A vibration monitoring and tunneling equipment data real-time acquisition synchronization method and system

Abstract

The present invention proposes a method and system for real-time synchronous collection of vibration monitoring and tunneling equipment data, which is used to solve the technical problem that vibration monitoring and tunneling equipment data are difficult to analyze synchronously due to different storage locations, large differences in sampling frequencies, and difficulty in time synchronization. The method of the present invention: synchronously update the time and date of the equipment that collects vibration data and tunneling equipment data; select the smaller of the sampling frequencies of vibration data and tunneling equipment data as the reference frequency, and use the reference frequency to scale the sampling frequency of vibration data or tunneling equipment data; perform sparse processing on the collected vibration data so that the sampling time interval between two adjacent points in the vibration data is consistent with the tunneling equipment data; merge the sparse vibration data with the tunneling equipment data to complete the synchronous linkage analysis of vibration data and tunneling equipment data. The synchronization efficiency and automation degree of the vibration data and tunneling equipment data of the present invention are high and easy to implement.

Description

Technical Field

[0001] The present invention relates to the technical field of data synchronization, and in particular to a method and system for real-time data acquisition and synchronization of vibration monitoring and tunneling equipment. Background Art

[0002] As an additional sensor for monitoring the excavation status of equipment, the vibration monitoring system can be divided into two modes: offline measurement and online measurement. Compared with the vibration offline measurement system that requires shutdown measurement, the vibration online measurement system can realize the real-time collection of vibration data during the excavation process of the equipment. On the one hand, the data acquisition of the vibration online monitoring system is usually high-frequency acquisition, and the sampling frequency is much greater than 1Hz, so an independent industrial computer with high performance and large storage capacity is required to collect, store and process vibration data. On the other hand, the excavation equipment data is transmitted to the host computer through PLC, and its data acquisition is usually low-frequency acquisition, with the highest sampling frequency of 1Hz, in order to reduce the storage cost of the equipment's own host computer. However, as the running time increases, the difference between the equipment host computer time and the independent industrial computer time used for vibration data storage will become larger and larger, and the lack of network inside the tunnel makes it difficult to synchronize the time. In view of the existing vibration data and excavation equipment data, it is difficult to synchronize and analyze them due to different storage locations, large sampling frequency differences, and difficult time synchronization. Therefore, how to realize the synchronous linkage analysis of vibration data and excavation equipment data is of vital significance for subsequent data utilization and mining.

[0003] The invention patent with application number 202011317751.8 discloses an intelligent vibration status monitoring system and method, which realizes the real-time online collection, real-time analysis and processing of vibration data, so that technicians can intuitively observe the vibration status of key parts of tunneling equipment and adjust tunneling parameters in real time according to the vibration status. However, this technical solution only considers vibration data, and the sampling frequency of vibration data and tunneling equipment data is significantly different and the time is inconsistent. It can only roughly estimate the status of tunneling equipment through the change trend of vibration status of key parts, and it is difficult to achieve accurate analysis. Summary of the invention

[0004] In order to solve the technical problems that vibration monitoring and tunneling equipment data are difficult to analyze synchronously due to different storage locations, large differences in sampling frequencies and difficulty in time synchronization, the present invention proposes a method and system for real-time acquisition and synchronization of vibration monitoring and tunneling equipment data. Through local area network time synchronization, vibration data sparse processing, and the same-interval merging and analysis of vibration data and tunneling equipment data, the synchronization efficiency and automation level of the two are high and easy to implement.

[0005] In order to achieve the above object, the technical solution of the present invention is implemented as follows: a vibration monitoring and tunneling equipment data real-time acquisition synchronization method, the steps of which are:

[0006] Step S1: Synchronously updating the time and date of the equipment that collects vibration data and excavation equipment data;

[0007] Step S2: selecting the smaller sampling frequency of the vibration data and the excavation equipment data as the reference frequency, and scaling the sampling frequency of the vibration data or the excavation equipment data using the reference frequency;

[0008] Step S3: performing sparse processing on the collected vibration data so that the sampling time interval between two adjacent points in the vibration data is consistent with the tunneling equipment data;

[0009] Step S4: The vibration data after sparse processing in step S3 is merged with the excavation equipment data to complete the synchronous linkage analysis of the vibration data and the excavation equipment data.

[0010] Furthermore, the vibration monitoring slave computer that collects vibration data in step S1 and the tunneling equipment host computer that collects tunneling equipment data are in the same local area network, and the time and date of the vibration monitoring slave computer and the tunneling equipment host computer are synchronously updated by synchronization through the local area network.

[0011] Furthermore, the local area network time synchronization is implemented by:

[0012] S1.1, the time synchronization software server is installed on the upper computer of the tunneling equipment as the time standard, and the time synchronization software client is installed on the lower computer of the vibration monitoring to synchronize the time of the upper computer of the tunneling equipment;

[0013] S1.2, the communication between the tunneling equipment host computer and the vibration monitoring slave computer adopts TCP protocol connection to achieve time consistency.

[0014] Furthermore, the acquisition frequency of the tunneling equipment data is much lower than the acquisition frequency of the vibration data. In step S2, the acquisition frequency of the tunneling equipment data is set as the reference frequency. f base , scale the vibration data to the reference frequency f base superior.

[0015] Furthermore, the method of sparse processing in step S3 is:

[0016] S3.1, performing a first thinning process on the original vibration data at intervals of seconds, thinning the vibration data to a sampling time interval of 1 second between two adjacent vibration data points;

[0017] S3.2, according to the reference frequency f base , calculate the common sampling time interval T between two adjacent points when analyzing vibration data and tunneling equipment data synchronously = 1 / fbase ;

[0018] S3.3, search and determine the starting time when the timestamp of the vibration data after the first thinning is consistent with the tunneling equipment data, and perform secondary thinning sampling on the vibration data after the first thinning processing obtained in step S3.1 at a common sampling time interval T. The sampling time interval between two adjacent points in the obtained vibration data is consistent with the tunneling equipment data.

[0019] Furthermore, the method of the first thinning process in step S3.1 is:

[0020] S3.1.1, divide the vibration data collected per second into N segments according to 60 points / segment, and calculate the mean square amplitude feature of each segment of vibration data, and extract N vibration mean square amplitude features in total: ;

[0021] in, Vib ( i ) represents the first i numerical values;

[0022] S3.1.2, for the N vibration mean square amplitude features extracted in segments Vib rms Calculate the median: , as the final vibration characteristic value per second; where, Vib t represents the final vibration eigenvalue, median ( ) represents the median function.

[0023] Furthermore, in step S3.1.1, the kurtosis, peak factor or margin factor of the vibration data is extracted to obtain the characteristics of the time domain waveform of the vibration data.

[0024] The vibration monitoring slave computer for collecting vibration data and the tunneling equipment master computer for collecting tunneling equipment data realize synchronous updating of time and date through a synchronous time synchronization control.

[0025] A vibration monitoring and tunneling equipment data real-time acquisition synchronization system comprises a timing unit, a frequency scaling module, a sparse processing module, a data same-interval analysis module and a data merging module. The timing unit is respectively connected to a tunneling equipment host computer and a vibration monitoring slave computer, the vibration data collected by the vibration monitoring slave computer is connected to the frequency scaling module, the frequency scaling module is connected to the sparse processing module, the sparse processing module is connected to the data same-interval analysis module, and the tunneling equipment data collected by the data same-interval analysis module and the tunneling equipment host computer are both connected to the data merging module.

[0026] Furthermore, the time synchronization unit is a local area network time synchronization or a synchronous time synchronization control.

[0027] Furthermore, the local area network synchronizes and updates the time and date of the vibration monitoring slave computer that collects vibration data and the tunneling equipment host computer that collects tunneling equipment data; the vibration monitoring slave computer and the tunneling equipment host computer communicate via the local area network.

[0028] Further, the frequency scaling module uses the sampling frequency of the tunneling equipment data as the reference frequency and scales the sampling frequency of the vibration data to be the same as the reference frequency;

[0029] Furthermore, the sparse processing module sparses the original vibration data to a sampling time interval of 1 second between two adjacent vibration data points by extracting vibration mean square amplitude features;

[0030] Furthermore, the data same-interval analysis module performs secondary sparse sampling on the vibration data processed by the sparse processing module according to the common sampling interval obtained by the reference frequency.

[0031] Furthermore, the data merging module merges the vibration data processed by the data interval analysis module with the tunneling equipment data.

[0032] Compared with the prior art, the present invention has the following beneficial effects: the independent industrial computer for storing vibration data and the TBM host computer for collecting tunneling equipment data are connected via Ethernet and are in the same local area network, and the time and date of the two are synchronized through the local area network; according to the acquisition frequency of the vibration monitoring system and the acquisition frequency of the tunneling equipment data, the minimum sampling frequency of the two is used as the reference frequency for synchronous analysis of vibration data and tunneling equipment data, and the vibration data and tunneling equipment data are scaled to the same acquisition frequency scale; vibration-tunneling data same interval analysis: the original vibration data is sparsely processed so that the sampling time interval between two adjacent points in the sparse vibration data is consistent with the tunneling equipment data; the vibration data obtained after the second sparse processing is merged with the tunneling equipment data to complete the synchronous linkage analysis of vibration data and tunneling equipment data. The synchronization efficiency and automation degree of the vibration data and tunneling equipment data of the present invention are high and easy to implement, providing strong data support for the accurate and real-time judgment of the health status of each key component of the subsequent tunneling equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0034] Figure 1 It is a schematic diagram of the process of the present invention.

[0035] Figure 2 It is a functional block diagram of the system of the present invention. DETAILED DESCRIPTION

[0036] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0037] Example 1

[0038] like Figure 1 As shown, the present invention provides a method for real-time data acquisition and synchronization of vibration monitoring and tunneling equipment, and the steps are as follows:

[0039] S1, considering that the independent industrial computer used for vibration data storage is connected to the TBM host computer of the tunneling equipment through Ethernet and is in the same local area network, the time and date of the independent industrial computer and the TBM host computer can be synchronized through the local area network.

[0040] In the process of multi-source data collection of tunnel boring machines, vibration monitoring data comes from the lower computer, and tunnel boring equipment data comes from the upper computer. The existing vibration data and tunnel boring equipment data have a time misalignment phenomenon due to the complex working conditions of the data collection process. The present invention realizes the synchronous update of the time and date of the two through the local area network:

[0041] S1.1, install the time synchronization software server end on the upper computer of the tunneling equipment as the time standard, and install the client end on the lower computer of the vibration monitoring to synchronize the time of the upper computer;

[0042] S1.2, the communication between the tunneling equipment host computer and the vibration monitoring slave computer adopts TCP protocol connection to ensure the time consistency between the upper and lower computers.

[0043] S2, according to the collection frequency of the vibration monitoring system f Vib , Frequency of data collection for tunneling equipment f tu The minimum sampling frequency of the two is used as the reference frequency for synchronous analysis of vibration data and tunneling equipment data. Because the acquisition frequency of tunneling equipment data is much lower than that of vibration data, the acquisition frequency of tunneling equipment data is set as the reference frequency. f base , so that the vibration data and tunneling equipment data can be scaled to the same acquisition frequency scale later.

[0044] S3, performing sparse processing on the original vibration monitoring data so that the sampling time interval between two adjacent points in the sparse vibration data is consistent with the tunneling equipment data. The specific steps are as follows:

[0045] S3.1, the high-density original vibration data is first sparsely processed at intervals of seconds. The sampling frequency of the original vibration data is f Vib Hz, that is, sampling per second f Vib The first sparse processing can sparse the high-density original vibration data to a sampling time interval of 1 second between two adjacent vibration data points. The specific steps are as follows:

[0046] S3.1.1, divide the vibration data collected per second into N segments according to 60 points / segment, and calculate the mean square amplitude feature of each segment of vibration data, and extract N vibration mean square amplitude features in total:

[0047]

[0048] in, Vib ( i ) represents the first i A numerical value.

[0049] S3.1.2, for the N vibration mean square amplitude features extracted in segments Vib rms The median is calculated as the final vibration characteristic value per second to avoid the situation where the value is too large due to the influence of data noise.

[0050]

[0051] in, Vib t represents the final vibration eigenvalue, median ( ) represents the median function.

[0052] The final vibration eigenvalue obtained by the first sparse processing is Vib t , the sampling time interval between two adjacent vibration data points is 1 second. The sampling frequency of vibration data is high, so the sampling interval is first scaled to 1 second to ensure that the information distortion is small during the sparseness of vibration data. The vibration mean square amplitude can characterize the size of the effective amplitude of equipment vibration, and has a strong correlation with tunneling equipment data and geological conditions. It can be used for the later identification of abnormal equipment vibration, and its stability is good.

[0053] S3.2, according to the reference frequency f base, calculate the common sampling time interval between two adjacent points when analyzing vibration and tunneling parameters synchronously:

[0054] T=1 / f base .

[0055] S3.3, based on the vibration data after the first thinning obtained in step S3.1, by comparing the timestamps of the vibration data and the tunneling equipment data, search and determine the starting time when the timestamp of the vibration data is consistent with the tunneling equipment data, and use the common sampling time interval T as an interval to perform secondary thinning sampling on the vibration data after the first thinning processing obtained in step S3.1. At this time, the sampling time interval between two adjacent points in the obtained vibration data is consistent with the tunneling equipment data.

[0056] S4, merging the vibration data after the second thinning obtained in step S3 with the tunneling equipment data, thereby completing the synchronous linkage analysis of the vibration and tunneling equipment data.

[0057] The m-dimensional vibration data and n-dimensional tunneling equipment data after the second thinning are merged with the timestamp as the synchronization tag. The dimension of the merged data is (m+n) dimensional.

[0058] Example 2

[0059] A method for real-time data collection and synchronization of vibration monitoring and tunneling equipment, wherein in step S1, a developed synchronization time control is used to achieve synchronous update of time and date of an independent industrial computer and a TBM host computer.

[0060] In the sparse processing in step S3.1, the kurtosis, peak factor, margin factor and other indicators of the vibration data are extracted to reflect the characteristics of the time domain waveform obtained by the monitoring component. The kurtosis, peak factor and margin factor are sensitive to equipment pulse faults and can be used for early equipment fault monitoring. At the same time, the kurtosis, peak factor, margin factor and mean square amplitude indicators are extracted to monitor the key components of the equipment to take into account sensitivity and stability.

[0061] The other implementation methods are the same as those in Example 1.

[0062] Example 3

[0063] like Figure 2As shown, a vibration monitoring and tunneling equipment data real-time acquisition synchronization system includes a timing unit, a frequency scaling module, a sparse processing module, a data same-interval analysis module, and a data merging module. The timing unit is respectively connected to the tunneling equipment host computer and the vibration monitoring slave computer, the vibration data collected by the vibration monitoring slave computer is connected to the frequency scaling module, the frequency scaling module is connected to the sparse processing module, the sparse processing module is connected to the data same-interval analysis module, and the tunneling equipment data collected by the data same-interval analysis module and the tunneling equipment host computer are both connected to the data merging module.

[0064] The time synchronization unit is a local area network time synchronization or a synchronous time synchronization control, which synchronizes the time and date of the vibration monitoring slave computer that collects vibration data and the tunneling equipment host computer that collects tunneling equipment data. The vibration monitoring slave computer and the tunneling equipment host computer communicate through the local area network.

[0065] The frequency scaling module uses the sampling frequency of the tunneling equipment data as the reference frequency and scales the sampling frequency of the vibration data to be the same as the reference frequency.

[0066] The sparse processing module sparses the original vibration data to a sampling time interval of 1 second between two adjacent vibration data points by extracting the vibration mean square amplitude feature. The sparse processing module can also extract indicators such as kurtosis, peak factor, margin factor, etc. to reflect the characteristics of the time domain waveform of the vibration data.

[0067] The data common interval analysis module performs secondary sparse sampling on the vibration data processed by the sparse processing module according to the common sampling interval obtained by the reference frequency.

[0068] The data merging module merges the vibration data processed by the data interval analysis module with the tunneling equipment data.

[0069] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for real-time data acquisition and synchronization of vibration monitoring and tunneling equipment, characterized in that: The steps are: Step S1: Synchronously update the time and date of the equipment that collects vibration data and excavation equipment data; Step S2: selecting the smaller sampling frequency of the vibration data and the excavation equipment data as the reference frequency; Step S3: performing sparse processing on the collected vibration data so that the sampling time interval between two adjacent points in the vibration data after the sparse processing is consistent with the tunneling equipment data; The method of sparse processing in step S3 is: S3.1, performing a first thinning process on the original vibration data at intervals of seconds, thinning the vibration data to a sampling time interval of 1 second between two adjacent vibration data points; S3.2, according to the reference frequency f base , calculate the common sampling time interval T between two adjacent points when analyzing vibration data and tunneling equipment data synchronously = 1 / f base ; S3.3, searching and determining the start time when the timestamp of the vibration data after the first thinning process is consistent with the tunneling equipment data, and performing secondary thinning sampling on the vibration data after the first thinning process obtained in step S3.1 at a common sampling time interval T, so that the sampling time interval between two adjacent points in the obtained vibration data after the thinning process is consistent with the tunneling equipment data; Step S4: The vibration data after sparse processing in step S3 is merged with the tunneling equipment data to complete the synchronous linkage analysis of the vibration data and the tunneling equipment data.

2. The vibration monitoring and tunneling equipment data real-time acquisition and synchronization method according to claim 1 is characterized in that: In step S1, the vibration monitoring slave computer that collects vibration data and the tunneling equipment host computer that collects tunneling equipment data are in the same local area network, and the time and date of the vibration monitoring slave computer and the tunneling equipment host computer are synchronously updated by using the local area network time synchronization.

3. The vibration monitoring and tunneling equipment data real-time acquisition and synchronization method according to claim 2 is characterized in that: The method for implementing the local area network time synchronization is as follows: S1.1, the time synchronization software server is installed on the upper computer of the tunneling equipment as the time standard, and the time synchronization software client is installed on the lower computer of the vibration monitoring to synchronize the time of the upper computer of the tunneling equipment; S1.2, the communication between the tunneling equipment host computer and the vibration monitoring slave computer adopts TCP protocol connection to achieve time consistency.

4. The method for real-time data acquisition and synchronization of vibration monitoring and tunneling equipment according to any one of claims 1 to 3, characterized in that: The acquisition frequency of the tunneling equipment data is much lower than the acquisition frequency of the vibration data. In step S2, the acquisition frequency of the tunneling equipment data is set as the reference frequency. f base , scale the sparsely processed vibration data to the reference frequency f base superior.

5. The vibration monitoring and tunneling equipment data real-time acquisition and synchronization method according to claim 1 is characterized in that: The method of the first thinning process in step S3.1 is: S3.1.1, divide the vibration data collected per second into N segments according to 60 points / segment, and calculate the mean square amplitude feature of each segment of vibration data, and extract N vibration mean square amplitude features in total: ; in, Vib ( i ) represents the first i numerical values; S3.1.2, for the N vibration mean square amplitude features extracted in segments Vib rms Calculate the median: , as the final vibration characteristic value per second; where, Vib t represents the final vibration eigenvalue, median ( ) represents the median function.

6. The vibration monitoring and tunneling equipment data real-time acquisition and synchronization method according to claim 5 is characterized in that: In the step S3.1.1, the kurtosis, peak factor or margin factor of the vibration data is extracted to obtain the characteristics of the time domain waveform of the vibration data.

7. The method for real-time data acquisition and synchronization of vibration monitoring and tunneling equipment according to any one of claims 1, 5 and 6, characterized in that: The vibration monitoring slave computer for collecting vibration data and the tunneling equipment master computer for collecting tunneling equipment data realize synchronous updating of time and date through a synchronous time synchronization control.

8. A synchronization system using the vibration monitoring and tunneling equipment data real-time acquisition synchronization method according to any one of claims 1 to 3, 5 and 6, characterized in that: It includes a timing unit, a frequency scaling module, a sparse processing module, a data same-interval analysis module, and a data merging module. The timing unit is connected to the tunneling equipment host computer and the vibration monitoring slave computer respectively. The vibration data collected by the vibration monitoring slave computer is connected to the frequency scaling module. The frequency scaling module is connected to the sparse processing module. The sparse processing module is connected to the data same-interval analysis module. The data same-interval analysis module and the tunneling equipment data collected by the tunneling equipment host computer are both connected to the data merging module.

9. The synchronization system according to claim 8, characterized in that: The time synchronization unit is a local area network time synchronization or a synchronous time synchronization control.

10. The synchronization system according to claim 9, characterized in that: The local area network synchronizes and updates the time and date of the vibration monitoring slave computer that collects vibration data and the tunneling equipment host computer that collects tunneling equipment data; the vibration monitoring slave computer and the tunneling equipment host computer communicate through the local area network.

11. The synchronization system according to claim 9 or 10, characterized in that: The frequency scaling module uses the sampling frequency of the tunneling equipment data as the reference frequency, and scales the sampling frequency of the vibration data processed by the sparse processing module to be the same as the reference frequency; The sparse processing module sparses the original vibration data to a sampling time interval of 1 second between two adjacent vibration data points by extracting the vibration mean square amplitude feature; The data same-interval analysis module performs secondary sparse sampling on the vibration data processed by the sparse processing module according to the common sampling interval obtained by the reference frequency; The data merging module merges the vibration data processed by the data interval analysis module with the tunneling equipment data.

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