Structural dynamic characteristic monitoring and early warning system based on intelligent micro-seismic accelerometer

Abstract

The invention relates to the technical field of structural dynamic characteristic monitoring and early warning, in particular to a structural dynamic characteristic monitoring and early warning system based on an intelligent micro-seismic accelerometer, which comprises a sensor sensing module used for measuring an input force of the intelligent micro-seismic accelerometer based on servo balance between a feedback force and the input force; the data acquisition module is used for acquiring data information and performing data conversion based on an analog-to-digital converter; the signal analysis module is used for preprocessing the digital signal obtained by the data acquisition module; the early warning module is used for monitoring the signal characteristic variables obtained by the signal analysis module in real time and judging whether data abnormity exists or not; the display module is used for visually displaying the signal characteristic variables and the early warning signals; and the data storage module group is used for storing the data information, the signal characteristic variables and the early warning signal sending condition. According to the invention, early warning information can be sent at the first time, so that a worker can take measures in time, and the engineering safety is greatly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of structural dynamic characteristics monitoring and early warning, and in particular to a structural dynamic characteristics monitoring and early warning system based on an intelligent microseismic accelerometer. Background Art

[0002] With the continuous development of modern buildings and infrastructure, the importance of structural health monitoring has become increasingly prominent. Many critical structures, such as bridges, high-rise buildings, wind turbine towers, mines, and slopes, face complex environments and operating conditions, requiring real-time monitoring of their dynamic characteristics to ensure structural safety and reliability. Traditional structural monitoring methods typically rely on manual inspections or simple sensor monitoring. These methods suffer from inefficiency, discontinuous monitoring, and inaccurate data, making them difficult to meet the needs of modern structural health monitoring.

[0003] In recent years, with the rapid development of sensor technology, data acquisition technology, and signal processing technology, structural dynamic characteristics monitoring systems based on intelligent sensors have gradually become a research hotspot. As a high-precision, low-frequency response sensor, intelligent microseismic accelerometers can effectively capture tiny structural vibration signals, providing strong support for structural health monitoring. However, most monitoring systems currently on the market have the following shortcomings:

[0004] 1. Traditional accelerometer sensors have limitations in low-frequency response and accuracy, making it difficult to accurately measure low-frequency vibration signals and unable to meet the high-precision, wide-bandwidth requirements of structural health monitoring.

[0005] 2. Existing monitoring systems are often relatively simple in terms of signal processing and lack the ability to conduct in-depth signal analysis and feature extraction. This results in inaccurate monitoring results and makes it difficult to detect potential safety hazards in a timely manner.

[0006] 3. Many monitoring systems lack real-time early warning capabilities and are unable to issue timely alarms when structural abnormalities occur, resulting in missing the best time to deal with the situation and increasing the risk of structural damage.

[0007] 4. The existing monitoring system has defects in data storage and management. It is unable to preserve monitoring data for a long time and it is difficult to conduct comparative analysis of historical data, which limits the long-term tracking and assessment of structural health status. Summary of the Invention

[0008] The purpose of the present invention is to provide a structural dynamic characteristics monitoring and early warning system based on an intelligent microseismic accelerometer, comprising:

[0009] A sensor sensing module for measuring the input force of the smart microseismic accelerometer based on a servo balance between the feedback force and the input force;

[0010] The data acquisition module is used to collect data information, perform data conversion based on the analog-to-digital converter, and convert the electrical signal obtained by the sensor perception module into a digital signal;

[0011] The signal analysis module is used to pre-process the digital signal obtained by the data acquisition module and obtain signal characteristic variables;

[0012] The early warning module is used to monitor the signal characteristic variables obtained by the signal analysis module in real time, determine whether there are data anomalies, and issue an early warning signal when there are data anomalies;

[0013] Display module, used to visualize signal characteristic variables and warning signals;

[0014] The data storage module group is used to store data information, signal characteristic variables and the issuance of early warning signals.

[0015] In some embodiments of the present application, the sensor sensing module adopts a JBA12 zero-frequency micro-seismic accelerometer sensor, which includes a force feedback measurement device composed of mechanical components and servo circuits, and adopts force balance electronic feedback and mechatronics design to convert unidirectional vibration acceleration into a voltage signal and output it.

[0016] In some embodiments of the present application, the data acquisition module uses a data acquisition 24-bit analog-to-digital converter to perform data conversion.

[0017] In some embodiments of the present application, the signal analysis module sequentially performs filtering and spectrum analysis preprocessing on the digital signal;

[0018] Among them, filtering includes low-pass filtering, high-pass filtering, and band-pass filtering. Based on the filtering process, frequencies outside the target frequency band are removed to obtain the target filtering results; spectrum analysis includes fast Fourier transform and power spectral density analysis. Based on the spectrum analysis, the target filtering results are analyzed to obtain the frequency characteristics of the signal.

[0019] In some embodiments of the present application, the visual display content of the display module includes a toolbar, a waveform display bar, and an early warning status bar;

[0020] Among them, the toolbar includes setting the range, setting the sampling rate, sampling start and stop control, amplitude display, filter setting, and area magnification. The waveform display bar includes the time domain waveform curve and the frequency domain waveform curve. The warning status bar includes the signal sampling rate, unit, mileage, acquisition time, data abnormality, and warning status.

[0021] In some embodiments of the present application, the early warning module determines the normal interval of the signal characteristic variable based on a pre-set threshold range, monitors the signal characteristic variable in real time, compares the current signal characteristic variable with the set threshold range, and determines whether the current signal characteristic variable is in the normal interval. If the current signal characteristic variable exceeds the normal interval, it is determined that the data is abnormal and an early warning is issued. If the current signal characteristic variable does not exceed the normal interval, it is determined that the data is normal and real-time monitoring is performed at the same time.

[0022] Among them, the warning methods include sound and light warnings and interface prompt warnings. If the data abnormalities are continuously monitored for more than the preset time period during the warning period, the warning information will be remotely notified.

[0023] In some embodiments of the present application, the data storage module group includes an original data storage unit, a characteristic variable storage unit, an early warning signal storage unit, and a data backup unit;

[0024] Among them, the data storage unit is used to store the unprocessed digital signal directly obtained from the data acquisition module; the characteristic variable storage unit is used to store the signal characteristic variables obtained by the signal analysis module; the early warning signal storage unit is used to store the early warning signal issued by the early warning module; the data backup unit is used to store the data in the external storage device and cloud storage at the same time.

[0025] The advantages and beneficial effects of the present invention over the prior art are:

[0026] 1. The present invention performs filtering and spectrum analysis preprocessing on the collected digital signals, including low-pass filtering, high-pass filtering, band-pass filtering, fast Fourier transform and power spectral density analysis, which can effectively remove noise and extract the key characteristic variables of the signal.

[0027] 2. This invention can monitor signal characteristic variables in real time based on preset thresholds, quickly determine whether the data is abnormal, and promptly issue warning signals when an anomaly occurs. Through various methods such as audio and visual warnings, interface prompts, and remote notifications, users can obtain warning information immediately and take timely measures to avoid potential safety accidents.

[0028] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 Schematic diagram of a structural dynamic characteristics monitoring and early warning system based on an intelligent microseismic accelerometer in an embodiment of the present invention. DETAILED DESCRIPTION

[0030] In the description of the present invention, it should be noted that the terms "upper", "lower", "inside", "outside" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, or the orientations or positional relationships in which the inventive product is usually placed when in use. These are only for the convenience of describing the present invention and simplifying the description, and are not intended to indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, they cannot be understood as limitations on the present invention. In the description of the present invention, it should also be noted that, unless otherwise expressly specified and limited, the terms "setting", "installation" and "connection" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or an indirect connection through an intermediate medium, or it can be a communication between the internal parts of two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0031] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0032] like Figure 1 As shown, the present invention provides a structural dynamic characteristics monitoring and early warning system based on an intelligent microseismic accelerometer, comprising:

[0033] A sensor sensing module for measuring the input force of the smart microseismic accelerometer based on a servo balance between the feedback force and the input force;

[0034] The data acquisition module is used to collect data information, perform data conversion based on the analog-to-digital converter, and convert the electrical signal obtained by the sensor perception module into a digital signal;

[0035] The signal analysis module is used to pre-process the digital signal obtained by the data acquisition module and obtain signal characteristic variables;

[0036] The early warning module is used to monitor the signal characteristic variables obtained by the signal analysis module in real time, determine whether there are data anomalies, and issue an early warning signal when there are data anomalies;

[0037] Display module, used to visualize signal characteristic variables and warning signals;

[0038] The data storage module group is used to store data information, signal characteristic variables and the issuance of early warning signals.

[0039] In some embodiments of the present application, the sensor sensing module adopts a JBA12 zero-frequency micro-seismic accelerometer sensor, which includes a force feedback measurement device composed of mechanical components and servo circuits, and adopts force balance electronic feedback and mechatronics design to convert unidirectional vibration acceleration into a voltage signal and output it.

[0040] Specifically, the sensor sensing module primarily consists of the JBA12 zero-frequency microseismic accelerometer. This is a force feedback measurement device composed of mechanical components and servo circuits. It is an absolutely low-frequency accelerometer that measures input force through a servo balance between feedback and input forces. It is a single-axis, wide-bandwidth accelerometer that utilizes force balance electronic feedback and mechatronic design to convert single-axis vibration acceleration into a voltage output, enabling measurement of various low- and ultra-low-frequency vibrations. This completes the signal conversion of the physical quantity being monitored. The sensor features high precision, a high dynamic range, excellent linearity, a flat frequency response starting at 0 Hz, and a linear phase change. It also boasts consistent technical parameters, stable and reliable performance, low power consumption, and a compact size. The acquisition system enables high-precision, continuous, fully synchronized, and independent data acquisition for each channel.

[0041] In some embodiments of the present application, the data acquisition module uses a data acquisition 24-bit analog-to-digital converter to perform data conversion.

[0042] Specifically, the data acquisition module uses a high-precision data acquisition 24-bit analog-to-digital converter for data conversion, which is used to collect data information and convert the electrical signals converted by the perception layer into digital signals to facilitate data transmission.

[0043] In some embodiments of the present application, the signal analysis module sequentially performs filtering and spectrum analysis preprocessing on the digital signal;

[0044] Among them, filtering includes low-pass filtering, high-pass filtering, and band-pass filtering. Based on the filtering process, frequencies outside the target frequency band are removed to obtain the target filtering results; spectrum analysis includes fast Fourier transform and power spectral density analysis. Based on the spectrum analysis, the target filtering results are analyzed to obtain the frequency characteristics of the signal.

[0045] In some embodiments of the present application, the visual display content of the display module includes a toolbar, a waveform display bar, and an early warning status bar;

[0046] Among them, the toolbar includes setting the range, setting the sampling rate, sampling start and stop control, amplitude display, filter setting, and area magnification. The waveform display bar includes the time domain waveform curve and the frequency domain waveform curve. The warning status bar includes the signal sampling rate, unit, mileage, acquisition time, data abnormality, and warning status.

[0047] In some embodiments of the present application, the early warning module determines the normal interval of the signal characteristic variable based on a pre-set threshold range, monitors the signal characteristic variable in real time, compares the current signal characteristic variable with the set threshold range, and determines whether the current signal characteristic variable is in the normal interval. If the current signal characteristic variable exceeds the normal interval, it is determined that the data is abnormal and an early warning is issued. If the current signal characteristic variable does not exceed the normal interval, it is determined that the data is normal and real-time monitoring is performed at the same time.

[0048] Among them, the warning methods include sound and light warnings and interface prompt warnings. If the data abnormalities are continuously monitored for more than the preset time period during the warning period, the warning information will be remotely notified.

[0049] In some embodiments of the present application, the data storage module group includes an original data storage unit, a characteristic variable storage unit, an early warning signal storage unit, and a data backup unit;

[0050] Among them, the data storage unit is used to store the unprocessed digital signal directly obtained from the data acquisition module; the characteristic variable storage unit is used to store the signal characteristic variables obtained by the signal analysis module; the early warning signal storage unit is used to store the early warning signal issued by the early warning module; the data backup unit is used to store the data in the external storage device and cloud storage at the same time.

[0051] The advantages and beneficial effects of the present invention over the prior art are:

[0052] 1. The present invention performs filtering and spectrum analysis preprocessing on the collected digital signals, including low-pass filtering, high-pass filtering, band-pass filtering, fast Fourier transform and power spectral density analysis, which can effectively remove noise and extract the key characteristic variables of the signal.

[0053] 2. This invention can monitor signal characteristic variables in real time based on preset thresholds, quickly determine whether the data is abnormal, and promptly issue warning signals when an anomaly occurs. Through various methods such as audio and visual warnings, interface prompts, and remote notifications, users can obtain warning information immediately and take timely measures to avoid potential safety accidents.

[0054] In this application, unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs. In the event of any inconsistency, the meaning described in this specification or the meaning derived from the contents recorded in this specification shall prevail. In addition, the terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0055] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit the same. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solutions of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A structural dynamic characteristics monitoring and early warning system based on intelligent microseismic accelerometer, characterized by: include: A sensor sensing module for measuring the input force of the smart microseismic accelerometer based on a servo balance between the feedback force and the input force; The data acquisition module is used to collect data information, perform data conversion based on the analog-to-digital converter, and convert the electrical signal obtained by the sensor perception module into a digital signal; The signal analysis module is used to pre-process the digital signal obtained by the data acquisition module and obtain signal characteristic variables; The early warning module is used to monitor the signal characteristic variables obtained by the signal analysis module in real time, determine whether there are data anomalies, and issue an early warning signal when there are data anomalies; Display module, used to visualize signal characteristic variables and warning signals; The data storage module group is used to store data information, signal characteristic variables and the issuance of early warning signals.

2. The structural dynamic characteristics monitoring and early warning system based on the intelligent microseismic accelerometer according to claim 1 is characterized in that: The sensor perception module adopts the JBA12 zero-frequency micro-seismic accelerometer sensor, including a force feedback measurement device composed of mechanical components and servo circuits, and adopts force balance electronic feedback and mechatronics design to truly convert unidirectional vibration acceleration into a voltage signal and output it.

3. The structural dynamic characteristics monitoring and early warning system based on intelligent microseismic accelerometer according to claim 1 is characterized in that: The data acquisition module uses a 24-bit analog-to-digital converter to perform data conversion.

4. The structural dynamic characteristics monitoring and early warning system based on intelligent microseismic accelerometer according to claim 1 is characterized in that: The signal analysis module performs filtering and spectrum analysis preprocessing on the digital signal in sequence; Among them, filtering includes low-pass filtering, high-pass filtering, and band-pass filtering. Based on the filtering process, frequencies outside the target frequency band are removed to obtain the target filtering results; spectrum analysis includes fast Fourier transform and power spectral density analysis. Based on the spectrum analysis, the target filtering results are analyzed to obtain the frequency characteristics of the signal.

5. The structural dynamic characteristics monitoring and early warning system based on intelligent microseismic accelerometer according to claim 1 is characterized in that: The visual display content of the display module includes a toolbar, a waveform display bar, and an early warning status bar; Among them, the toolbar includes setting the range, setting the sampling rate, sampling start and stop control, amplitude display, filter setting, and area magnification. The waveform display bar includes the time domain waveform curve and the frequency domain waveform curve. The warning status bar includes the signal sampling rate, unit, mileage, acquisition time, data abnormality, and warning status.

6. The structural dynamic characteristics monitoring and early warning system based on intelligent microseismic accelerometer according to claim 1 is characterized in that: The early warning module determines the normal interval of the signal characteristic variable based on a pre-set threshold range, monitors the signal characteristic variable in real time, compares the current signal characteristic variable with the set threshold range, and determines whether the current signal characteristic variable is in the normal interval. If the current signal characteristic variable exceeds the normal interval, it is determined that the data is abnormal and an early warning is issued. If the current signal characteristic variable does not exceed the normal interval, it is determined that the data is normal and real-time monitoring is performed at the same time. Among them, the warning methods include sound and light warnings and interface prompt warnings. If the data abnormalities are continuously monitored for more than the preset time period during the warning period, the warning information will be remotely notified.

7. The structural dynamic characteristics monitoring and early warning system based on intelligent microseismic accelerometer according to claim 1 is characterized in that: The data storage module group includes an original data storage unit, a characteristic variable storage unit, an early warning signal storage unit, and a data backup unit; Among them, the data storage unit is used to store the unprocessed digital signal directly obtained from the data acquisition module; the characteristic variable storage unit is used to store the signal characteristic variables obtained by the signal analysis module; the early warning signal storage unit is used to store the early warning signal issued by the early warning module; the data backup unit is used to store the data in the external storage device and cloud storage at the same time.

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