High-precision building inclination angle detection method, system and equipment

Abstract

The invention discloses a high-precision building inclination angle detection method, system and equipment, and relates to the technical field of building measurement. The method comprises the following steps: the micro-control unit receives original detection data transmitted by the inertial measurement unit; the inertial measurement unit preprocesses the original detection data through multi-stage filtering to obtain optimized detection data; the inertial measurement unit performs data fusion processing on the optimized detection data to obtain a three-axis Euler angle; and after receiving the alarm threshold value sent by the micro-control unit, the inertial measurement unit outputs alarm judgment by comparing the alarm threshold value with the three-axis Euler angle. The technical problems of insufficient building inclination angle detection precision and poor anti-interference capability in the prior art are solved, and the technical effects of improving the building inclination angle detection precision and enhancing the data stability and the anti-interference capability are achieved through multi-stage filtering and data fusion processing.

Description

Technical Field

[0001] The present invention relates to the technical field of building measurement, and in particular to a high-precision building inclination detection method, system and equipment. Background Art

[0002] With the acceleration of urbanization, the number of high-rise buildings is increasing. However, due to geological disasters, soil subsidence and other factors, building tilt events occur frequently, which seriously affects the structural safety and use function of buildings. Therefore, timely and accurate monitoring of building tilt changes has become a crucial part of building safety management. At present, most of the existing tilt detection algorithms are based on accelerometers. The acceleration data of the object is collected by the accelerometer, and the three-axis acceleration value in the reference direction is used as the reference vector a (x1, y1, z1), and the real-time acceleration of the object is used as the real-time vector b (x2, y2, z2). The angle between the object and the reference direction is obtained by calculating the angle between vector a and vector b. However, the accelerometer is greatly affected by environmental noise, especially in the case of high-frequency vibration or impact, which may lead to inaccurate measurement; the accelerometer may have a bias, which causes the drift of the tilt measurement over time and requires regular calibration; the accelerometer can usually only measure the acceleration in a specific direction and cannot provide complete three-dimensional spatial information. Summary of the invention

[0003] The present application provides a high-precision building inclination detection method, system and equipment, which solve the technical problems of insufficient building inclination detection accuracy and poor anti-interference ability in the prior art.

[0004] In view of the above problems, the present application provides a high-precision building inclination detection method, system and equipment.

[0005] In a first aspect of the present application, a high-precision building inclination detection method is provided, the method comprising:

[0006] The microcontroller unit receives the original detection data transmitted by the inertial measurement unit; the inertial measurement unit preprocesses the original detection data through multi-stage filtering to obtain optimized detection data; the inertial measurement unit performs data fusion processing on the optimized detection data to obtain the three-axis Euler angle; after receiving the alarm threshold sent by the microcontroller unit, the inertial measurement unit outputs an alarm judgment by comparing the alarm threshold and the three-axis Euler angle.

[0007] A second aspect of the present application provides a high-precision building inclination detection system, the system comprising:

[0008] Data receiving module: the microcontroller unit receives the original detection data transmitted by the inertial measurement unit; preprocessing module: the inertial measurement unit preprocesses the original detection data through multi-stage filtering to obtain optimized detection data; fusion processing module: the inertial measurement unit performs data fusion processing on the optimized detection data to obtain the three-axis Euler angle; early warning module: after the inertial measurement unit receives the alarm threshold sent by the microcontroller unit, it outputs an alarm judgment by comparing the alarm threshold and the three-axis Euler angle.

[0009] The third aspect of the present application provides a high-precision building inclination detection device, including: an inertial measurement unit; a micro control unit, wherein the micro control unit and the inertial measurement unit are connected via an SPI bus.

[0010] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0011] First, the microcontroller unit receives the original detection data transmitted by the inertial measurement unit. Next, the inertial measurement unit preprocesses the original detection data through multi-stage filtering to obtain optimized detection data. Then, the inertial measurement unit performs data fusion processing on the optimized detection data to obtain the three-axis Euler angle. Finally, after the inertial measurement unit receives the alarm threshold sent by the microcontroller unit, it outputs the alarm judgment by comparing the alarm threshold and the three-axis Euler angle. The technical problems of insufficient building inclination detection accuracy and poor anti-interference ability in the prior art are solved. Through multi-stage filtering and data fusion processing, the technical effect of improving the building inclination detection accuracy, enhancing data stability and anti-interference ability is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. 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 creative work.

[0013] Figure 1 A schematic diagram of a high-precision building inclination detection method flow chart provided in an embodiment of the present application;

[0014] Figure 2 A schematic diagram of the structure of a high-precision building inclination detection system provided in an embodiment of the present application.

[0015] Explanation of the reference numerals: data receiving module 11 , preprocessing module 12 , fusion processing module 13 , early warning module 14 . DETAILED DESCRIPTION

[0016] The present application solves the technical problems of insufficient building inclination detection accuracy and poor anti-interference ability in the prior art by providing a high-precision building inclination detection method, system and equipment.

[0017] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0018] It should be noted that the terms "including" and "having" are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules that are not explicitly listed or are inherent to these processes, methods, products or devices.

[0019] Embodiment 1, as Figure 1 As shown, the present application provides a high-precision building inclination detection method, wherein the method includes:

[0020] The micro control unit receives the raw detection data transmitted by the inertial measurement unit.

[0021] The inertial measurement unit collects the motion data of the building in real time through built-in sensors (such as accelerometers, gyroscopes, etc.), including physical quantities such as acceleration and angular velocity. The microcontroller unit (MCU) communicates with the inertial measurement unit (IMU) through SPI and receives the raw detection data transmitted from the inertial measurement unit.

[0022] Furthermore, before the microcontroller unit receives the raw detection data transmitted by the inertial measurement unit, the method includes:

[0023] The building data is collected by the six-axis gyroscope module in the inertial measurement unit to obtain the original angular velocity information; the building data is collected by the accelerometer module in the inertial measurement unit to obtain the original acceleration data; the inertial measurement unit uses the original angular velocity information and the original acceleration data as the original detection data and transmits them to the micro control unit through the SPI bus.

[0024] The six-axis gyroscope module in the inertial measurement unit is used to collect building data to obtain raw angular velocity information, which reflects the rotational movement of the building in three-dimensional space; the accelerometer module in the inertial measurement unit is used to collect building data to obtain raw acceleration data, which provides acceleration information of the building in three axes and is used to analyze tilt changes; the raw angular velocity information and acceleration data collected above are used as raw detection data and transmitted to a microcontroller unit (MCU) through an SPI bus, wherein the SPI bus, as a high-speed serial communication interface, ensures efficient transmission of data between the inertial measurement unit and the microcontroller unit.

[0025] The inertial measurement unit preprocesses the original detection data through multi-stage filtering to obtain optimized detection data.

[0026] The inertial measurement unit pre-processes the raw detection data through multi-stage filtering to reduce noise interference and improve the accuracy and stability of the data. Multi-stage filtering usually includes low-pass filtering and Kalman filtering. Among them, low-pass filtering: by removing high-frequency noise, ensure that the collected data can more accurately reflect the real dynamic changes of the building; Kalman filtering: combining the data of multiple sensors to perform weighted averaging on the raw information, optimize the accuracy of the signal, and reduce system errors.

[0027] Through multi-stage filtering processing, the inertial measurement unit obtains optimized detection data, providing a more accurate and clean data basis for subsequent calculations.

[0028] Furthermore, the inertial measurement unit preprocesses the raw detection data through multi-stage filtering to obtain optimized detection data, and the method includes:

[0029] A low-pass filtering algorithm is used to perform a first layer of filtering on the original detection data to remove high-frequency noise and smooth the data to obtain first filtered data; Kalman filtering is performed on the first filtered data to eliminate deviation and drift to obtain the optimized detection data, wherein the optimized detection data includes optimized angular velocity information and optimized acceleration data.

[0030] Specifically, a low-pass filtering algorithm is used to perform the first layer of filtering on the original detection data in order to remove high-frequency noise and smooth the data. Low-pass filtering can effectively eliminate rapidly changing signals caused by environmental interference or sensor errors, obtain the first filtered data, and provide cleaner basic data for subsequent processing; the first filtered data is processed by Kalman filtering. Kalman filtering can eliminate errors caused by system deviations and measurement drift in the process of multi-source data fusion, making the data more accurate and stable. Through Kalman filtering processing, the optimized detection data includes corrected angular velocity information and acceleration data. These optimized data are closer to the actual motion state of the building.

[0031] The inertial measurement unit performs data fusion processing on the optimized detection data to obtain three-axis Euler angles.

[0032] The inertial measurement unit performs data fusion processing on the optimized detection data, that is, the angular velocity and acceleration data after low-pass filtering and Kalman filtering optimization are fused to obtain the three-axis Euler angle. The three-axis Euler angle represents the tilt and rotation of the building relative to the reference coordinate system in three-dimensional space, where the roll angle represents the rotation of the building around the X-axis, the pitch angle represents the rotation of the building around the Y-axis, and the yaw angle represents the rotation of the building around the Z-axis.

[0033] Furthermore, the inertial measurement unit performs data fusion processing on the optimized detection data to obtain the three-axis Euler angle, and the method includes:

[0034] The optimized angular velocity information is integrated to obtain an angle change; the optimized acceleration data is tilted to obtain an X-axis tilt angle and a Y-axis tilt angle; and a six-axis fusion algorithm is used to perform data fusion processing on the angle change, the X-axis tilt angle and the Y-axis tilt angle to obtain the three-axis Euler angle.

[0035] Specifically, the optimized angular velocity information is integrated and calculated. Through the integration process, the angular velocity data is converted into angle changes, reflecting the rotation changes of the building on each axis, thereby obtaining the angle changes; the optimized acceleration data is subjected to inclination angle calculation, and the acceleration values ​​of the accelerometer data in the three-axis direction can be used to calculate the degree of inclination of the building relative to the direction of gravity, thereby obtaining the inclination angles on the X-axis and Y-axis, and obtaining the X-axis inclination angle and the Y-axis inclination angle; the six-axis fusion algorithm (Madgwick or Mahony algorithm) is applied to perform data fusion processing on the angle change, the X-axis inclination angle and the Y-axis inclination angle. The six-axis fusion algorithm combines angular velocity information and acceleration information, optimizes data in a complementary manner, and ensures that more accurate and stable three-axis Euler angles are obtained. The three-axis Euler angles include pitch angle, roll angle and yaw angle.

[0036] After receiving the alarm threshold sent by the micro control unit, the inertial measurement unit outputs an alarm judgment by comparing the alarm threshold and the three-axis Euler angle.

[0037] The inertial measurement unit receives the alarm threshold information sent by the microcontroller unit. The alarm threshold includes a preset maximum tilt angle or rotation angle. When the alarm threshold is exceeded, an early warning will be triggered. The inertial measurement unit compares the received alarm threshold with the calculated three-axis Euler angle. Specifically, it compares the difference between the current tilt angle of the building (i.e., the three-axis Euler angle) and the preset alarm threshold. If a value of the three-axis Euler angle exceeds the set threshold range, it means that the building may have a safety hazard. When the comparison result shows that the three-axis Euler angle exceeds the alarm threshold, the inertial measurement unit outputs an alarm signal to notify the microcontroller unit for further processing or trigger other safety measures.

[0038] Furthermore, after the inertial measurement unit receives the alarm threshold sent by the micro control unit, it outputs an alarm judgment by comparing the alarm threshold and the three-axis Euler angle, and the method includes:

[0039] The microcontrol unit constructs a Modbus frame by initiating a communication request, wherein the Modbus frame includes a device address, a function code and a data field, and the function code includes the alarm threshold; the microcontrol unit sends the Modbus frame to the inertial measurement unit through the RS-485 protocol and the ModBus protocol; after receiving the alarm threshold, the inertial measurement unit compares the data with the three-axis Euler angle to determine whether the alarm condition is met and outputs an alarm judgment; if the alarm judgment is that the three-axis Euler angle does not meet the alarm threshold, the inertial measurement unit generates an alarm signal, and transmits the alarm signal back to the microcontroller unit through the RS-485 protocol and the ModBus protocol.

[0040] Specifically, the microcontroller unit constructs a Modbus frame by initiating a communication request. The Modbus frame includes a device address, a function code, and a data field. The function code contains alarm threshold information. The Modbus frame is a standardized communication protocol format used to transmit control instructions and data between devices. The microcontroller unit sends the constructed Modbus frame to the inertial measurement unit through the RS-485 protocol and the Modbus protocol. The RS-485 protocol provides stable multi-point communication capabilities, which is suitable for long-distance data transmission in industrial automation systems, ensuring that the alarm threshold can be accurately and efficiently transmitted to the Inertial measurement unit; after receiving the alarm threshold, the inertial measurement unit compares the value with the three-axis Euler angle calculated in real time, and compares the difference between the inclination angle of the building (i.e., the three-axis Euler angle) and the preset alarm threshold. If one dimension of the three-axis Euler angle exceeds the alarm threshold, it means that there is a potential safety risk in the building; if the three-axis Euler angle does not meet the alarm threshold (i.e., the inclination angle of the building is too large), the inertial measurement unit will generate an alarm signal, indicating that the building is abnormally tilted; the alarm signal is transmitted back to the microcontroller unit via the RS-485 protocol and Modbus protocol, notifying the system to process it or trigger other safety measures.

[0041] Furthermore, the micro control unit receives and triggers an alarm according to the alarm signal.

[0042] The microcontroller unit receives the alarm signal sent back by the inertial measurement unit through the RS-485 protocol and the Modbus protocol. The alarm signal indicates that the tilt angle of the building exceeds the preset alarm threshold and there is a potential safety hazard. Based on the received alarm signal, the microcontroller unit immediately starts the alarm program.

[0043] In summary, the embodiments of the present application have at least the following technical effects:

[0044] First, the microcontroller unit receives the original detection data transmitted by the inertial measurement unit. Next, the inertial measurement unit preprocesses the original detection data through multi-stage filtering to obtain optimized detection data. Then, the inertial measurement unit performs data fusion processing on the optimized detection data to obtain the three-axis Euler angle. Finally, after the inertial measurement unit receives the alarm threshold sent by the microcontroller unit, it outputs the alarm judgment by comparing the alarm threshold and the three-axis Euler angle. The technical problems of insufficient building inclination detection accuracy and poor anti-interference ability in the prior art are solved. Through multi-stage filtering and data fusion processing, the technical effect of improving the building inclination detection accuracy, enhancing data stability and anti-interference ability is achieved.

[0045] Embodiment 2, based on the same inventive concept as the high-precision building inclination detection method in the above embodiment, Figure 2As shown, the present application provides a high-precision building inclination detection system, wherein the system includes:

[0046] Data receiving module 11: the micro control unit receives the original detection data transmitted by the inertial measurement unit; pre-processing module 12: the inertial measurement unit pre-processes the original detection data through multi-stage filtering to obtain optimized detection data; fusion processing module 13: the inertial measurement unit performs data fusion processing on the optimized detection data to obtain the three-axis Euler angle; early warning module 14: after the inertial measurement unit receives the alarm threshold sent by the micro control unit, it outputs an alarm judgment by comparing the alarm threshold and the three-axis Euler angle.

[0047] Furthermore, the data receiving module 11 is used to execute the following method:

[0048] The building data is collected by the six-axis gyroscope module in the inertial measurement unit to obtain the original angular velocity information; the building data is collected by the accelerometer module in the inertial measurement unit to obtain the original acceleration data; the inertial measurement unit uses the original angular velocity information and the original acceleration data as the original detection data and transmits them to the micro control unit through the SPI bus.

[0049] Furthermore, the preprocessing module 12 is used to perform the following method:

[0050] A low-pass filtering algorithm is used to perform a first layer of filtering on the original detection data to remove high-frequency noise and smooth the data to obtain first filtered data; Kalman filtering is performed on the first filtered data to eliminate deviation and drift to obtain the optimized detection data, wherein the optimized detection data includes optimized angular velocity information and optimized acceleration data.

[0051] Furthermore, the fusion processing module 13 is used to perform the following method:

[0052] The optimized angular velocity information is integrated to obtain an angle change; the optimized acceleration data is tilted to obtain an X-axis tilt angle and a Y-axis tilt angle; and a six-axis fusion algorithm is used to perform data fusion processing on the angle change, the X-axis tilt angle and the Y-axis tilt angle to obtain the three-axis Euler angle.

[0053] Furthermore, the early warning module 14 is used to execute the following method:

[0054] The microcontrol unit constructs a Modbus frame by initiating a communication request, wherein the Modbus frame includes a device address, a function code and a data field, and the function code includes the alarm threshold; the microcontrol unit sends the Modbus frame to the inertial measurement unit through the RS-485 protocol and the ModBus protocol; after receiving the alarm threshold, the inertial measurement unit compares the data with the three-axis Euler angle to determine whether the alarm condition is met and outputs an alarm judgment; if the alarm judgment is that the three-axis Euler angle does not meet the alarm threshold, the inertial measurement unit generates an alarm signal, and transmits the alarm signal back to the microcontroller unit through the RS-485 protocol and the ModBus protocol.

[0055] Furthermore, the early warning module 14 is used to execute the following method:

[0056] The micro control unit receives and triggers an alarm according to the alarm signal.

[0057] Embodiment three, a kind of high-precision building inclination detection equipment, comprises an inertial measurement unit (IMU) and a microcontroller unit (MCU). The microcontroller unit and the inertial measurement unit are connected via an SPI bus, and bidirectional communication is performed via the RS-485 protocol and the ModBus protocol. The inertial measurement unit comprises a six-axis gyroscope module and an accelerometer module, which are respectively used to collect the angular velocity and acceleration data of the building. The RS-485 protocol is a serial communication standard of the physical layer, and transmits data via differential signals. However, since the microcontroller unit uses a TTL signal and does not directly comply with the RS-485 standard, a TTL to RS-485 converter is used to convert the TTL signal into a differential signal of RS-485, and then the data is transmitted on the AB line. At the same time, the ModBus protocol, as a serial communication protocol of the transport layer, can perform CRC check during data transmission to ensure the reliability and integrity of data transmission. During the communication process, the microcontroller unit initiates a communication request and constructs a Modbus frame, which contains a device address, a function code (such as information such as an alarm threshold) and a data field. Then, the microcontroller sends the constructed ModBus frame to the inertial measurement unit through the RS-485 protocol. After receiving the request, the inertial measurement unit processes the relevant information and returns a response frame, which contains alarm information, such as the tilt angle offset data on the X-axis and Y-axis. After receiving the response frame, the microcontroller parses the data and verifies the integrity of the data through CRC check to ensure accurate transmission of information.

[0058] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0059] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

[0060] This specification and drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these modifications and variations.

Claims

1. A high-precision building inclination detection method, characterized in that: The method comprises: The micro control unit receives the raw detection data transmitted by the inertial measurement unit; The inertial measurement unit preprocesses the raw detection data through multi-stage filtering to obtain optimized detection data; The inertial measurement unit performs data fusion processing on the optimized detection data to obtain three-axis Euler angles; After receiving the alarm threshold sent by the micro control unit, the inertial measurement unit outputs an alarm judgment by comparing the alarm threshold and the three-axis Euler angle.

2. A high-precision building inclination detection method as claimed in claim 1, characterized in that: Before the microcontroller unit receives the raw detection data transmitted by the inertial measurement unit, the method includes: The six-axis gyroscope module in the inertial measurement unit is used to collect building data and obtain the original angular velocity information; The building data is collected through the accelerometer module in the inertial measurement unit to obtain the original acceleration data; The inertial measurement unit uses the original angular velocity information and the original acceleration data as the original detection data and transmits them to the micro control unit through the SPI bus.

3. A high-precision building inclination detection method as claimed in claim 2, characterized in that: The inertial measurement unit preprocesses the original detection data through multi-stage filtering to obtain optimized detection data, and the method includes: Performing a first-layer filtering on the raw detection data using a low-pass filtering algorithm to remove high-frequency noise and smooth the data, thereby obtaining first filtered data; The first filtered data is subjected to Kalman filtering to eliminate deviation and drift, thereby obtaining the optimized detection data, wherein the optimized detection data includes optimized angular velocity information and optimized acceleration data.

4. A high-precision building inclination detection method as claimed in claim 3, characterized in that: The inertial measurement unit performs data fusion processing on the optimized detection data to obtain three-axis Euler angles, and the method includes: Integrating the optimized angular velocity information to obtain an angle change; Calculating the tilt angle of the optimized acceleration data to obtain the X-axis tilt angle and the Y-axis tilt angle; A six-axis fusion algorithm is applied to perform data fusion processing on the angle variation, the X-axis tilt angle and the Y-axis tilt angle to obtain the three-axis Euler angle.

5. A high-precision building inclination detection method as claimed in claim 1, characterized in that: After the inertial measurement unit receives the alarm threshold sent by the micro control unit, it outputs an alarm judgment by comparing the alarm threshold and the three-axis Euler angle. The method includes: The micro control unit constructs a Modbus frame by initiating a communication request, wherein the Modbus frame includes a device address, a function code and a data field, and the function code includes the alarm threshold; The microcontroller unit sends the Modbus frame to the inertial measurement unit via RS-485 protocol and ModBus protocol; After receiving the alarm threshold, the inertial measurement unit compares the data with the three-axis Euler angle to determine whether the alarm condition is met and outputs an alarm judgment; If the alarm is determined to be that the three-axis Euler angles do not meet the alarm threshold, the inertial measurement unit generates an alarm signal and transmits the alarm signal back to the micro control unit via the RS-485 protocol and the ModBus protocol.

6. A high-precision building inclination detection method as claimed in claim 5, characterized in that: The micro control unit receives and triggers an alarm according to the alarm signal.

7. A high-precision building inclination detection system, characterized in that: A high-precision building inclination detection method for implementing any one of claims 1 to 6, the system comprising: Data receiving module: The microcontroller unit receives the original detection data transmitted by the inertial measurement unit; Preprocessing module: the inertial measurement unit preprocesses the original detection data through multi-stage filtering to obtain optimized detection data; Fusion processing module: the inertial measurement unit performs data fusion processing on the optimized detection data to obtain the three-axis Euler angle; Early warning module: After receiving the alarm threshold sent by the micro control unit, the inertial measurement unit outputs an alarm judgment by comparing the alarm threshold and the three-axis Euler angle.

8. A high-precision building inclination detection device, characterized in that: The device comprises: Inertial measurement unit; The micro control unit is connected to the inertial measurement unit via an SPI bus.

9. A high-precision building inclination detection device as claimed in claim 8, characterized in that: The micro control unit and the inertial measurement unit communicate bidirectionally via RS-485 protocol and ModBus protocol.

10. A high-precision building inclination detection device as claimed in claim 8, characterized in that: The inertial measurement unit includes a six-axis gyroscope module and an accelerometer module.

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