Method, device and equipment for emergency monitoring deformation of collapsed buildings at earthquake rescue sites

Abstract

The present invention belongs to the technical field of earthquake monitoring and early warning, and discloses an emergency monitoring method, device and equipment for earthquake collapsed building deformation. The method mainly utilizes an all-weather, real-time and high-precision GNSS RTK / MEMS-IMU combined sensor to obtain original GNSS and IMU observation data, and performs dual-antenna GNSS attitude measurement to assist IMU rapid alignment. After alignment, a dual-antenna GNSS / MEMS-IMU combined rapid positioning attitude measurement algorithm is used to obtain the attitude, speed and position information of the carrier, and then a vibration signal extraction method under high background noise is used to monitor the building deformation monitoring and corresponding time information in real time. When the deformation amount exceeds a threshold, a warning is issued in time to notify relevant personnel to take protective measures in time, and further completes the design and development, rapid deployment and networking monitoring of emergency monitoring terminals, thereby meeting the needs of rapid installation, signal extraction and real-time monitoring at the rescue site, and providing safety protection for rescue personnel.

Description

Technical Field

[0001] The present invention belongs to the technical field of earthquake monitoring and early warning, and in particular relates to a method, device and equipment for emergency monitoring deformation of earthquake collapsed buildings. Background Art

[0002] Earthquake disasters are inevitable natural disasters in any country or region. They not only cause property losses, changes in living environments, but also casualties. my country is located at the collision and compression of the Eurasian Plate and the Indian and Pacific Plates, and is located in an earthquake zone. Since the 21st century, mainland my country and its surrounding areas have entered a relatively active period of earthquakes, with a significantly larger distribution range and a significantly higher frequency of earthquakes. In the past decade, two earthquakes of magnitude 8.0 or above have occurred, including the 2008 Wenchuan earthquake, which caused 69,227 deaths, 374,643 injuries, and 17,923 missing persons. There are frequent aftershocks at the earthquake site, and the life channels in the collapsed buildings are at risk of further collapse at any time. There is currently no effective monitoring method. Traditional deformation monitoring equipment cannot meet the needs of rapid installation, signal extraction, and real-time monitoring at the rescue site. Earthquakes seriously threaten the safety and use of buildings in earthquake-stricken areas. Especially after an earthquake, the basic structure of the building may be damaged and may collapse at any time. It is of great significance to monitor the deformation of buildings after an earthquake, grasp the deformation development trend of buildings, ensure the safety of rescue personnel, and seek further rescue and treatment solutions.

[0003] GNSS (Global Navigation Satellite System)-RTK (Real Time Kinematic) positioning, as an emerging space measurement technology, is widely used in communication, transportation, electricity, geological exploration, navigation and mapping, disaster monitoring and other fields, especially in the fields of bridge, dam and high slope monitoring, where it has played a great advantage. However, although GNSS has wide coverage, good real-time performance, and positioning error does not accumulate over time, it cannot meet the requirements of anti-interference and dynamic tracking at the same time, and is easily blocked and interfered with, and has a low data update rate. MEMS (Micro-Electro-Mechanical System)-IMU (Inertial Measurement Unit), as an inertial measurement unit based on MEMS technology composed of silicon micro gyroscopes and accelerometers, has the advantages of good autonomy and strong anti-interference ability, can be mass-produced, low cost, small size, easy to carry, and has broad application prospects. However, MEMS-IMU has the disadvantages of increasing accumulated errors over time and reducing positioning accuracy. Therefore, relying solely on a single navigation and positioning method can no longer meet the needs of high-precision, real-time tracking navigation and positioning. It is necessary to establish a reasonable dynamic model to integrate the two to form complementary advantages, thereby providing a new idea and method for the field of emergency monitoring of building collapse.

[0004] The shortcomings and problems of the prior art mainly include the following aspects:

[0005] 1) Limitations of a single technology: As mentioned above, single GNSS or MEMS-IMU technology has certain limitations, such as GNSS is easily blocked and interfered, the data update rate is low, and the MEMS-IMU positioning accuracy accumulates errors over time. These limitations make it difficult for a single technology to meet the needs of high-precision, real-time tracking of building deformation monitoring after an earthquake.

[0006] 2) Insufficient data fusion: Although there have been studies on the fusion of GNSS and MEMS-IMU data, most of them use simple data fusion methods, such as weighted averaging. This method cannot fully utilize the advantages of the two technologies, resulting in low accuracy and real-time performance of the fused data.

[0007] 3) Poor anti-interference ability: The post-earthquake environment is complex and changeable, and there may be various signal interferences and obstructions. The existing technology is still insufficient in anti-interference ability and is easily affected by the external environment, which reduces the monitoring accuracy.

[0008] 4) Insufficient dynamic tracking performance: During the deformation monitoring of buildings after an earthquake, sudden and instantaneous large deformations may occur. The existing technology has limited performance in dynamic tracking and is difficult to meet monitoring needs.

[0009] 5) System scalability and universality: The scenarios of building deformation monitoring after an earthquake are diverse, and strong scalability and universality are required. Existing technologies still need to be improved in this regard and may not be able to adapt to the needs of different scenarios.

[0010] In summary, the existing technology has certain limitations in monitoring building deformation after an earthquake, and more advanced and efficient methods and technologies need to be studied to better meet the monitoring needs in terms of high precision, real-time, anti-interference, and dynamic tracking. Summary of the invention

[0011] In view of the problems existing in the prior art, the present invention provides a method, device and equipment for emergency monitoring deformation of collapsed buildings due to earthquakes.

[0012] The present invention is implemented as follows: an emergency monitoring method for earthquake collapsed building deformation uses an all-weather, real-time, high-precision GNSS RTK / MEMS-IMU combined sensor to obtain original GNSS and IMU observation data, performs dual-antenna GNSS attitude measurement to assist IMU rapid alignment, and after alignment, uses a dual-antenna GNSS / MEMS-IMU combined rapid positioning attitude measurement algorithm to obtain the carrier's attitude, speed and position information, and then uses a vibration signal extraction method under high background noise to monitor building deformation monitoring and corresponding time information in real time. When the deformation amount exceeds a threshold, a warning is issued in time to notify relevant personnel to take protective measures in time.

[0013] Furthermore, the method for realizing dual-antenna GNSS / IMU fast combined positioning and attitude measurement comprises the following steps:

[0014] In the first step, the GNSS pseudorange and carrier phase observation equations can be written as:

[0015]

[0016]

[0017] Where j is the observation frequency used, P is the pseudorange observation value, φ is the carrier phase observation value, λ is the carrier wavelength, ρ is the satellite-to-ground geometric distance, and dt r and dt s are the receiver clock error and satellite clock error respectively, T is the tropospheric delay, I is the ionospheric delay, d r and d s are the code hardware delays of the receiver and the satellite, δ r and δ s are the carrier phase hardware delays of the receiver and satellite, ω r and ω sare the initial phase values ​​of the receiver and the satellite, respectively, N is the undifferenced integer ambiguity, e and ε are the pseudorange and carrier phase observation noises (including unmodeled errors such as multipath), respectively;

[0018] In the second step, before performing RTK solution, it is necessary to construct a double-difference observation equation. Each system GNSS observation value selects an independent reference satellite to ensure the integer characteristics of the double-difference ambiguity. Under the condition of short baseline synchronous observation, after double-difference between satellites within the system, errors related only to the receiver and only to the satellite (such as clock error, hardware delay, initial phase value of carrier phase) are completely eliminated, and ionospheric delay and tropospheric delay are also basically eliminated and can be ignored. Therefore, the double-difference observation equation constructed by the receiver r and b and the satellite s and k can be expressed as:

[0019]

[0020]

[0021] In the formula, is a double difference operator, which calculates the approximate coordinates of the satellite from the broadcast ephemeris and The approximate coordinates of the base station and the mobile station are known to be and Linearize equations (1-3) and (1-4), and ignore the influence of satellite coordinate and reference station coordinate errors, then the double difference observation equations of pseudorange and carrier phase can be written as:

[0022]

[0023]

[0024] In the formula, is the satellite-to-ground geometric distance calculated from the approximate coordinates of the satellite and receiver, u r is the direction cosine from the receiver to the satellite, Δr is the baseline component correction; from equations (1-5) and (1-6), it can be seen that the parameters to be estimated are only the three-dimensional baseline vector correction and the double-difference integer ambiguity; using the least squares method or Kalman filtering algorithm, the real number solution of the double-difference ambiguity can be obtained and its covariance matrix Construct the following objective function:

[0025]

[0026] Where N is the double difference ambiguity integer solution. The ambiguity search is performed using the Least Square Ambiguity Decorrelation Adjustment (LAMBDA) method, and the Ratio test method is used to confirm the ambiguity:

[0027]

[0028] When Ratio is greater than 2, the fixed ambiguity is an integer solution N, and a high-precision three-dimensional baseline vector solution can be obtained;

[0029] The third step is to complete the initialization of the dual-antenna GNSS attitude measurement assisted inertial navigation. The dual-antenna GNSS attitude measurement can provide external attitude information, especially improve the observability of the heading angle. Once the dual-antenna GNSS correctly fixes the ambiguity, the accurate antenna baseline vector can be obtained, so that the heading angle and pitch angle can be calculated:

[0030]

[0031]

[0032] For the emergency monitoring of collapsed building deformation at earthquake rescue sites, it is assumed that when the equipment is just fixed to the building, the building is in a quasi-static state. The roll angle can be calculated based on the leveling principle of the static base accelerometer, and the heading angle and pitch angle can be obtained by using the dual-antenna GNSS attitude measurement. At this time, the coarse alignment process can be completed, and then the Kalman filter is used for fine alignment, and the heading angle and pitch angle obtained by the dual-antenna GNSS attitude measurement are fused into the filter model as virtual observation values, and finally the rapid initialization of inertial navigation assisted by the dual-antenna GNSS attitude measurement can be realized;

[0033] The fourth step is to perform GNSS RTK / MEMS-IMU combined attitude measurement and positioning; select n system as the navigation system, and the state equation of the navigation parameters can be expressed as:

[0034]

[0035] In the formula, and φ are position error, velocity error and misalignment angle respectively; f b and δf b denote specific force and specific force error respectively; is the gyroscope angular rate error; δg n Indicates gravity error; Represents the coordinate transformation matrix from b system to n system. Based on the state equation, time can be updated:

[0036]

[0037]

[0038] In the formula, and They represent the estimated values ​​of the state parameters and the covariance matrix at epoch k-1 respectively; and They represent the predicted values ​​of the state parameters at epoch k and the corresponding covariance matrix respectively; Φ k,k-1 Represents the state transition matrix from epoch k-1 to epoch k;

[0039] Furthermore, after considering the GNSS arm correction, the loose combined measurement model is expressed as follows:

[0040]

[0041] in

[0042]

[0043]

[0044] In the formula, and represents the GNSS position and velocity vector; [ε p ε v ] T Represents the position and velocity errors, and its corresponding variance matrix is ​​R k ; l b H is the GNSS arm correction; k is the design matrix; Z k is the new information vector; based on the observation equation, the measurement update can be performed:

[0045]

[0046]

[0047]

[0048] After data preprocessing, GNSS performs RTK solution and outputs positioning results. After mechanical arrangement, MEMS-IMU outputs dead reckoning results. After the two types of measurement information are synchronized in time and space, they enter the loose combination filter to form a closed-loop correction for the MEMS-IMU and output the combined positioning result.

[0049] Furthermore, the vibration signal extraction method under high background noise mainly includes:

[0050] The first step is to use the building vibration time series as the building vibration signal, taking into account the sampling theorem and Fourier transform, and setting the cutoff frequency of the low-pass filter according to the Fourier spectrum to initially eliminate the high-frequency background noise in the building vibration signal;

[0051] In the second step, after the initial filtering, the start and end time of the vibration signal is determined based on the prior noise of the static state monitoring signal as the threshold, and the time sequence of the vibration signal after triggering is mapped to the time-frequency domain using continuous wavelet transform to obtain the time-frequency diagram of the building vibration signal;

[0052] The third step is to identify the time-frequency area where the earthquake natural disaster affects the building in the time-frequency diagram, and use the inverse wavelet transform to restore the waveform of the building vibration signal to obtain a relatively pure building vibration signal. Finally, use wavelet spectrum analysis to extract the characteristic information (static offset, signal amplitude, etc.) of the building vibration signal caused by the natural earthquake;

[0053] Further, the third step specifically includes:

[0054] High-frequency background noise preprocessing method

[0055] The Nyquist sampling theorem states that in order to restore the original signal from the sampled signal without distortion, the sampling frequency should be greater than twice the highest frequency of the signal. If the sampling frequency is less than twice the highest frequency of the spectrum, the spectrum of the signal will be aliased. According to this theorem, it can be pointed out that the highest cutoff frequency of the low-pass filter of the building vibration signal is half of the sampling frequency. The building vibration signal is Fourier transformed to obtain the Fourier spectrum of the signal, and the cutoff frequency of the low-pass filter is designed to eliminate the high-frequency background noise in the building vibration signal for the first time.

[0056] Vibration signal feature extraction method

[0057] Since the clutter around the building will affect the building vibration signal, if it is not removed, it will not be able to accurately reflect the degree of damage to the building caused by the earthquake. Therefore, the continuous wavelet transform is used to map the building vibration signal to the time-frequency domain, and the inaction method or inverse wavelet transform is used to extract and restore the building vibration signal; the building vibration signal f(t) in any L2(R) space is expanded under the wavelet basis, which is the continuous wavelet transform of the vibration signal f(t), and its expression is:

[0058]

[0059] Among them, ψ a,τ (t) shall meet the following requirements:

[0060]

[0061] The preprocessed building vibration signal is mapped to the time-frequency domain using the continuous wavelet transform described in the above formula to obtain the characteristic information of the building vibration signal;

[0062] The admissible conditions for the inverse continuous wavelet transform are:

[0063]

[0064] The formula for its inverse transformation is:

[0065]

[0066] The waveform f(t) of the building vibration signal after noise elimination is restored by using the inaction principle or the above wavelet inverse transform formula under permissible conditions.

[0067] Furthermore, the design and development of the earthquake collapse emergency monitoring terminal and the rapid deployment and networking monitoring steps are as follows:

[0068] The first step is that data communication is the premise for ensuring the stable operation of the monitoring terminal and the continuous output of positioning solution results. According to the actual application environment, generally, on the premise of ensuring the communication quality, a data communication method that is easy to maintain and economical is selected;

[0069] In the second step, the developed terminal mainly includes dual-antenna GNSS module, MEMS-IMU module, 4G communication module, radio module, processor, data storage module, power module, interface, indicator light, etc.;

[0070] The third step is to customize a shell that can be embedded with the terminal and GNSS dual antennas according to the shape and size of the earthquake collapsed building deformation emergency monitoring terminal and the GNSS antenna. Strong adhesive patches are placed on the bottom and sides of the shell. After the outer skin of the strong adhesive patches is torn off, the shell can be quickly pasted on the roof, wall, beam and column on the top of the earthquake collapsed building by drones, robots or manual labor, so as to realize the rapid deployment of the earthquake collapsed building deformation emergency monitoring terminal.

[0071] The fourth step is to carry out the overall design of the server. The base station is deployed outside the rescue operation range of the collapsed body, and the observation data is sent to the terminal through the server communication module. After receiving the observation data, the terminal completes the solution and transmits the solved acceleration, velocity, displacement and attitude data back to the server. The server software completes vibration signal extraction, early warning and visualization.

[0072] Furthermore, the terminal developed in the second step adopts an integrated design to tightly integrate the above modules, and through the effective cooperation of software and hardware, achieves:

[0073] 1) Collection and storage of GPS L1 / L2, GLONASS L1 / L2, GALILEO E1 / E5a, BDS B1 / B3 observation data and high sampling rate (100Hz or even 200Hz) angular velocity and acceleration data;

[0074] 2) Perform attitude measurement based on dual-antenna GNSS observations and combine initial static constraints to achieve fast initial alignment of inertial navigation;

[0075] 3) Obtain the GNSS observation values ​​of the base station through 4G or radio communication, perform GNSS RTK solution, and combine the MEMS-IMU angular velocity and acceleration data to achieve GNSS RTK / MEMS-IMU combined positioning and attitude determination.

[0076] Another object of the present invention is to provide an earthquake collapsed building deformation emergency monitoring system for implementing the earthquake collapsed building deformation emergency monitoring method, the system comprising:

[0077] Combined positioning and attitude measurement module, used to realize dual-antenna GNSS attitude measurement to assist inertial navigation rapid initialization, real-time solution of high-precision attitude, displacement and velocity results, applied to earthquake collapse monitoring and early warning fields;

[0078] The vibration signal extraction module uses modern time-frequency analysis technology and combines it with the optimization calculation method to accurately and efficiently extract building vibration signals under strong noise backgrounds. It can be used to assess the impact of earthquakes and aftershocks on buildings, set reasonable thresholds, and issue collapse warnings at rescue sites.

[0079] The terminal design and development as well as the rapid deployment and networking monitoring modules can meet the needs of installation and rapid deployment in any direction at the rescue site, signal extraction, and real-time monitoring, providing safety protection for rescue personnel.

[0080] Another object of the present invention is to provide a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the earthquake collapsed building deformation emergency monitoring method.

[0081] Another object of the present invention is to provide a computer-readable storage medium storing a computer program, which, when executed by a processor, enables the processor to execute the steps of the earthquake collapsed building deformation emergency monitoring method.

[0082] Another object of the present invention is to provide an information data processing device, which is used to implement the earthquake collapsed building deformation emergency monitoring system.

[0083] In combination with the above technical solutions and the technical problems solved, the advantages and positive effects of the technical solutions to be protected by the present invention are as follows:

[0084] First, the dual-antenna GNSS / IMU rapid combined positioning and attitude measurement method provided in the embodiment of the present invention can realize the rapid initialization of the dual-antenna GNSS attitude measurement-assisted inertial navigation, and calculate the high-precision attitude, displacement and velocity results in real time, which is applied to the field of earthquake collapse monitoring and early warning.

[0085] The vibration signal extraction method under high background noise provided by the embodiment of the present invention uses modern time-frequency analysis technology as a means, combined with an optimization calculation method, to accurately and efficiently extract building vibration signals under a strong noise background. It can be used to assess the impact of earthquakes and aftershocks on buildings, set reasonable thresholds, and provide collapse warnings for rescue sites.

[0086] The earthquake collapse emergency monitoring terminal design and development, rapid deployment and networking monitoring technical solutions provided by the embodiments of the present invention can meet the needs of installation and rapid deployment in any direction, signal extraction, and real-time monitoring at the rescue site, providing safety protection for rescue personnel.

[0087] Second, the present invention utilizes dual-antenna GNSS high-precision direction-finding information to assist in the rapid initialization of inertial navigation, and realizes a dual-antenna GNSS RTK / MEMS-IMU combined positioning and attitude measurement algorithm; combined with modern time-frequency analysis methods, the vibration signal extraction method under high background noise is studied, which can be used to assess the impact of earthquakes and aftershocks on buildings, set reasonable thresholds, and provide collapse warnings for rescue sites; the design and development, rapid deployment and networking monitoring technical solutions for earthquake collapse emergency monitoring terminals are designed, which can meet the needs of installation and rapid deployment in any direction at the rescue site, signal extraction, and real-time monitoring, providing safety protection for rescue personnel.

[0088] Third, as auxiliary evidence of the inventiveness of the claims of the present invention, it is also reflected in the following important aspects:

[0089] (1) The expected benefits and commercial value of the technical solution of the present invention after transformation are:

[0090] The earthquake collapse emergency monitoring terminal design and development, rapid deployment and networking monitoring technical solutions provided in the embodiments of the present invention can meet the needs of installation and rapid deployment in any direction, signal extraction, and real-time monitoring at the rescue site, provide safety protection for earthquake rescue personnel, protect the lives of earthquake rescue personnel, and reduce the loss of people’s property safety.

[0091] (2) The technical solution of the present invention fills the technical gap in the industry at home and abroad:

[0092] The vibration signal extraction method under high background noise provided by the embodiment of the present invention uses modern time-frequency analysis technology as a means, combined with an optimization calculation method, to accurately and efficiently extract building vibration signals under a strong noise background. It can be used to assess the impact of earthquakes and aftershocks on buildings, set reasonable thresholds, and provide collapse warnings for rescue sites.

[0093] (3) Whether the technical solution of the present invention solves the technical problems that people have been eager to solve but have not been able to solve successfully:

[0094] The dual-antenna GNSS / IMU rapid combined positioning and attitude measurement method provided in the embodiment of the present invention can realize the rapid initialization of the dual-antenna GNSS attitude measurement-assisted inertial navigation, and calculate the high-precision attitude, displacement and velocity results in real time, which is applied to the field of earthquake collapse monitoring and early warning. BRIEF DESCRIPTION OF THE DRAWINGS

[0095] Figure 1 It is the overall technical roadmap for the implementation of the method of the present invention;

[0096] Figure 2 It is a flow chart of the dual-antenna GNSS RTK / MEMS-IMU combined rapid positioning and attitude measurement algorithm implemented by the present invention;

[0097] Figure 3 It is a flow chart of the vibration signal extraction method under high background noise implemented by the present invention;

[0098] Figure 4 It is a user terminal design diagram of the earthquake collapse emergency monitoring terminal implemented by the present invention;

[0099] Figure 5 It is a design diagram of a terminal service end for emergency monitoring of earthquake collapse implemented by the present invention;

[0100] Figure 6 This is a physical diagram of the short baseline and dual antenna positioning experiment design in Example 2;

[0101] Figure 7-Figure 12 This is the result diagram of short baseline and dual antenna positioning;

[0102] Figure 13 to Figure 14 This is the result of dual-antenna attitude measurement;

[0103] Fig.15 This is the experimental design diagram of vibration signal extraction under high background noise;

[0104] Figures 16 to 21 This is the experimental result diagram of vibration signal extraction under high background noise;

[0105] Figure 22 to Figure 23 This is a simulation experiment result diagram for vibration signal extraction under high background noise. DETAILED DESCRIPTION

[0106] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0107] In order to enable those skilled in the art to fully understand how to implement the present invention in detail, this section is an explanatory embodiment that expands and describes the technical solution of the claims.

[0108] Example 1

[0109] The technical solution adopted by the present invention includes a dual-antenna GNSS / IMU rapid combined positioning and attitude measurement method, a vibration signal extraction method under high background noise, and the design and development of an earthquake collapse emergency monitoring terminal, as well as rapid deployment and networking monitoring.

[0110] Furthermore, the dual-antenna GNSS / IMU fast combined positioning and attitude measurement method includes the following steps:

[0111] In the first step, the GNSS pseudorange and carrier phase observation equations can be written as:

[0112]

[0113]

[0114] Where j is the observation frequency used, P is the pseudorange observation value, φ is the carrier phase observation value, λ is the carrier wavelength, ρ is the satellite-to-ground geometric distance, and dt r and dt s are the receiver clock error and satellite clock error respectively, T is the tropospheric delay, I is the ionospheric delay, d r and d s are the code hardware delays of the receiver and the satellite, δ r and δ s are the carrier phase hardware delays of the receiver and satellite, ω r and ω s are the initial phase values ​​of the receiver and the satellite, respectively, N is the undifferenced integer ambiguity, e and ε are the pseudorange and carrier phase observation noises (including unmodeled errors such as multipath), respectively.

[0115] The second step is to construct a double-difference observation equation before RTK solution. Each system GNSS observation value selects an independent reference satellite to ensure the integer characteristics of the double-difference ambiguity. Under the condition of short baseline synchronous observation, after double-difference between satellites within the system, errors related only to the receiver and only to the satellite (such as clock error, hardware delay, initial phase value of carrier phase) are completely eliminated, and ionospheric delay and tropospheric delay are basically eliminated and can be ignored. Therefore, the double-difference observation equation constructed by receiver r and b and satellite s and k can be expressed as:

[0116]

[0117]

[0118] In the formula, is a double difference operator, which calculates the approximate coordinates of the satellite from the broadcast ephemeris and The approximate coordinates of the base station and the mobile station are known to be and Linearize equations (1-3) and (1-4), and ignore the influence of satellite coordinate and reference station coordinate errors, then the double difference observation equations of pseudorange and carrier phase can be written as:

[0119]

[0120]

[0121] In the formula, is the satellite-to-ground geometric distance calculated from the approximate coordinates of the satellite and receiver, u r is the direction cosine from the receiver to the satellite, and Δr is the baseline component correction. From equations (1-5) and (1-6), we can see that the parameters to be estimated are only the three-dimensional baseline vector correction and the double-difference integer ambiguity. Using the least squares method or Kalman filtering algorithm, the real number solution of the double-difference ambiguity can be obtained: and its covariance matrix Construct the following objective function:

[0122]

[0123] Where N is the double difference ambiguity integer solution. The ambiguity search is performed using the Least Square Ambiguity Decorrelation Adjustment (LAMBDA) method, and the Ratio test method is used to confirm the ambiguity:

[0124]

[0125] When Ratio is greater than 2, the fixed ambiguity is an integer solution N, and a high-precision three-dimensional baseline vector solution can be obtained.

[0126] The third step is to complete the initialization of the dual-antenna GNSS attitude measurement assisted inertial navigation. Dual-antenna GNSS attitude measurement can provide external attitude information, especially improve the observability of the heading angle. Once the dual-antenna GNSS correctly fixes the ambiguity, the accurate antenna baseline vector can be obtained, so that the heading angle and pitch angle can be calculated:

[0127]

[0128]

[0129] For the emergency monitoring of collapsed building deformation at earthquake rescue sites, it is assumed that when the equipment is just fixed to the building, the building is in a quasi-stationary state. The roll angle can be calculated based on the leveling principle of the static base accelerometer, and the heading angle and pitch angle can be obtained by using the dual-antenna GNSS attitude measurement. At this time, the rough alignment process can be completed. Then, Kalman filtering is used for fine alignment, and the heading angle and pitch angle obtained by the dual-antenna GNSS attitude measurement are fused into the filter model as virtual observation values, and finally the rapid initialization of inertial navigation assisted by the dual-antenna GNSS attitude measurement can be realized ( Figure 2 ).

[0130] The fourth step is to perform GNSS RTK / MEMS-IMU combined attitude measurement and positioning. Selecting n as the navigation system, the state equation of the navigation parameters can be expressed as:

[0131]

[0132] In the formula, and φ are position error, velocity error and misalignment angle respectively; f b and δf b denote specific force and specific force error respectively; is the gyroscope angular rate error; δg n Indicates gravity error; Represents the coordinate transformation matrix from b system to n system. Based on the state equation, time update can be performed:

[0133]

[0134]

[0135] In the formula, and They represent the estimated values ​​of the state parameters and the covariance matrix at epoch k-1 respectively; and They represent the predicted values ​​of the state parameters at epoch k and the corresponding covariance matrix respectively; Φ k,k-1 Represents the state transition matrix from epoch k-1 to epoch k.

[0136] Furthermore, after considering the GNSS arm correction, the loose combined measurement model is expressed as follows:

[0137]

[0138] in

[0139]

[0140]

[0141] In the formula, and represents the GNSS position and velocity vector; [ε p ε v ] T Represents the position and velocity errors, and its corresponding variance matrix is ​​R k ; l b H is the GNSS arm correction; k is the design matrix; Z k is the new information vector. Based on the observation equation, the measurement update can be performed:

[0142]

[0143]

[0144]

[0145] The specific fusion process of the combined module is as follows Figure 2 After data preprocessing, GNSS performs RTK solution and outputs positioning results. After mechanical arrangement, MEMS-IMU outputs dead reckoning results. After time and space synchronization, the two types of measurement information enter the loose combination filter, which forms a closed-loop correction for MEMS-IMU and outputs a combined positioning result.

[0146] Furthermore, the specific process of the building vibration signal extraction method designed by the institute is as follows Figure 3 As shown, it mainly includes:

[0147] In the first step, the building vibration time series is used as the building vibration signal, taking into account the sampling theorem and Fourier transform, and setting the cutoff frequency of the low-pass filter according to the Fourier spectrum to initially eliminate the high-frequency background noise in the building vibration signal.

[0148] In the second step, after the initial filtering, the start and end time of the vibration signal is determined based on the prior noise of the static state monitoring signal as the threshold, and the building vibration signal is mapped to the time-frequency domain using continuous wavelet transform to obtain the time-frequency diagram of the building vibration signal.

[0149] The third step is to identify the time-frequency area where the earthquake natural disaster affects the building in the time-frequency diagram, use the inverse wavelet transform to restore the waveform of the building vibration signal, obtain a relatively pure building vibration signal, and finally use wavelet spectrum analysis to extract the characteristic information (static offset, signal amplitude, etc.) of the building vibration signal caused by natural earthquakes.

[0150] High-frequency background noise preprocessing method

[0151] The Nyquist sampling theorem states that in order to restore the original signal from the sampled signal without distortion, the sampling frequency should be greater than twice the highest frequency of the signal. If the sampling frequency is less than twice the highest frequency of the spectrum, the spectrum of the signal will be aliased. According to this theorem, it can be pointed out that the highest cutoff frequency of the low-pass filter of the building vibration signal is half of the sampling frequency. The building vibration signal is Fourier transformed to obtain the Fourier spectrum of the signal, and the cutoff frequency of the low-pass filter is designed to initially eliminate the high-frequency background noise in the building vibration signal.

[0152] Vibration signal feature extraction method

[0153] Since the clutter around the building will affect the building vibration signal. If it is not removed, it will not be able to accurately reflect the degree of damage to the building caused by the earthquake. For this reason, the continuous wavelet transform is used to map the building vibration signal to the time-frequency domain, and the inaction method or wavelet inverse transform is used to extract and restore the building vibration signal. The building vibration signal f(t) in any L2(R) space is expanded under the wavelet basis, which is the continuous wavelet transform of the vibration signal f(t). Its expression is:

[0154]

[0155] Among them, ψ a,τ (t) shall meet the following requirements:

[0156]

[0157] The continuous wavelet transform described in the above formula is used to map the preprocessed building vibration signal to the time-frequency domain to obtain the characteristic information of the building vibration signal.

[0158] The admissible conditions for the inverse continuous wavelet transform are:

[0159]

[0160] The formula for its inverse transformation is:

[0161]

[0162] The waveform f(t) of the building vibration signal after noise elimination is restored by using the inaction principle or the above wavelet inverse transform formula under permissible conditions.

[0163] Furthermore, the design and development steps of the earthquake collapse emergency monitoring terminal are as follows:

[0164] The first step is data communication, which is the premise for ensuring the stable operation of the monitoring terminal and the continuous output of positioning solution results. According to the actual application environment, under the premise of ensuring the communication quality, a data communication method that is easy to maintain and economical is generally selected. Table 1-1 gives the characteristics of several data transmission methods. It can be seen that different data transmission methods have advantages and disadvantages. After analysis, the terminal can currently choose to use two communication methods: 4G mobile network and wireless radio.

[0165] Table 1 Characteristics of several data transmission technologies

[0166]

[0167] In the second step, the developed terminal mainly includes dual-antenna GNSS module, MEMS-IMU module, 4G communication module, radio module, processor, data storage module, power module, interface, indicator light, etc. ( Figure 4 ), the above modules are tightly integrated by integrated design, and through the effective cooperation of software and hardware, the following can be achieved:

[0168] 1) Collection and storage of GPS L1 / L2, GLONASS L1 / L2, GALILEO E1 / E5a, BDS B1 / B3 observation data and high sampling rate (100Hz or even 200Hz) angular velocity and acceleration data;

[0169] 2) Perform attitude measurement based on dual-antenna GNSS observations and combine initial static constraints to achieve fast initial alignment of inertial navigation;

[0170] 3) Obtain the GNSS observation values ​​of the base station through 4G or radio communication, perform GNSS RTK solution, and combine the MEMS-IMU angular velocity and acceleration data to achieve GNSS RTK / MEMS-IMU combined positioning and attitude determination.

[0171] The third step is to customize a shell that can be embedded with the terminal and GNSS dual antenna according to the shape and size of the earthquake collapsed building deformation emergency monitoring terminal and the GNSS antenna. Strong adhesive patches are placed on the bottom and sides of the shell. After tearing off the outer skin of the strong adhesive patches, the shell can be quickly pasted on the roof, walls, beams and columns on the top of the earthquake collapsed building by drones, robots, or manual labor, thereby realizing the rapid deployment of the earthquake collapsed building deformation emergency monitoring terminal.

[0172] The fourth step is to design the overall server side ( Figure 5 ). The base station is deployed outside the rescue operation range of the collapsed body, and sends observation data to the terminal through the server communication module. The terminal completes the solution after receiving the observation data, and transmits the calculated acceleration, velocity, displacement and attitude data back to the server. The server software completes vibration signal extraction, early warning and visualization.

[0173] Example 2

[0174] The following is an example of the application scenario of the earthquake collapse body emergency rescue deformation monitoring method, device, equipment and terminal:

[0175] (1) GNSS RTK / MEMS-IMU combined positioning test

[0176] The research on GNSS RTK / MEMS-IMU combined positioning method was carried out, and short baseline relative positioning experiment and dual antenna relative positioning experiment were designed. Figure 6 ), the positioning performance of the customized high-precision GNSS / MEMS-IMU combined positioning module was evaluated and tested as a whole. The dual antenna and short baseline data collection process is in a static state. Static relative positioning is used for solution, and millimeter-level relative positioning results can be obtained as a reference; in the evaluation of positioning results, the self-developed RTK positioning software is used to calculate the difference between the real-time solution result and the reference value as the positioning error. A total of 6 experimental results were collected from March 6 to April 10 ( Figures 7 to 12 ).

[0177] The results of 6 experiments show that the relative positioning accuracy of the short baseline is better than 4 mm in the horizontal direction and better than 8 cm in the vertical direction (Table 3); the relative positioning accuracy of the dual antenna is better than 2 mm in the horizontal direction and better than 6 mm in the vertical direction (Table 4).

[0178] Table 2 Short baseline positioning results (m)

[0179]

[0180] Table 3 Dual antenna positioning results (m)

[0181]

[0182] In order to verify the accuracy and initialization time of the dual-antenna GNSS RTK / MEMS-IMU combined attitude measurement, two sets of experiments were conducted. The experimental platform was the same as the positioning experiment mentioned above. The results of the two experiments showed (Table 4) that the heading angle measurement accuracy of the dual-antenna GNSS-assisted heading angle measurement was better than 3.7cm, the roll angle measurement accuracy was better than 1.1cm, the pitch angle measurement accuracy was better than 1.4cm, and the attitude convergence time was better than 30s ( Figures 13 to 14 ).

[0183] Table 4. Pose measurement test results (m)

[0184]

[0185]

[0186] (2) Vibration signal extraction experiment under high background noise

[0187] In order to further study the vibration signal extraction method under high background noise, the developed terminal was built on a strapdown dual-antenna experimental platform ( Fig.15 ), artificially simulate the three states of "stationary-shaking-stationary" of the building and record the duration, use the threshold method to determine the start and end time of the building vibration, and use the time-frequency analysis method to separate the high-frequency background noise and extract the vibration signal.

[0188] The results of the first arrival extraction of 6 horizontal vibration signals are as follows: Figures 16 to 21 Table 5 shows the experimental results of the first arrival and end time discrimination of 6 vibration signals, among which the difference between the first arrival discrimination results of 6 vibrations and the manual discrimination results is less than 1s. Table 6 shows the characteristic information of the extracted vibration signal, among which the average amplitude value in the horizontal direction of the 6 vibration tests is 15.05cm, and the average static offset is 27.50cm; the average amplitude value in the vertical direction is 3.45cm, and the average static offset is 1.27cm.

[0189] Table 5 Vibration automatic picking results

[0190]

[0191] Table 6 Vibration signal separation results (m)

[0192]

[0193]

[0194] In order to prove the creativity and technical value of the technical solution of the present invention, this section provides application examples of the claimed technical solution on specific products or related technologies.

[0195] The embodiment of the present invention provides an earthquake collapsed building deformation emergency monitoring system for implementing the earthquake collapsed building deformation emergency monitoring method, the system comprising:

[0196] Combined positioning and attitude measurement module, used to realize dual-antenna GNSS attitude measurement to assist inertial navigation rapid initialization, real-time solution of high-precision attitude, displacement and velocity results, applied to earthquake collapse monitoring and early warning fields;

[0197] The vibration signal extraction module uses modern time-frequency analysis technology and combines it with the optimization calculation method to accurately and efficiently extract building vibration signals under strong noise backgrounds. It can be used to assess the impact of earthquakes and aftershocks on buildings, set reasonable thresholds, and issue collapse warnings at rescue sites.

[0198] The terminal design and development as well as the rapid deployment and networking monitoring modules can meet the needs of installation and rapid deployment in any direction at the rescue site, signal extraction, and real-time monitoring, providing safety protection for rescue personnel.

[0199] An embodiment of the present invention provides a computer device, which includes a memory and a processor. The memory stores a computer program. When the computer program is executed by the processor, the processor executes the steps of the earthquake collapsed building deformation emergency monitoring method.

[0200] An embodiment of the present invention provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the processor executes the steps of the earthquake collapsed building deformation emergency monitoring method.

[0201] The working principle and technical effects of the earthquake collapse building deformation emergency monitoring system provided by the embodiment of the present invention are as follows:

[0202] 1) Combined positioning and attitude measurement module: This module uses dual-antenna GNSS attitude measurement to assist inertial navigation technology to achieve rapid initialization. By integrating GNSS and MEMS-IMU data, high-precision attitude, displacement and velocity results are calculated in real time. Dual-antenna GNSS attitude measurement can provide more accurate direction information and reduce the impact of GNSS signals being blocked and interfered with, while the inertial navigation system has strong dynamic tracking capabilities. This combined positioning and attitude measurement technology can effectively improve the accuracy and real-time performance of earthquake collapse monitoring and early warning.

[0203] 2) Vibration signal extraction module: This module uses modern time-frequency analysis technology and combines it with optimization calculation methods to achieve accurate and efficient extraction of building vibration signals under strong noise background. By evaluating the impact of earthquakes and aftershocks on buildings and setting reasonable thresholds, collapse warnings can be achieved at the rescue site. In this module, time-frequency analysis methods such as short-time Fourier transform and wavelet transform, as well as optimization algorithms such as particle swarm optimization and genetic algorithms, can be used to improve the accuracy of vibration signal extraction.

[0204] 3) Terminal design and development, rapid deployment and network monitoring module: This module is designed with portable and easy-to-install terminal devices to meet the needs of the rescue site. These devices can meet the installation requirements of any direction of the rescue site, and achieve rapid deployment, signal extraction and real-time monitoring. Through wireless communication technology, network monitoring is realized, which makes it easier for rescuers to grasp the deformation of the building in real time and provide safety protection for rescuers.

[0205] In summary, the earthquake collapsed building deformation emergency monitoring system realizes high-precision, real-time, and dynamic tracking earthquake collapsed building deformation monitoring by combining positioning and attitude measurement, vibration signal extraction, and terminal design and development technologies. This system has important application value at the post-earthquake rescue site, providing strong support for ensuring the safety of rescue personnel, assessing the condition of buildings, and formulating rescue plans.

[0206] The vibration signal extraction method under high-frequency background noise mentioned in the present invention was simulated and the S wave and P wave ( Fig. 22 ), and a Gaussian white noise perturbation with a variance of 0.03 is added to the original signal, and the denoising result of the smoothing prior information method is used as a comparison to verify the denoising effect of the proposed method. Fig.23 It can be seen that the signal time-frequency diagram after time-frequency transformation denoising is most similar to the original seismic displacement. Although the smooth prior information method can also eliminate some of the influence, its elimination effect in the low-frequency part is obviously inferior to the signal denoising method based on time-frequency analysis. The denoising effect of the two methods was evaluated by the correlation coefficient between the denoised signal and the original signal. The correlation coefficient of the noisy signal is 0.8943, the correlation coefficient of the time-frequency analysis method is 0.9577, and the smooth prior information method is 0.9373. The vibration signal extraction method under high background noise based on time-frequency analysis technology has a more significant denoising effect than the smooth prior information method.

[0207] It should be noted that the embodiments of the present invention can be implemented by hardware, software, or a combination of software and hardware. The hardware part can be implemented using dedicated logic; the software part can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated design hardware. It can be understood by a person of ordinary skill in the art that the above-mentioned devices and methods can be implemented using computer executable instructions and / or contained in a processor control code, such as a carrier medium such as a disk, CD or DVD-ROM, a programmable memory such as a read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. Such code is provided on the carrier medium. The device and its modules of the present invention can be implemented by hardware circuits such as very large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., can also be implemented by software executed by various types of processors, and can also be implemented by a combination of the above-mentioned hardware circuits and software, such as firmware.

[0208] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any modifications, equivalent substitutions and improvements made by any technician familiar with the technical field within the technical scope disclosed by the present invention and within the spirit and principle of the present invention should be covered by the protection scope of the present invention.

Claims

1. An emergency monitoring method for deformation of collapsed buildings due to earthquakes, characterized in that: Use the all-weather, real-time, high-precision GNSS RTK / MEMS-IMU combined sensor to obtain the original GNSS and IMU observation data, perform dual-antenna GNSS attitude measurement to assist IMU rapid alignment, and then use the dual-antenna GNSS / MEMS-IMU rapid combined positioning and attitude measurement method to obtain the carrier's attitude, speed and position information. Then use the vibration signal extraction method under high background noise to monitor the building deformation and corresponding time information in real time. When the deformation exceeds the threshold, issue a warning in time to notify relevant personnel to take protective measures in time. The dual-antenna GNSS / MEMS-IMU fast combined positioning and attitude measurement method comprises the following steps: In the first step, the GNSS pseudorange and carrier phase observation equations are: Where j is the observation frequency used, P is the pseudorange observation value, Φ is the carrier phase observation value, λ is the carrier wavelength, ρ is the satellite-to-ground geometric distance, and dt r and dt s are the receiver clock error and satellite clock error respectively, T is the tropospheric delay, I is the ionospheric delay, d r and d s are the code hardware delays of the receiver and the satellite, δ r and δ s are the carrier phase hardware delays of the receiver and satellite, ω r and ω s are the initial phase values ​​of the receiver and the satellite, respectively, N is the undifferenced integer ambiguity, e and ε are the pseudorange and carrier phase observation noise, respectively, including the unmodeled multipath error; In the second step, before performing RTK solution, it is necessary to construct a double-difference observation equation. Each system GNSS observation value selects an independent reference satellite to ensure the integer characteristics of the double-difference ambiguity. Under the condition of short baseline synchronous observation, after double-difference between satellites within the system, the errors related only to the receiver and only to the satellite are completely eliminated, and the ionospheric delay and tropospheric delay are also basically eliminated and can be ignored. Therefore, the double-difference observation equation constructed by the receiver r and b and the satellite s and k is expressed as: In the formula, is a double difference operator, which calculates the approximate coordinates of the satellite from the broadcast ephemeris and The approximate coordinates of the base station and the mobile station are known to be and Linearize equations (1-3) and (1-4), and ignore the influence of satellite coordinate and reference station coordinate errors, then the double difference observation equations of pseudorange and carrier phase are written as: In the formula, is the satellite-to-ground geometric distance calculated from the approximate coordinates of the satellite and receiver, u r is the direction cosine from the receiver to the satellite, Δr is the baseline component correction number; from equations (1-5) and (1-6), it can be seen that the parameters to be estimated are only the three-dimensional baseline vector correction number and the double-difference integer ambiguity; using the least squares method or Kalman filtering algorithm, the real number solution estimate of the double-difference ambiguity is obtained and its covariance matrix Construct the following objective function: In the formula, is the estimated value of the double-difference ambiguity integer solution. The ambiguity search is performed using the Leastsquare Ambiguity Decorrelation Adjustment (LAMBDA) method, and the Ratio test method is used to confirm the ambiguity: When Ratio is greater than 2, the ambiguity is fixed to an integer solution, and then a high-precision three-dimensional baseline vector solution is obtained; The third step is to complete the initialization of the dual-antenna GNSS attitude measurement assisted inertial navigation. The dual-antenna GNSS attitude measurement provides external attitude information, which can improve the observability of the heading angle. Once the dual-antenna GNSS correctly fixes the ambiguity, the accurate antenna baseline vector is obtained, thereby calculating the heading angle and pitch angle: For the emergency monitoring of collapsed building deformation at earthquake rescue sites, it is assumed that when the equipment is just fixed to the building, the building is in a quasi-static state. The roll angle is calculated based on the leveling principle of the static base accelerometer, and the heading angle and pitch angle are obtained by dual-antenna GNSS attitude measurement. At this time, the coarse alignment process is completed, and then the Kalman filter is used for fine alignment, and the heading angle and pitch angle obtained by the dual-antenna GNSS attitude measurement are fused into the filter model as virtual observation values, and finally the rapid initialization of inertial navigation assisted by dual-antenna GNSS attitude measurement is realized; The fourth step is to perform GNSS RTK / MEMS-IMU combined attitude measurement and positioning; select n system as the navigation system, and the state equation of the navigation parameters is expressed as: In the formula, and φ are position error, velocity error and misalignment angle respectively; f b and δf b denote specific force and specific force error respectively; is the gyroscope angular rate error; δg n Indicates gravity error; Represents the coordinate transformation matrix from b system to n system, which is updated in time based on the state equation: In the formula, and They represent the estimated values ​​of the state parameters and the covariance matrix at epoch k-1 respectively; and They represent the predicted values ​​of the state parameters at epoch k and the corresponding covariance matrix respectively; Φ k,k-1 Represents the state transition matrix from epoch k-1 to epoch k; Furthermore, after considering the GNSS arm correction, the loose combined measurement model is expressed as follows: in In the formula, and Represents the GNSS position and velocity vector; l b H is the GNSS arm correction; k is the design matrix; Z k is the new information vector; based on the observation equation, the measurement update is performed: After data preprocessing, GNSS performs RTK solution and outputs positioning results. After mechanical arrangement, MEMS-IMU outputs dead reckoning results. After the two types of measurement information are synchronized in time and space, they enter the loose combination filter to form a closed-loop correction for MEMS-IMU and output the combined positioning results. The vibration signal extraction method under high background noise mainly includes: The first step is to use the building vibration time series as the building vibration signal, taking into account the sampling theorem and Fourier transform, and setting the cutoff frequency of the low-pass filter according to the Fourier spectrum to initially eliminate the high-frequency background noise in the building vibration signal; In the second step, after the initial filtering, the start and end time of the vibration signal is determined based on the prior noise of the static state monitoring signal as the threshold, and the time sequence of the vibration signal after triggering is mapped to the time-frequency domain using continuous wavelet transform to obtain the time-frequency diagram of the building vibration signal; The third step is to identify the time-frequency area where the earthquake natural disaster affects the building in the time-frequency diagram, use the inverse wavelet transform to restore the waveform of the building vibration signal, obtain a relatively pure building vibration signal, and finally use wavelet spectrum analysis to extract the characteristic information of the building vibration signal caused by the natural earthquake, which includes static offset and signal amplitude.

2. The method for monitoring deformation of collapsed buildings during earthquakes according to claim 1, characterized in that: The vibration signal extraction method under high background noise also includes: ① High-frequency background noise preprocessing method The Nyquist sampling theorem states that in order to restore the original signal from the sampled signal without distortion, the sampling frequency should be greater than twice the highest frequency of the signal. If the sampling frequency is less than twice the highest frequency of the spectrum, the spectrum of the signal will be aliased. According to this theorem, the highest cutoff frequency of the low-pass filter of the building vibration signal is half of the sampling frequency. The building vibration signal is Fourier transformed to obtain the Fourier spectrum of the signal, and the cutoff frequency of the low-pass filter is designed to initially eliminate the high-frequency background noise in the building vibration signal. ②Vibration signal feature extraction method Since the clutter around the building will affect the building vibration signal, if it is not removed, it will not be able to accurately reflect the degree of damage to the building caused by the earthquake. Therefore, the continuous wavelet transform is used to map the building vibration signal to the time-frequency domain, and the inaction principle or wavelet inverse transform is used to extract and restore the building vibration signal; the building vibration signal f(t) in any L2 space is expanded under the wavelet basis, which is the continuous wavelet transform of the vibration signal f(t), and its expression is: Among them, ψ a,τ (t) shall meet the following requirements: The preprocessed building vibration signal is mapped to the time-frequency domain using the continuous wavelet transform described in the above formula to obtain the characteristic information of the building vibration signal; The admissible conditions for the inverse continuous wavelet transform are: The formula for its inverse transformation is: The waveform f(t) of the building vibration signal after noise elimination is restored by using the inaction principle or the above wavelet inverse transform formula under permissible conditions.

3. The method for monitoring deformation of collapsed buildings during earthquakes according to claim 1, characterized in that: The steps for designing, developing, rapidly deploying and networking the earthquake collapse emergency monitoring terminal are as follows: The first step is that data communication is the premise for ensuring the stable operation of the monitoring terminal and the continuous output of positioning solution results. According to the actual application environment, generally, on the premise of ensuring the communication quality, a data communication method that is easy to maintain and economical is selected; In the second step, the developed terminal mainly includes dual-antenna GNSS module, MEMS-IMU module, 4G communication module, radio module, processor, data storage module, power module, interface, and indicator light; The third step is to customize a shell that can embed the terminal and GNSS dual antennas according to the shape and size of the earthquake collapsed building deformation emergency monitoring terminal and the GNSS antenna. Strong adhesive patches are placed on the bottom and sides of the shell. After the outer skin of the strong adhesive patches is torn off, the shell is quickly pasted on the roof, wall, beam and column of the top of the earthquake collapsed building by drones, robots or manual labor, so as to realize the rapid deployment of the earthquake collapsed building deformation emergency monitoring terminal. The fourth step is to carry out the overall design of the server. The base station is deployed outside the rescue operation range of the collapsed body, and the observation data is sent to the terminal through the server communication module. After receiving the observation data, the terminal completes the solution and transmits the solved acceleration, velocity, displacement and attitude data back to the server. The server software completes vibration signal extraction, early warning and visualization.

4. The method for emergency monitoring of earthquake collapsed building deformation according to claim 3, characterized in that: The terminal developed in the second step adopts an integrated design to tightly integrate the above modules, and through the effective cooperation of software and hardware, achieves: 1) Collection and storage of GPS L1 / L2, GLONASS L1 / L2, GALILEO E1 / E5a, BDS B1 / B3 observation data and 100Hz or 200Hz high sampling rate angular velocity and acceleration data; 2) Perform attitude measurement based on dual-antenna GNSS observations and combine initial static constraints to achieve fast initial alignment of inertial navigation; 3) Obtain the GNSS observation values ​​of the base station through 4G or radio communication, perform GNSS RTK solution, and combine the MEMS-IMU angular velocity and acceleration data to achieve GNSS RTK / MEMS-IMU combined positioning and attitude determination.

5. An earthquake collapsed building deformation emergency monitoring system implementing the earthquake collapsed building deformation emergency monitoring method according to any one of claims 1 to 4, characterized in that: The system includes: Combined positioning and attitude measurement module, used to realize dual-antenna GNSS attitude measurement to assist inertial navigation rapid initialization, real-time solution of high-precision attitude, displacement and velocity results, applied to earthquake collapse monitoring and early warning fields; The vibration signal extraction module uses modern time-frequency analysis technology and combines it with the optimization calculation method to accurately and efficiently extract building vibration signals under strong noise backgrounds. This module is used to assess the impact of earthquakes and aftershocks on buildings, set reasonable thresholds, and issue collapse warnings at rescue sites. The terminal design and development as well as the rapid deployment and networking monitoring modules meet the needs of installation and rapid deployment in any direction at the rescue site, signal extraction, and real-time monitoring, providing safety protection for rescue personnel.

6. A computer device, characterized in that: The computer device includes a memory and a processor, the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the earthquake collapsed building deformation emergency monitoring method as claimed in any one of claims 1-4.

7. A computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the processor executes the steps of the earthquake collapsed building deformation emergency monitoring method as claimed in any one of claims 1 to 4.

8. An information data processing device, characterized in that: The information data processing device is used to implement the earthquake collapsed building deformation emergency monitoring system as described in claim 5.

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