it is uploaded to the remote data center through the network interface 2.

[0035] Shield machine example: The present invention also proposes a shield machine, which includes a processor, wherein the processor is used to execute the above-mentioned shield machine main bearing status monitoring method, wherein in an actual application scenario, the shield machine is installed with multiple vibration acceleration sensors and dynamic signal collectors.

[0036] like Figure 3 As shown, it is a topological diagram among the main bearing, vibration acceleration sensor, dynamic signal collector and monitoring terminal of a shield machine proposed by the present invention in an actual application scenario, wherein six vibration acceleration sensors are installed in the axial direction of the outer ring of the main bearing, specifically, six vibration acceleration sensors are installed at six positions of 1 o'clock, 3 o'clock, 5 o'clock, 7 o'clock, 9 o'clock and 11 o'clock; the vibration signals sensed by the six vibration acceleration sensors are connected to the dynamic signal collector, wherein the dynamic signal collector can synchronously collect multiple vibration signals for feature calculation and comparative analysis, and at the same time, the collector also uploads data through the network interface, and the collector has two network interfaces, which can be connected to the host room in the tunnel and the remote data center at the same time.

[0037] In summary, by setting two independent threads, edge feature calculation can be performed synchronously while collecting dynamic signals. The edge calculation and sampling transmission control method can not only collect the long-period waveform signals required for calculating the characteristic values, but also realize the requirements of real-time status monitoring. The collected data are sent to the industrial computer in the main engine room in the tunnel and the remote data center through the network interface respectively. The requirements of signal analysis integrity and status monitoring real-time are taken into account, thereby improving the intelligence level of healthy operation and maintenance of the main bearing of the shield machine.

Claims

1. A method for monitoring the condition of a main bearing of a shield machine, characterized in that: include: Collect continuous vibration signals of the shield machine during operation, and store the vibration signals in a dynamic buffer that meets the preset sampling length according to the first-in-first-out principle; At every first upload time, a characteristic value is calculated according to the vibration signal stored in the dynamic buffer, and the characteristic value is uploaded to a monitoring terminal connected to the shield machine network; If there are at least two consecutive characteristic values ​​that reach the preset alarm value, it is confirmed that the shield machine has an abnormality.

2. The method for monitoring the condition of the main bearing of a shield machine according to claim 1, characterized in that: Every second upload time, a vibration waveform is also generated based on the vibration signal stored in the dynamic buffer and uploaded to a monitoring terminal connected to the shield machine network, so that the monitoring terminal can perform remote operation and maintenance, big data collection and analysis, and visualization applications based on the vibration waveform; The first upload time is smaller than the second upload time.

3. The method for monitoring the condition of the main bearing of a shield machine according to claim 2, characterized in that: In response to an abnormality of the shield machine, starting from the next time the first upload time is reached, the characteristic value is calculated and the vibration waveform is generated according to the vibration signal stored in the dynamic buffer, and the characteristic value and the vibration waveform are uploaded to the monitoring terminal connected to the shield machine network.

4. The method for monitoring the condition of the main bearing of a shield machine according to claim 3, characterized in that: If the characteristic values ​​calculated by the shield machine that has an abnormality within the preset period each time reach the preset alarm value at the first upload time, the uploading of the vibration waveform will be stopped.

5. The method for monitoring the condition of the main bearing of a shield machine according to claim 2, characterized in that: The monitoring terminal includes a host monitoring terminal and a remote monitoring terminal, and uploads the characteristic value to the host monitoring terminal in the tunnel that establishes a network connection with the shield machine; The vibration waveform is uploaded to a remote monitoring terminal that has a network connection with the shield machine.

6. The method for monitoring the condition of the main bearing of a shield machine according to claim 2, characterized in that: During the second upload time, if there are at least two consecutive characteristic values ​​reaching the preset alarm value, it is confirmed that the shield machine has an abnormality.

7. The method for monitoring the condition of the main bearing of a shield machine according to claim 1, characterized in that: Vibration signals are collected using a vibration acceleration sensor located in the axial direction of the outer ring of the main bearing of the shield machine.

8. The method for monitoring the condition of the main bearing of a shield machine according to claim 1, characterized in that: The eigenvalues ​​are calculated as follows: When the first upload time is reached, the stored vibration signal is extracted from the dynamic buffer to generate a target vibration waveform; and the characteristic value is calculated according to the target vibration waveform.

9. The method for monitoring the condition of a main bearing of a shield machine according to any one of claims 1 to 8, characterized in that: The characteristic values ​​include: vibration acceleration peak value, acceleration effective value and kurtosis index.

10. A shield machine, characterized in that: It comprises a processor, wherein the processor is used to execute the condition monitoring method of the main bearing of the shield machine as described in any one of claims 1-9.

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