Vibration monitoring system and vibration monitoring method
Through a system that combines vibration sensor nodes with a cloud platform, construction vibration data is collected and processed in real time, solving the problems of cumbersome equipment operation and easy data damage in existing technologies, and achieving efficient and reliable construction vibration monitoring.
Patent Information
- Application Number
- CN202410253340.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-03-06
- Publication Date
- 2025-09-09
AI Technical Summary
Existing construction vibration monitoring methods have the disadvantages of cumbersome equipment operation, easily corrupted data, and lack of real-time data transmission capabilities, resulting in low monitoring efficiency, which is especially disadvantageous in remote sites.
A system combining vibration sensor nodes and a vibration monitoring cloud platform is used. The sensor nodes collect and process vibration data in real time, transmit the data to the cloud platform for analysis and storage, and provide real-time monitoring results.
It improves the efficiency of vibration monitoring and the security of data, and ensures the reliability and real-time performance of monitoring data in unstable networks or remote sites.
Smart Images
Figure CN120609440A_ABST
Abstract
Description
Technical Field
[0001] The present application belongs to the technical field of construction safety monitoring, and in particular relates to a vibration monitoring system and a vibration monitoring method. Background Art
[0002] Construction activities, such as blasting, demolition, pile foundation construction, soil compaction, and the use of vibrating machinery, can generate ground vibrations that may exceed prescribed safety limits and adversely affect the structural integrity of adjacent buildings and infrastructure. Furthermore, this type of construction-induced vibration can pose a potential risk to highly sensitive equipment or institutions near the construction site, such as medical institutions and biological research laboratories. Real-time vibration monitoring is crucial to ensure the structural safety of adjacent buildings and facilities.
[0003] Existing construction vibration monitoring methods are generally divided into two categories: fixed monitoring station monitoring and temporary measurements using portable equipment, but each has certain limitations. The establishment and operation of fixed monitoring stations require specially trained professionals, which means that not all construction workers can accurately set up, calibrate, and analyze data, and usually need to seek help from third-party professional consultation or expert support. On the other hand, portable equipment (such as seismographs) is expensive and mostly relies on manual methods for data extraction, which is not only cumbersome to operate, but also prone to data loss or damage, seriously affecting the monitoring effect. What is more noteworthy is that both types of monitoring methods lack real-time data transmission capabilities, which is extremely disadvantageous in construction sites with remote locations or limited access, greatly reducing the efficiency of vibration monitoring.
[0004] Therefore, how to improve the efficiency of vibration monitoring during construction has become an urgent problem to be solved. Summary of the Invention
[0005] The embodiments of the present application provide a vibration monitoring system and a vibration monitoring method, which effectively improve the efficiency of vibration monitoring during the construction process.
[0006] In a first aspect, an embodiment of the present application provides a vibration monitoring system, which includes a vibration sensing node and a vibration monitoring cloud platform, wherein the vibration sensing node is installed at a location to be monitored, and the vibration sensing node is communicatively connected to the vibration monitoring cloud platform; the vibration sensing node is used to collect original vibration data, perform real-time data processing on the original vibration data to obtain vibration index data, and transmit the original vibration data and the vibration index data to the vibration monitoring cloud platform in real time; the vibration monitoring cloud platform is used to obtain a vibration monitoring result based on the vibration index data and a first preset threshold, and store the original vibration data, the vibration index data and the vibration monitoring result, wherein the vibration monitoring result indicates whether there is vibration index data exceeding the first preset threshold.
[0007] In one possible implementation, the vibration sensing node includes a micro single-board computer, a micro-electromechanical system sensor, a wireless communication module and a power supply module, and the micro single-board computer is communicatively connected to the micro-electromechanical system sensor, the wireless communication module and the power supply module respectively; the micro-electromechanical system sensor is used to collect the original vibration data; the micro single-board computer is used to process the original vibration data to obtain the vibration index data; the wireless communication module is used to transmit the original vibration data and the vibration index data to the vibration monitoring cloud platform; and the power supply module is used to power the vibration sensing node.
[0008] In one possible implementation, the micro single-board computer includes a first data processing module and a storage module; the first data processing module is used to process the original vibration data to obtain the vibration index data; the storage module is used to store the original vibration data and the vibration index data.
[0009] In one possible implementation, the micro single-board computer also includes a watchdog timer and a first alarm module; the watchdog timer is used to monitor the network connection status of the vibration sensing node and the vibration monitoring cloud platform in real time; the first alarm module is used to alarm when the vibration sensing node is disconnected from the vibration monitoring cloud platform for more than a preset time period; the wireless communication module is also used to automatically reconnect when the vibration sensing node is disconnected from the vibration monitoring cloud platform, and when the vibration sensing node is restored to the vibration monitoring cloud platform, the original vibration data and vibration index data stored in the storage module, which were generated when the vibration sensing node was disconnected from the vibration monitoring cloud platform, are transmitted to the vibration monitoring cloud platform.
[0010] In a possible implementation, the micro single-board computer further includes a time synchronization module; the time synchronization module is configured to align an internal clock of the micro single-board computer with a reference network time.
[0011] In one possible implementation, the time synchronization module includes: an acquisition unit, configured to acquire a timestamp based on a first preset time interval within a preset time period; a calculation unit, configured to calculate a mean absolute time offset of the preset time period based on the timestamp; and a correction unit, configured to correct the internal clock of the micro single-board computer to align with the reference network time when the mean absolute time offset is greater than a second preset threshold.
[0012] In one possible implementation, the vibration monitoring cloud platform includes a second data processing module and a second alarm module; the second data processing module is used to process the original vibration data to obtain the vibration index data, and obtain the vibration monitoring result based on the vibration index data and the first preset threshold; the second alarm module is used to alarm when the vibration index data is greater than the first preset threshold.
[0013] In one possible implementation, the raw vibration data includes raw acceleration data, and the vibration index data includes acceleration time history, peak vibration velocity and 1 / 3 octave root mean square velocity. The first data processing module and the second data processing module are specifically used to: perform fast Fourier transform, bandpass filtering and inverse fast Fourier transform on the raw acceleration data to obtain the acceleration time history; perform integration, fast Fourier transform, bandpass filtering and inverse fast Fourier transform on the raw acceleration data to obtain the peak vibration velocity; perform integration, fast Fourier transform, inverse fast Fourier transform and 1 / 3 octave division on the raw acceleration data to obtain the 1 / 3 octave root mean square velocity.
[0014] In one possible implementation, the vibration monitoring cloud platform also includes a MySQL database and a visualization interface; the MySQL database is used to partition and store the original vibration data, the vibration index data, and the vibration monitoring results according to preset storage rules, and regularly back up the original vibration data, the vibration index data, and the vibration monitoring results; the visualization interface is used to perform real-time data display, historical data retrieval, and data export based on the MySQL database.
[0015] In a second aspect, an embodiment of the present application provides a vibration monitoring method, which is characterized in that, when applied to a vibration monitoring system, the method includes: obtaining original vibration data; determining vibration index data based on the original vibration data; and determining a vibration monitoring result based on the vibration index data and a first preset threshold, wherein the vibration monitoring result indicates whether there is vibration index data that exceeds the first preset threshold.
[0016] The beneficial effects of the embodiments of the present application compared with the prior art are as follows: the vibration sensor node is used to collect original vibration data, and can perform real-time data processing on the original vibration data to obtain vibration index data, and then transmit the original vibration data and vibration index data to the vibration monitoring cloud platform in real time, so that in application scenarios that require rapid response or the network is unavailable or the network connection is unstable, there is no need to transmit the original vibration data to the vibration monitoring cloud platform for calculation of the vibration index data. Instead, the vibration sensor node processes the collected original vibration in real time to obtain vibration index data, which effectively improves the efficiency of vibration monitoring; the vibration monitoring cloud platform provides powerful analysis and computing resources, which can obtain vibration monitoring results based on the vibration index data transmitted by the vibration sensor node and preset thresholds, and also provides data storage function, which can store original vibration data, vibration index data and vibration monitoring results, ensuring the security and continuous availability of the data. BRIEF DESCRIPTION OF THE DRAWINGS
[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments or descriptions of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.
[0018] Figure 1 A schematic diagram of the architecture of a vibration monitoring system provided in one embodiment of the present application;
[0019] Figure 2 A schematic structural diagram of a vibration sensing node 110 provided in one embodiment of the present application;
[0020] Figure 3 A schematic diagram of the architecture of a micro single-board computer 1101 provided in one embodiment of the present application;
[0021] Figure 4 A schematic diagram of the architecture of a vibration monitoring cloud platform 120 provided in one embodiment of the present application;
[0022] Figure 5 A schematic flow chart of a vibration monitoring method provided in one embodiment of the present application;
[0023] Figure 6 A flowchart of another vibration monitoring method provided in an embodiment of the present application. DETAILED DESCRIPTION
[0024] In the following description, specific details such as specific system structures and techniques are provided for purposes of illustration rather than limitation to facilitate a thorough understanding of the embodiments of the present application. However, it will be apparent to those skilled in the art that the present application may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid obscuring the description of the present application with unnecessary detail.
[0025] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or collections thereof.
[0026] It will also be understood that the term "and / or" used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
[0027] As used in this specification and the appended claims, the term "if" can be interpreted as "when" or "upon" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "upon determination" or "in response to determining" or "upon detection of [described condition or event]" or "in response to detecting [described condition or event]," depending on the context.
[0028] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.
[0029] References to "one embodiment" or "some embodiments" in this specification mean that a particular feature, structure, or characteristic described in conjunction with that embodiment is included in one or more embodiments of the present application. Thus, phrases such as "in one embodiment," "in some embodiments," "in other embodiments," and "in other embodiments" appearing in various places in this specification do not necessarily refer to the same embodiment, but rather mean "one or more but not all embodiments," unless otherwise specifically emphasized. The terms "including," "comprising," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.
[0030] Construction activities, such as blasting, demolition, pile foundation construction, soil compaction, and the use of vibrating machinery, can generate ground vibrations that may exceed prescribed safety limits and adversely affect the structural integrity of adjacent buildings and infrastructure. Furthermore, this type of construction-induced vibration can pose a potential risk to highly sensitive equipment or institutions near the construction site, such as medical institutions and biological research laboratories. Real-time vibration monitoring is crucial to ensure the structural safety of adjacent buildings and facilities.
[0031] Existing construction vibration monitoring methods are generally divided into two categories: fixed monitoring station monitoring and temporary measurements using portable equipment, but each has certain limitations. The establishment and operation of fixed monitoring stations require specially trained professionals, which means that not all construction workers can accurately set up, calibrate, and analyze data, and usually need to seek help from third-party professional consultation or expert support. On the other hand, portable equipment (such as seismographs) is expensive and mostly relies on manual methods for data extraction, which is not only cumbersome to operate, but also prone to data loss or damage, seriously affecting the monitoring effect. What is more noteworthy is that both types of monitoring methods lack real-time data transmission capabilities, which is extremely disadvantageous in construction sites with remote locations or limited access, greatly reducing the efficiency of vibration monitoring.
[0032] In order to solve the above technical problems, the present application proposes a vibration monitoring system and a vibration monitoring method, which system includes a vibration sensing node and a vibration monitoring cloud platform. The vibration sensing node is installed at the location to be monitored, and the vibration sensing node is communicatively connected to the vibration monitoring cloud platform; wherein, the vibration sensing node is used to collect original vibration data, perform real-time data processing on the original vibration data, obtain vibration index data, and transmit the original vibration data and vibration index data to the vibration monitoring cloud platform in real time; the vibration monitoring cloud platform is used to obtain vibration monitoring results based on the vibration index data and a first preset threshold, and store the original vibration data, vibration index data and vibration monitoring results. The vibration monitoring results characterize whether there is vibration index data exceeding the first preset threshold, which effectively improves the efficiency of vibration monitoring, and at the same time improves the security and continuous availability of monitoring data.
[0033] For ease of understanding, the technical solution of this application will be described in detail below with reference to the accompanying drawings.
[0034] Figure 1 This is a schematic diagram of the architecture of a vibration monitoring system provided in one embodiment of the present application, such as Figure 1As shown, the vibration monitoring system 100 includes a vibration sensor node 110 and a vibration monitoring cloud platform 120. The vibration sensor node 110 is installed at a location to be monitored, and the vibration sensor node 110 is communicatively connected to the vibration monitoring cloud platform.
[0035] In a specific implementation, the vibration sensing node 110 is used to collect raw vibration data, perform real-time data processing on the raw vibration data to obtain vibration index data, and transmit the raw vibration data and vibration index data to the vibration monitoring cloud platform 120 in real time; the vibration monitoring cloud platform 120 is used to obtain vibration monitoring results based on the vibration index data and a first preset threshold, and store the raw vibration data, vibration index data, and vibration monitoring results, etc. The vibration monitoring results represent whether there is vibration index data that exceeds the first preset threshold.
[0036] In one embodiment, in application scenarios where a quick response is required or the network is unavailable or the network connection is unstable, the vibration sensing node 110 collects the raw vibration data and processes the raw vibration data locally in real time to obtain vibration index data, and then transmits the raw vibration data and vibration index data to the vibration monitoring cloud platform 120 in real time for analysis and storage.
[0037] In another embodiment, when large-scale data analysis, machine learning model training, or highly scalable computing is required, the vibration sensing node 110 collects the raw vibration data and transmits the collected raw vibration data to the vibration monitoring cloud platform 120 in real time. The vibration monitoring cloud platform 120 processes and analyzes the raw vibration data to obtain vibration index data and vibration monitoring results, and stores the raw vibration data, vibration index data, and vibration monitoring results.
[0038] Exemplarily, the original vibration data is the acceleration data of the position to be monitored, the vibration index data is one or more of the peak particle velocity (PPV), the root mean square velocity in 1 / 3 octave band spectrum, and the acceleration time history, and the vibration monitoring result is used to indicate whether the calculated vibration index data exceeds the corresponding first preset threshold value. For example, when the vibration monitoring result is 1, it indicates that the calculated vibration index data contains data that exceeds the corresponding first preset threshold value; when the vibration monitoring result is 0, it indicates that the calculated vibration index data does not exceed the corresponding first preset threshold value. Among them, different types of vibration index data correspond to different first preset threshold values, which need to be set separately according to actual needs. When the vibration monitoring result shows that there is vibration index data that exceeds the first preset threshold value, it indicates that the vibration does not meet the requirements; when the vibration monitoring result shows that there is no vibration index data that exceeds the first preset threshold value, it indicates that the vibration meets the requirements.
[0039] As an example, Figure 2 As shown, the vibration sensing node 110 includes a micro single board computer 1101, a micro electromechanical system sensor 1102, a wireless communication module 1103 and a power supply module 1104. The micro single board computer 1101 is communicatively connected to the micro electromechanical system sensor 1102, the wireless communication module 1103 and the power supply module 1104 respectively.
[0040] In a specific implementation, the micro-electromechanical system sensor 1102 is used to collect raw vibration data; the micro single-board computer 1101 is used to process the raw vibration data to obtain vibration index data; the wireless communication module 1103 is used to transmit the raw vibration data and vibration index data to the vibration monitoring cloud platform 120; and the power supply module 1104 is used to power the vibration sensing node 110.
[0041] Preferably, the micro single-board computer 1101 selects Raspberry Pi 4, the micro-electromechanical system sensor 1102 selects BMI160, the wireless communication module 1103 selects a 4G network module or a long-term evolution (LTE) network module, such as HUAWEI E8372, and the power supply module 1104 selects a solar power supply system.
[0042] Specifically, the Raspberry Pi 4 is responsible for collecting and processing acceleration data from the BMI160 accelerometer. The Raspberry Pi 4 is equipped with a high-performance central processing unit (CPU) and graphics processing unit (GPU), enabling it to perform complex signal processing and support multiple sensing modes. Furthermore, the Raspberry Pi 4 is equipped with a large-capacity flash memory for temporary data storage in the event of a network connection failure, thereby enhancing the fault tolerance of the vibration monitoring system 100 and ensuring that data collection can continue even during network outages.
[0043] Specifically, the BMI160 sensor features versatility, low power consumption, and low noise levels. The sensor includes a 16-bit digital triaxial accelerometer and a 16-bit digital triaxial gyroscope, enabling precise measurements along the x, y, and z axes. It offers multiple acceleration ranges, including ±2 g, ±4 g, ±8 g, and ±16 g, along with corresponding sensitivity settings of 0.061 mg per least significant bit (mg / LSB), 0.122 mg / LSB, 0.244 mg / LSB, and 0.488 mg / LSB. The BMI160 sensor has a configurable sampling frequency, typically ranging from 12.5 Hz to 1600 Hz. These parameters can be adjusted to specific application scenarios, for example, setting the acceleration range to ±2 g and the sampling frequency to 400 Hz. Furthermore, the BMI160 sensor supports both the Integrated Circuit (I2C) and Serial Peripheral Interface (SPI) communication protocols, making it compatible with a variety of micro-electromechanical system (MEMS) sensors.
[0044] For example, if the BMI160 sensor communicates digital measurement data with a Raspberry Pi 4 using high-speed I2C mode, the 3V3, GND, SCL, SDA, and SA0 pins on the BMI160 sensor circuit board need to be connected to the 3.3V PWR, GND, I2C SCL, I2C SD, and GND pins on the Raspberry Pi 4 circuit board, respectively. Table 1 provides detailed information on the BMI160 sensor pins.
[0045] Table 1
[0046] Pins name connect Function 1 3V3 3.3V PWR 3.3 volt power pin 2 GND GND Grounding 3 SCL I2C SCL I2C communication clock line 4 SDA I2C SDA I2C communication data line 5 SA0 GND Slave address bit 0, grounded
[0047] In a specific implementation, all hardware components in the vibration sensing node 110 are enclosed in a waterproof box for easy installation. For example, the dimensions of the waterproof box are 140 x 120 x 72 millimeters (mm), and the total weight of the integrated prototype is 650 grams. This compact and lightweight design facilitates the deployment of the vibration sensing node 110 in various environments.
[0048] This embodiment also provides multiple installation methods for the vibration sensor node 110 to accommodate various locations to be monitored. For example, using a strong magnet fastened to the bottom of the vibration sensor node 110, three installation methods are proposed:
[0049] 1. When the location to be monitored is a soil surface, a steel soil nail is inserted into the ground, and then the vibration sensor node 110 equipped with a magnet is fixed thereon.
[0050] 2. When the location to be monitored is a concrete or rock surface, use epoxy AB glue to firmly adhere the vibration sensing node 110 thereto.
[0051] 3. When the location to be monitored is a vertical surface (such as a pillar or a wall), the vibration sensing node 110 is directly fixed on the smooth surface using screws.
[0052] Figure 3 A schematic diagram of the architecture of a micro single-board computer 1101 provided in one embodiment of the present application is shown in FIG. Figure 3 As shown, the micro single board computer 1101 includes a first data processing module 310 , a storage module 320 , a watchdog timer 330 , a first alarm module 340 and a time synchronization module 350 .
[0053] In a specific implementation, the first data processing module 310 is used to process the original vibration data to obtain vibration index data; the storage module 320 is used to store the original vibration data and vibration index data; the watchdog timer 330 is used to monitor the network connection status between the vibration sensing node 110 and the vibration monitoring cloud platform 120 in real time; the first alarm module 340 is used to alarm when the vibration sensing node 110 is disconnected from the vibration monitoring cloud platform 120 for longer than a preset time; the time synchronization module 350 is used to align the internal clock of the micro single-board computer 1101 with the reference network time.
[0054] Specifically, the raw vibration data includes raw acceleration data, and the vibration index data includes acceleration time history, peak vibration velocity and 1 / 3 octave root mean square velocity. The first data processing module 310 first removes noise from the raw acceleration data through fast Fourier transform (FFT) and bandpass filtering, and then uses the built-in maximum and minimum array functions to calculate the peak vibration velocity of the particle, and calculates the 1 / 3 octave root mean square velocity in the time domain and frequency domain through 1 / 3 octave division.
[0055] Exemplarily, the first data processing module 310 performs fast Fourier transform (FFT) on the raw acceleration data to obtain a spectrum, performs bandpass filtering on the spectrum to obtain a filter spectrum, and performs inverse fast Fourier transform (IFFT) on the filter spectrum to obtain the acceleration time history.
[0056] Exemplarily, the first data processing module 310 integrates the raw acceleration data to obtain raw velocity data, performs fast Fourier transform on the raw velocity data to obtain a spectrum, performs bandpass filtering on the spectrum to obtain a filter spectrum, performs inverse fast Fourier transform on the filter spectrum to obtain a velocity time history, and processes the velocity time history to obtain a peak vibration velocity.
[0057] Exemplarily, the first data processing module 310 integrates the raw acceleration data to obtain raw velocity data, performs fast Fourier transform on the raw velocity data to obtain a spectrum, processes the spectrum to obtain band partitions, performs inverse fast Fourier transform and 1 / 3 octave division processing on the band partitions to obtain 1 / 3 octave root mean square velocity.
[0058] Specifically, the storage module 320 is used to store the original vibration data and vibration index data in a comma separated values (CSV) format.
[0059] Exemplarily, the storage module 320 is a flash memory configured in the Raspberry Pi 4.
[0060] Specifically, watchdog timer 330 monitors the network connection status of vibration sensing node 110 and vibration monitoring cloud platform 120 in real time, and monitors the data insertion process in real time. If the data insertion delay exceeds a predetermined time limit, watchdog timer 330 will automatically restart and notify relevant personnel via email. When it is determined by watchdog timer 330 that vibration sensing node 110 is disconnected from vibration monitoring cloud platform 120, wireless communication module 1103 automatically reconnects vibration sensing node 110 with vibration monitoring cloud platform 120, and when vibration sensing node 110 is reconnected from vibration monitoring cloud platform 120, the original vibration data and vibration index data stored in storage module 320, generated when vibration sensing node 110 is disconnected from vibration monitoring cloud platform 120, are transmitted to vibration monitoring cloud platform 120. In addition, when the time that vibration sensing node 110 is disconnected from vibration monitoring cloud platform 120 exceeds a preset duration by watchdog timer 330, first alarm module 340 alarms, for example, notifies relevant operating personnel immediately by email.
[0061] Specifically, to ensure accurate and consistent time synchronization for the vibration sensor node 110, the time synchronization module 350 uses the Network Time Protocol (NTP) algorithm, using the Google NTP server (time.google.com) as a time reference source, to calibrate the internal clock of the micro single-board computer 1101. The time synchronization module 350 includes an acquisition unit, a calculation unit, and a correction unit. The acquisition unit is configured to acquire timestamps based on a first preset time interval within a preset time period; the calculation unit is configured to calculate an average absolute time offset for the preset time period based on the acquired timestamps; and the correction unit is configured to align the micro single-board computer's internal clock with the reference network time when the calculated average absolute time offset exceeds a second preset threshold.
[0062] Exemplarily, the preset time period is one hour, the first preset time interval is 5 minutes, and the second preset threshold is 10 milliseconds. The time synchronization module 350 automatically obtains and evaluates the difference between the two sets of timestamps (T2-T1) and (T4-T3) every 5 minutes, and calculates the time offset through the time offset calculation formula. Based on the periodic evaluation, the absolute time offset mean is generated every hour. When the absolute time offset mean is less than or equal to 10 milliseconds, it means that the internal clock of the micro single-board computer 1101 remains stable and no adjustment is required until the next hour's evaluation cycle. On the contrary, if the generated absolute time offset mean is greater than 10 milliseconds, the time synchronization module 350 will automatically correct its internal clock to align with the reference network time. As an example, the time offset calculation formula is shown in the following formula (1):
[0063]
[0064] Wherein, Td represents the time offset, (T2-T1) and (T4-T3) represent two sets of timestamps respectively.
[0065] Furthermore, all time adjustment activities are recorded in detail in a dedicated log file. This design not only significantly improves the time accuracy of vibration monitoring system 100, but also enhances its robustness and reliability. By adaptively adjusting for potential time offsets, vibration monitoring system 100 ensures accurate and consistent data collection and analysis, providing a solid foundation for its widespread deployment in various application scenarios.
[0066] Figure 4 A schematic diagram of the architecture of a vibration monitoring cloud platform 120 provided in one embodiment of the present application is shown in FIG. Figure 4 As shown, the vibration monitoring cloud platform 120 includes a second data processing module 1201 , a second alarm module 1202 , a MySQL database 1203 and a visualization interface 1204 .
[0067] In a specific implementation, the second data processing module 1201 is used to process the original vibration data to obtain vibration index data, and obtain vibration monitoring results based on the vibration index data and the first preset threshold; the second alarm module 1202 is used to alarm when the vibration index data exceeds the first preset threshold; the MySQL database 1203 is used to partition and store the original vibration data, vibration index data and vibration monitoring results according to preset storage rules, and regularly back up the original vibration data, vibration index data and vibration monitoring results; the visualization interface 1204 is used to perform real-time data display, historical data retrieval and data export based on the MySQL database.
[0068] Specifically, to achieve accurate and efficient vibration monitoring, the vibration monitoring cloud platform 120 incorporates a series of advanced signal processing algorithms. Data processing is performed by the second data processing module 1201. This processing flow covers everything from noise removal to the real-time calculation of various vibration indicators, providing a comprehensive, efficient, and reliable data analysis platform. The second data processing module 1201 first removes noise from the raw acceleration signal uploaded by the vibration sensing node 110 through fast Fourier transform and bandpass filtering. It then uses built-in maximum and minimum array functions to calculate the peak vibration velocity of the particle. Using 1 / 3 octave band division, it can calculate the 1 / 3 octave root mean square velocity in both the time and frequency domains.
[0069] Exemplarily, the second data processing module 1201 performs fast Fourier transform on the original acceleration data to obtain a spectrum, performs bandpass filtering on the spectrum to obtain a filter spectrum, and performs inverse fast Fourier transform on the filter spectrum to obtain the acceleration time history.
[0070] Exemplarily, the second data processing module 1201 integrates the raw acceleration data to obtain raw velocity data, performs fast Fourier transform on the raw velocity data to obtain a spectrum, performs bandpass filtering on the spectrum to obtain a filter spectrum, performs inverse fast Fourier transform on the filter spectrum to obtain a velocity time history, and processes the velocity time history to obtain a peak vibration velocity.
[0071] Exemplarily, the second data processing module 1201 integrates the original acceleration data to obtain original velocity data, performs fast Fourier transform on the original velocity data to obtain a spectrum, processes the spectrum to obtain band partitions, performs inverse fast Fourier transform and 1 / 3 octave division processing on the band partitions to obtain 1 / 3 octave root mean square velocity.
[0072] Specifically, the second alarm module 1202 monitors the vibration level in real time through a Python program, and compares and analyzes it with the first preset threshold. The first preset threshold can be configured according to specific safety regulations or standards applicable to different structures or facilities. When there is vibration index data exceeding the corresponding first preset threshold in one or more calculated vibration index data, an autonomous alarm mechanism will be triggered, and an email notification will be sent to predefined stakeholders (such as construction contractors, on-site engineers and other parties involved) through the second alarm module 1202. The notification email will include the current vibration index data and necessary key information, wherein the necessary key information includes the vibration threshold of the location and the specific structures or facilities that may be affected. The autonomous alarm function makes immediate intervention possible, allowing related activities to be suspended for in-depth evaluation when necessary, thereby greatly improving the safety and reliability of the entire vibration monitoring system 100.
[0073] Specifically, the MySQL database 1203 is used for long-term data storage. A complete set of data transmission mechanisms is implemented through the Python programming language, which can not only store the collected raw vibration data, vibration index data and vibration monitoring results in the MySQL database 1203, but also automatically create new data tables in the MySQL database 1203, and record all successful or failed database operations. For long-term vibration monitoring projects, the collected and calculated data will be stored in different data tables according to date partitions. Each data table has a clear identifier, consistent index, field type and character set. To prevent accidental data loss or damage, all MySQL databases 1203 will regularly back up these data.
[0074] Specifically, the visualization interface 1204 supports a variety of data-related operations, including real-time data visualization, historical data retrieval, and data export.
[0075] Preferably, the visualization interface 1204 is a page-based visualization interface, and the server-side page is developed using a hypertext preprocessor (PHP); while on the client side, a chart software library Highcharts written in JavaScript is used to display and download data. The page triggers a specified PHP script through regular asynchronous JavaScript and XML (AJAX) requests to obtain real-time data from the MySQL database 1203. The script queries the MySQL database 1203, retrieves the latest data, and uses it for client-side rendering. Highcharts visualizes this data in the form of an interactive line chart, thereby providing an intuitive user interface.
[0076] For historical data retrieval, the visualization interface 1204 provides a date selector to specify the time range to be retrieved. Once the user selects a date, another PHP script queries the MySQL database 1203 to collect data for that time range. The retrieved data is then parsed and displayed alongside the real-time data in the same line chart, which dynamically updates to include both types of data.
[0077] In addition, the Highcharts library provides built-in data export functionality, allowing users to download data in a variety of formats (such as portable network graphics (PNG) images or CSV raw data) through a menu on the chart. This allows users to not only conduct in-depth analysis of the data but also save it for future analysis, sharing, or to meet regulatory requirements, ensuring convenient and comprehensive data manipulation and analysis on the vibration monitoring cloud platform 120.
[0078] Figure 5 A flow chart of a vibration monitoring method provided in one embodiment of the present application is shown as follows: Figure 5 As shown, this method is applied to Figure 1 The vibration monitoring system 100 shown, the method includes:
[0079] S510: Obtain original vibration data.
[0080] In a specific implementation, the original vibration data is obtained by the micro-electromechanical system sensor in the vibration sensing node. When the micro-electromechanical system sensor uses the BMI160 accelerometer, the obtained original vibration data is the original acceleration data of the position to be monitored.
[0081] For example, the vibration sensing node is Figure 1 The vibration sensing node 110 in the micro-electromechanical system sensor is Figure 2 The micro-electromechanical system sensor 1102 in FIG.
[0082] S520: Determine vibration index data based on the original vibration data.
[0083] In one embodiment, in application scenarios where a quick response is required or the network is unavailable or the network connection is unstable, the raw vibration data is processed locally in real time by a micro single-board computer in the vibration sensor node to determine vibration index data.
[0084] Specifically, the first data processing module in the micro single-board computer processes the original vibration data locally in real time to determine the vibration index data.
[0085] For example, the micro single board computer is Figure 2 The micro single board computer 1101 in the first data processing module is Figure 3 The first data processing module 310 in.
[0086] In another embodiment, when large-scale data analysis, machine learning model training, or highly scalable computing is required, after obtaining the original vibration data, the obtained original vibration data is transmitted to the vibration monitoring cloud platform in real time, and the vibration monitoring cloud platform processes the original vibration data to determine the vibration index data.
[0087] Specifically, the second data processing module in the vibration monitoring cloud platform processes the original vibration data to determine the vibration index data.
[0088] For example, the vibration monitoring cloud platform is Figure 1 The vibration monitoring cloud platform 120 in the second data processing module is Figure 4 The second data processing module 1201 in.
[0089] Specifically, the vibration index data includes but is not limited to acceleration time history, peak vibration velocity, and 1 / 3 octave root mean square velocity. The process of processing the raw vibration data to determine the vibration index data includes: performing fast Fourier transform, bandpass filtering, and inverse fast Fourier transform on the acquired raw acceleration data to obtain acceleration time history; integrating, fast Fourier transform, bandpass filtering, and inverse fast Fourier transform on the acquired raw acceleration data to obtain peak vibration velocity; integrating, fast Fourier transform, inverse fast Fourier transform, and 1 / 3 octave division on the raw acceleration data to obtain 1 / 3 octave root mean square velocity.
[0090] S530: Determine a vibration monitoring result based on the vibration index data and a first preset threshold.
[0091] In a specific implementation, the vibration monitoring cloud platform determines a vibration monitoring result based on the vibration index data and a first preset threshold. The vibration monitoring result is used to indicate whether the calculated vibration index data exceeds the corresponding first preset threshold. For example, when the vibration monitoring result is 1, it indicates that the calculated vibration index data contains data that exceeds the corresponding first preset threshold; when the vibration monitoring result is 0, it indicates that none of the calculated vibration index data exceeds the corresponding first preset threshold. Different types of vibration index data correspond to different first preset thresholds and need to be set according to actual needs.
[0092] Specifically, the second data processing module in the vibration monitoring cloud platform determines the vibration monitoring result based on the vibration index data and the first preset threshold.
[0093] Figure 6 This is a flow chart of another vibration monitoring method provided in one embodiment of the present application. Figure 6 As shown, this method is applied to Figure 2 The vibration sensing node 110 shown, the method includes:
[0094] S610 , initializing the MEMS sensor and checking the communication interface between the MEMS sensor and the micro single board computer.
[0095] In a specific implementation, an example of a micro-electromechanical system sensor is Figure 2 An example of a micro-electromechanical system sensor 1102 in a micro single-board computer is Figure 2 When the MEMS sensor uses the BMI 160 and communicates with the micro single board computer via I2C, the BMI 160 is initialized and the I2C interface is checked.
[0096] S620: Set the sampling frequency and acceleration range of the MEMS sensor.
[0097] In specific implementations, when the BMI160 is selected as a MEMS sensor, the BMI160 provides multiple acceleration ranges, such as ±2g, ±4g, ±8g, and ±16g. The sampling frequency of the BMI160 sensor typically ranges from 12.5Hz to 1600Hz. The sampling frequency and acceleration range of the BMI160 can be customized based on actual conditions, and this application does not limit this. For example, the acceleration range of the BMI160 is set to ±2g, and the sampling frequency is set to 400Hz.
[0098] S630: Read and store the raw vibration data locally.
[0099] In a specific implementation, after the sampling frequency and acceleration range of the MEMS sensor are set, the MEMS sensor collects raw vibration data of the position to be monitored, and the micro single-board computer reads and stores the raw vibration data.
[0100] In addition, in application scenarios where a quick response is required or the network is unavailable or the network connection is unstable, the micro single-board computer can process the collected raw vibration data locally in real time to obtain vibration index data.
[0101] S640 transmits the raw vibration data to the vibration monitoring cloud platform.
[0102] In one embodiment, the raw vibration data is transmitted to the vibration monitoring cloud platform via a wireless communication module.
[0103] In another embodiment, in application scenarios such as when a quick response is required or the network is unavailable or the network connection is unstable, the wireless communication module transmits the raw vibration data and the vibration index data obtained by real-time processing of the collected raw vibration data locally by the micro single-board computer to the vibration monitoring cloud platform.
[0104] An example of a wireless communication module is Figure 2 The wireless communication module 1103 in the vibration monitoring cloud platform is an example of Figure 1 Vibration monitoring cloud platform 120.
[0105] The technical solution provided by the present application is that the vibration sensor node is used to collect raw vibration data, and can perform real-time data processing on the raw vibration data to obtain vibration index data, and then transmit the raw vibration data and vibration index data to the vibration monitoring cloud platform in real time. In application scenarios where a quick response is required or the network is unavailable or the network connection is unstable, there is no need to transmit the raw vibration data to the vibration monitoring cloud platform for calculation of the vibration index data. Instead, the vibration sensor node processes the collected raw vibration in real time to obtain vibration index data, effectively improving the efficiency of vibration monitoring. The vibration monitoring cloud platform provides powerful analysis and computing resources, which can obtain vibration monitoring results based on the vibration index data transmitted by the vibration sensor node and a preset threshold value. At the same time, it provides a data storage function, which can store raw vibration data, vibration index data and vibration monitoring results, ensuring the security and continuous availability of the data. In addition, the vibration sensor node is built with open source hardware components, which greatly reduces the cost and enhances the scalability of the vibration monitoring system.
[0106] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other and are not used to limit the scope of protection of this application. In the above embodiments, the description of each embodiment has its own focus. For the parts that are not described or recorded in detail in a certain embodiment, please refer to the relevant description of other embodiments.
[0107] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included in the scope of protection of the present application.
Claims
1. A vibration monitoring system, characterized in that: The vibration monitoring system includes a vibration sensor node and a vibration monitoring cloud platform, wherein the vibration sensor node is installed at a location to be monitored and is communicatively connected to the vibration monitoring cloud platform; The vibration sensing node is used to collect raw vibration data, perform real-time data processing on the raw vibration data to obtain vibration index data, and transmit the raw vibration data and the vibration index data to the vibration monitoring cloud platform in real time; The vibration monitoring cloud platform is used to obtain a vibration monitoring result based on the vibration index data and a first preset threshold, and store the original vibration data, the vibration index data and the vibration monitoring result, wherein the vibration monitoring result indicates whether there is vibration index data exceeding the first preset threshold.
2. The vibration monitoring system according to claim 1, characterized in that The vibration sensing node includes a micro single board computer, a micro electromechanical system sensor, a wireless communication module and a power supply module, wherein the micro single board computer is communicatively connected to the micro electromechanical system sensor, the wireless communication module and the power supply module respectively; The micro-electromechanical system sensor is used to collect the original vibration data; The micro single-board computer is used to process the original vibration data to obtain the vibration index data; The wireless communication module is used to transmit the original vibration data and the vibration index data to the vibration monitoring cloud platform; The power supply module is used to supply power to the vibration sensor node.
3. The vibration monitoring system according to claim 2, characterized in that: The micro single-board computer includes a first data processing module and a storage module; The first data processing module is used to process the original vibration data to obtain the vibration index data; The storage module is used to store the original vibration data and the vibration index data.
4. The vibration monitoring system according to claim 3, characterized in that: The micro single-board computer further includes a watchdog timer and a first alarm module; The watchdog timer is used to monitor the network connection status between the vibration sensor node and the vibration monitoring cloud platform in real time; The first alarm module is configured to generate an alarm when the vibration sensor node is disconnected from the vibration monitoring cloud platform for a period exceeding a preset time; The wireless communication module is also used to automatically reconnect when the vibration sensing node is disconnected from the vibration monitoring cloud platform, and when the vibration sensing node is restored to the vibration monitoring cloud platform, transmit the original vibration data and vibration index data stored in the storage module, which are generated when the vibration sensing node is disconnected from the vibration monitoring cloud platform, to the vibration monitoring cloud platform.
5. The vibration monitoring system according to claim 2, characterized in that: The micro single-board computer also includes a time synchronization module; The time synchronization module is used to align the internal clock of the micro single-board computer with the reference network time.
6. The vibration monitoring system according to claim 5, characterized in that: The time synchronization module includes: an acquiring unit, configured to acquire a timestamp based on a first preset time interval within a preset period; a calculation unit, configured to calculate a mean of the absolute time offsets of the preset time period based on the timestamp; The correction unit is used to correct the internal clock of the micro single-board computer to align with the reference network time when the average value of the absolute time offset is greater than a second preset threshold.
7. The vibration monitoring system according to claim 1, characterized in that: The vibration monitoring cloud platform includes a second data processing module and a second alarm module; The second data processing module is configured to process the raw vibration data to obtain the vibration index data, and obtain the vibration monitoring result based on the vibration index data and the first preset threshold value; The second alarm module is configured to generate an alarm when the vibration index data is greater than the first preset threshold.
8. The vibration monitoring system according to claim 3 or 7, characterized in that: The raw vibration data includes raw acceleration data, and the vibration index data includes acceleration time history, peak vibration velocity, and 1 / 3 octave root mean square velocity. The first data processing module and the second data processing module are specifically configured to: Performing fast Fourier transform, bandpass filtering, and inverse fast Fourier transform on the raw acceleration data to obtain the acceleration time history; Integrating, fast Fourier transforming, bandpass filtering, and inverse fast Fourier transforming the raw acceleration data to obtain the peak vibration velocity; The raw acceleration data is integrated, fast Fourier transformed, inverse fast Fourier transformed, and 1 / 3 octave divided to obtain the 1 / 3 octave root mean square velocity.
9. The vibration monitoring system according to claim 1, characterized in that: The vibration monitoring cloud platform also includes a MySQL database and a visual interface; The MySQL database is used to partition and store the original vibration data, the vibration index data, and the vibration monitoring results according to preset storage rules, and regularly back up the original vibration data, the vibration index data, and the vibration monitoring results; The visualization interface is used for real-time data display, historical data retrieval and data export based on the MySQL database.
10. A vibration monitoring method, characterized in that: Applied to a vibration monitoring system, the method comprises: Get raw vibration data; Determining vibration index data based on the original vibration data; A vibration monitoring result is determined based on the vibration index data and a first preset threshold, where the vibration monitoring result indicates whether there is vibration index data exceeding the first preset threshold.