Safety early warning system for anti-seismic support

Abstract

The present application relates to the technical field of structural health monitoring, in particular to a kind of anti-seismic support safety early warning system, comprising: vibration acquisition module for obtaining the vibration signal of several measuring points on anti-seismic support hanger;According to the attenuation analysis module of vibration attenuation characteristic value determination corresponding measuring point whether there is abnormality;With to determine abnormality as integrity abnormality or local abnormality when there is abnormality distribution discrimination module;With to determine whether the integrity abnormality is derived from mechanical and electrical equipment operation interference when determining as integrity abnormality interference attribution module;With to determine whether the local abnormality is the damage of anti-seismic support hanger connecting node when determining as local abnormality damage detection module;With to adjust the sampling frequency of abnormal measuring point when determining as the damage of anti-seismic support hanger connecting node monitoring control module.The present application improves the early warning reliability of anti-seismic support safety early warning.

Description

Technical Field

[0001] This invention relates to the field of structural health monitoring technology, specifically to a seismic bracing safety early warning system. Background Technology

[0002] In building electromechanical engineering, facilities such as water pipes, air ducts, and cable trays must be securely connected to the building structure using seismic bracing to withstand horizontal forces during earthquakes and prevent pipelines from falling and causing injury. Standards require seismic design for the electromechanical systems of buildings with a seismic fortification intensity of 6 degrees or higher. Current standards further require safety monitoring and early warning systems for seismic bracing. The main defects in seismic bracing during use are loose bolts at connection points, anchorage failure, and component corrosion. These defects can cause local stiffness degradation in the bracing, and if not detected in time, will lead to bracing failure during earthquakes.

[0003] Existing monitoring solutions typically involve installing vibration, loosening, or deformation sensors on seismic bracing to collect monitoring parameters and compare them with preset thresholds. Once the limits are exceeded, an alarm is triggered.

[0004] However, the operation of mechanical and electrical equipment such as water pumps, fans, and elevators within buildings generates continuous vibrations, and sudden excitations such as earthquakes and heavy object impacts can also cause vibrations in the supports and hangers. These environmental disturbances, along with actual damage to the connection nodes, can cause monitoring parameters to exceed preset thresholds. Existing solutions struggle to distinguish whether abnormal vibrations originate from actual damage to the support and hanger connection nodes or from environmental disturbances, leading to false alarms and missed alarms: either environmental disturbances are falsely reported as damage, resulting in wasted maintenance, or minor early loosening is mistaken for disturbance and missed. Summary of the Invention

[0005] To address this issue, the present invention provides a seismic bracing safety early warning system to overcome the problem that existing technologies do not consider the impact of environmental interference on the seismic bracing safety monitoring parameters, cannot distinguish whether vibration anomalies are caused by environmental interference or by actual damage to the connection nodes of the seismic bracing based on the spatial distribution differences of abnormal measuring points, and thus generate false alarms and missed alarms, resulting in poor early warning reliability of the seismic bracing safety early warning system.

[0006] To achieve the above objectives, the present invention provides a seismic bracing safety early warning system, comprising: a vibration acquisition module, used to acquire vibration signals at a sampling frequency from several measuring points installed on various seismic bracing supports within a building; The attenuation analysis module is connected to the vibration acquisition module and is used to determine the vibration attenuation characterization value of each measuring point based on the vibration signal, and to determine whether there is an abnormality at the corresponding measuring point based on the vibration attenuation characterization value. A distribution discrimination module, which is connected to the attenuation analysis module, is used to determine the spatial distribution discrimination coefficient based on the spatial distribution of the abnormal measurement points when the abnormality exists, and to determine whether the abnormality is a global abnormality or a local abnormality based on the spatial distribution discrimination coefficient. An interference attribution module, which is connected to the distribution discrimination module, is used to determine whether the overall anomaly originates from interference in the operation of electromechanical equipment based on the interference attribution confidence level when the overall anomaly is determined. The damage detection module, which is connected to the distribution discrimination module, is used to determine whether the local anomaly is damage to the connection node of the seismic bracing and hanger based on the connection stiffness degradation coefficient when the local anomaly is determined. The monitoring and control module is connected to the damage detection module and the vibration acquisition module respectively, and is used to adjust the sampling frequency of abnormal measuring points according to the connection stiffness degradation coefficient when damage is determined to be at the connection node of the seismic bracing.

[0007] By employing the above technical solution, this invention collects vibration signals from several measuring points deployed on various seismic bracing supports. First, it screens out abnormal measuring points based on vibration attenuation values ​​reflecting the damping characteristics of the supports themselves. Then, it distinguishes between overall and local anomalies by utilizing the spatial distribution characteristics of these anomalies. For overall anomalies, it identifies whether they originate from interference from the operation of electromechanical equipment. For local anomalies, it confirms whether they represent actual damage to the connection nodes based on the degree of connection stiffness degradation. After confirming damage, it adaptively intensifies monitoring of the corresponding measuring points according to the degree of damage. This accurately distinguishes between vibration anomalies caused by environmental interference such as the operation of electromechanical equipment and sudden excitations, and vibration anomalies caused by actual damage to connection nodes. This avoids misreporting environmental interference as damage, resulting in wasted maintenance, and also avoids misjudging early minor loosening as interference, thus reducing false alarms and missed alarms and improving the reliability of seismic bracing safety early warning.

[0008] This invention determines whether there is an anomaly at the measuring point by comparing the vibration attenuation characterization value with a preset attenuation threshold. The subsequent discrimination process is only triggered when a statistically significant anomaly occurs, thus avoiding the consumption of complex discrimination calculations throughout the system and improving the timeliness of the abnormal response of the seismic support safety early warning.

[0009] This invention compares the spatial distribution discrimination coefficient with a preset distribution threshold, and in response to different comparison results, classifies anomalies as either global anomalies or local anomalies, thereby rapidly diverting the two types of anomalies along different branches, thus improving the processing efficiency of subsequent attribution and monitoring.

[0010] This invention filters out extrinsic interferences and promptly verifies the structural state under sudden external stimuli by classifying overall anomalies as mechanical and electrical equipment operation interference when the interference attribution confidence is greater than or equal to a preset attribution threshold, and classifies them as external stimuli when the attribution confidence is less than the preset attribution threshold, thereby improving the timeliness of post-earthquake damage investigation. Attached Figure Description

[0011] The present application will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0012] Figure 1 This is a schematic diagram of the module connection of the seismic bracing safety early warning system according to an embodiment of the present invention; Figure 2 This is a flowchart illustrating how the anomaly is determined to be either a global anomaly or a local anomaly based on the spatial distribution discrimination coefficient in the seismic bracing safety early warning system of this invention. Figure 3 This is a schematic diagram of the distribution discrimination module in the seismic bracing safety early warning system of this invention. Detailed Implementation

[0013] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0014] Please see Figure 1 As shown, this embodiment provides a seismic bracing safety early warning system, which is applied to the safety monitoring and early warning of seismic bracing for electromechanical pipelines such as water supply and drainage pipes, HVAC ducts, and cable trays in buildings. Pumps, fans, elevators, and other electromechanical equipment in buildings generate continuous vibrations during operation, and sudden excitations such as earthquakes and heavy object impacts can also cause vibrations in the bracing; these environmental disturbances and actual damage to connection nodes can also cause monitoring parameters to exceed preset thresholds.

[0015] The seismic bracing safety early warning system of this embodiment includes: The vibration acquisition module is used to acquire vibration signals from several measuring points on various seismic bracing and hangers within the building at a sampling frequency of 250Hz. The attenuation analysis module is connected to the vibration acquisition module and is used to determine the vibration attenuation characterization value of each measuring point based on the vibration signal, and to determine whether there is an abnormality at the corresponding measuring point based on the vibration attenuation characterization value. A distribution discrimination module, which is connected to the attenuation analysis module, is used to determine the spatial distribution discrimination coefficient based on the spatial distribution of the abnormal measurement points when the abnormality exists, and to determine whether the abnormality is a global abnormality or a local abnormality based on the spatial distribution discrimination coefficient. An interference attribution module, which is connected to the distribution discrimination module, is used to determine whether the overall anomaly originates from interference in the operation of electromechanical equipment based on the interference attribution confidence level when the overall anomaly is determined. The damage detection module, which is connected to the distribution discrimination module, is used to determine whether the local anomaly is damage to the connection node of the seismic bracing and hanger based on the connection stiffness degradation coefficient when the local anomaly is determined. The monitoring and control module is connected to the damage detection module and the vibration acquisition module respectively, and is used to adjust the sampling frequency of abnormal measuring points according to the connection stiffness degradation coefficient when damage is determined to be at the connection node of the seismic bracing.

[0016] It should be noted that the seismic bracing monitored in this embodiment is a conventional structure in the prior art. Seismic bracing is a seismic support facility that is firmly connected to the building structure and bears the main load of earthquake action. It mainly includes anchors, reinforcing rods, seismic connection components, pipe connection components, and seismic diagonal braces: Anchors are used to anchor the seismic bracing to the building structure, such as floor slabs or beams; The upper end of the reinforcing rod is connected to the anchor through the seismic connection component, and the lower end is directly or through a crossbeam to the pipe connection component, used to bear the vertical load of the pipeline; Pipe connection components, such as pipe clamps or U-shaped pipe clamps, are used to fix the pipeline to the seismic bracing; Seismic diagonal braces are connected between the reinforcing rod or crossbeam and the building structure. Seismic diagonal braces set perpendicular to the pipeline direction constitute lateral seismic support, and seismic diagonal braces set along the pipeline direction constitute longitudinal seismic support, used to bear the horizontal action caused by earthquakes. Accordingly, the connection nodes mentioned in this invention refer to the connection parts between the above-mentioned components. For example, they may be the anchoring parts between the anchor and the building structure, the connection parts between the reinforcing rod and the seismic connection components, the connection parts at both ends of the seismic brace, and the clamping parts of the pipeline connection components for the pipeline. The above-mentioned connection parts are usually bolted, which are prone to bolt loosening and anchoring failure under long-term vibration environment, resulting in local stiffness degradation of the connection nodes, which are the objects of monitoring and early warning in this system.

[0017] In this embodiment, the vibration acquisition module includes several vibration sensors, a data acquisition unit, and a time synchronization unit. The vibration sensors are arranged one-to-one at the measuring points of each seismic brace to sense the vibration signals at each measuring point in real time. The vibration sensors are piezoelectric accelerometers, and their range and frequency response range should cover the vibration magnitude and the first few natural frequencies of the seismic brace. Optionally, the measuring points are located at locations with larger amplitudes in the main vibration modes of the seismic brace, avoiding vibration mode nodes. For example, these could be the clamping points of pipe connection components on the pipeline, the points on the crossarm supporting the pipeline, or the middle of the reinforced hanger, to sensitively reflect changes in the dynamic characteristics of the seismic brace connection nodes. Each measuring point records its three-dimensional spatial coordinates (x, y, z), which serve as the location basis for the spatial distribution analysis performed by the distribution discrimination module. The data acquisition unit is connected to each vibration sensor and is used to synchronously sample each vibration signal according to the sampling frequency, and convert the analog vibration signal into a digital vibration signal sequence; the time synchronization unit is used to mark the sampling data of each measuring point with a unified timestamp to ensure the synchronization of cross-measuring point calculations such as cross-correlation coefficients and energy statistics.

[0018] The specific structure of the attenuation analysis module, distribution discrimination module, interference attribution module, damage detection module, and monitoring and control module is not limited. Each module and its units can be composed of logic components, including field-programmable components, computers, or microprocessors in computers.

[0019] It should be noted that the sampling frequency should be greater than twice the highest frequency to be monitored in order to satisfy the Nyquist sampling theorem and avoid frequency aliasing. Preferably, it should be more than 2.5 times the highest frequency to be monitored. In this embodiment, the highest frequency to be monitored is 100Hz, and the sampling frequency is usually set between 200Hz and 500Hz. In this embodiment, it is set to 250Hz, which can completely retain the spectral information of the main modes of the support and the excitation of the electromechanical equipment.

[0020] In this embodiment, the attenuation analysis module includes: The autocorrelation calculation unit is used to perform normalized autocorrelation calculation on the vibration signal of each measuring point within a preset time window of 2 seconds to obtain the autocorrelation function of each measuring point; The attenuation extraction unit is used to determine the attenuation characteristic quantity based on the attenuation rate of the autocorrelation function, and to determine the relative deviation between the attenuation characteristic quantity and the healthy attenuation baseline of the corresponding measurement point as the vibration attenuation characterization value, wherein the relative deviation is the ratio of the absolute value of the difference between the attenuation characteristic quantity and the healthy attenuation baseline to the healthy attenuation baseline.

[0021] Specifically, for a given measuring point, a discrete sequence of vibration signals x(n) within a preset time window is taken, where n = 1, 2, ... N is the number of sampling points within the window; normalized autocorrelation function Where τ is the time delay, and the denominator is the total energy of the signal within the window. Due to normalization, =1 and | |≤1, It is independent of the absolute amplitude of the signal, and only reflects the decay rate of waveform self-similarity as the time delay increases. It should be noted that normalized autocorrelation is a common technique in the field of digital signal processing. Its input is a discrete sequence of vibration signals within a preset time window, and its output is a sequence of dimensionless autocorrelation functions that vary with the time delay τ. It can be implemented based on fast Fourier transform or direct correlation method, which will not be elaborated here.

[0022] In this embodiment, the preset time window is used to capture vibration signals that can reflect the attenuation characteristics of the structure. Its value needs to include several vibration cycles so that the autocorrelation function can be fully attenuated within the window and the attenuation rate can be identified. It should not be too long to ensure the timeliness of anomaly detection. The preset time window is usually set between 1 second and 5 seconds. In this embodiment, it is set to 2 seconds.

[0023] Specifically, the decay characteristic is a quantity that quantitatively characterizes the decay rate of the autocorrelation function, and it can be determined by: performing an exponential fit on the envelope of the autocorrelation function. The attenuation coefficient λ obtained by fitting is used as the attenuation feature; alternatively, the time delay corresponding to the first attenuation of the autocorrelation function to a preset reference value, such as 0.5, can be used as the attenuation feature; or the integral value of the autocorrelation function within a preset time delay interval can also be used. In this embodiment, the exponentially fitted attenuation coefficient λ is used as the attenuation feature.

[0024] Let the current attenuation characteristic be A, and the healthy attenuation baseline of the corresponding measuring point be A0. Then, the vibration attenuation characterization value V = |A - A0| / A0. The healthy attenuation baseline A0 is the reference value of the attenuation characteristic at this measuring point under healthy conditions at the seismic bracing connection node. After the seismic bracing and hangers are installed, the connection nodes are tightened, and the system is confirmed to be undamaged, the vibration signal at the measuring point is repeatedly collected several times, and the attenuation characteristic is calculated for each measurement. The statistical mean is taken as A0. When there is a lack of measured data in the healthy state, numerical simulation results or laboratory calibration test data of seismic bracing and hangers of the same type and specification can be used to set the parameters. Using relative deviation can eliminate the baseline differences caused by differences in the layout location and bracing and hanger specifications of different measuring points, making the anomaly judgments of each measuring point comparable on the same dimensionless scale.

[0025] Loose or damaged connection nodes can alter the friction and damping characteristics of the structural contact surfaces, thereby changing the rate of vibration energy dissipation, which manifests as a change in the decay rate of the autocorrelation function. Normalized autocorrelation calculation eliminates the influence of external excitation amplitude, making the vibration decay characterization value sensitive only to the damping characteristics of the structure itself. It can reflect the state changes of connection nodes under passive monitoring conditions without measuring the excitation force.

[0026] In this embodiment, the attenuation analysis module further includes: The anomaly determination unit is used to determine that there is no anomaly at the corresponding measuring point when the vibration attenuation characterization value is less than the preset attenuation threshold of 0.2; and to determine that there is an anomaly at the corresponding measuring point when the vibration attenuation characterization value is greater than or equal to the preset attenuation threshold, and to identify the measuring point with the anomaly as an abnormal measuring point.

[0027] In this embodiment, the preset attenuation threshold is determined based on the normal fluctuation range of the attenuation characteristic quantity under healthy conditions and the change amplitude of the attenuation characteristic quantity caused by damage to the connection node: Relative deviation data of the attenuation characteristic quantity at each measuring point under healthy conditions are collected, and its mean plus three times the standard deviation is used as the statistical upper limit of normal fluctuation; the lower limit of the relative deviation under damaged conditions is determined through a connection node damage simulation experiment (such as artificially graded loosening of bolts); an appropriate value between the two is taken as the preset attenuation threshold. The preset attenuation threshold is usually set between 0.1 and 0.3; in this embodiment, it is set to 0.2, which can filter out normal fluctuations under healthy conditions while capturing changes in attenuation characteristics caused by early loosening of the connection node.

[0028] In a specific example, suppose the health attenuation baseline A0 = 2.0 at a certain measuring point, and the current attenuation characteristic A = 2.5 is obtained in a certain monitoring, then the vibration attenuation characterization value V = |2.5-2.0| / 2.0 = 0.25 > 0.2, and it is determined that there is an anomaly at the measuring point; if another measurement shows A = 2.1, then V = 0.05 < 0.2, and it is determined that there is no anomaly at the measuring point.

[0029] Please see Figure 3 As shown, in this embodiment, the distribution discrimination module includes: The synchronization determination unit is used to calculate the cross-correlation coefficients between the vibration signals of each of the abnormal measuring points during the same acquisition period, and to determine the arithmetic mean of the cross-correlation coefficients as the synchronization degree. The clustering determination unit is used to determine the spatial coordinates of each abnormal measuring point according to the installation position of each abnormal measuring point, determine two abnormal measuring points with a spatial distance of less than 3 meters as adjacent measuring points, divide the abnormal measuring points with direct or indirect adjacent relationships into the same abnormal cluster according to the adjacent relationship, count the number of measuring points contained in each abnormal cluster, and determine the clustering degree as the ratio of the maximum value to the total number of abnormal measuring points. The coefficient determination unit is used to determine the spatial distribution discrimination coefficient based on the ratio of the aggregation degree to the synchronization degree.

[0030] Specifically, suppose there are p abnormal measurement points, where p ≥ 2. For any two abnormal measurement points, calculate the normalized cross-correlation coefficient of their vibration signal sequences within the same acquisition period. Then, take the arithmetic mean of the cross-correlation coefficients of all p(p-1) / 2 measurement point pairs to obtain the synchronization degree C. It should be noted that the calculation of the cross-correlation coefficient is a common technique in the field of digital signal processing. Its input is the vibration signal sequences of the two measurement points within the same acquisition period, and the output is a dimensionless correlation coefficient characterizing the similarity between the two sequences. It can be implemented through time-domain correlation operations or frequency-domain cross-spectral methods, which will not be elaborated here.

[0031] Specifically, the clustering determination unit reads the spatial coordinates of each anomalous measurement point, calculates the spatial distance between any two anomalous measurement points, and determines two anomalous measurement points whose spatial distance is less than a preset connectivity threshold as adjacent measurement points. Then, based on the adjacency relationship, anomalous measurement points with direct or indirect adjacency relationships are grouped into the same anomalous cluster, and the number of measurement points contained in each anomalous cluster is counted. The ratio of the maximum value to the total number of anomalous measurement points p is determined as the clustering degree G. It should be noted that the above clustering is a common technique in graph theory and data mining. Its input is the spatial coordinates of each anomalous measurement point and the adjacency relationship determined by the preset connectivity threshold. The output is several anomalous clusters and the number of measurement points contained in each cluster. This can be implemented using a disjoint-set data structure algorithm or a density-based clustering algorithm such as DBSCAN, which will not be elaborated here.

[0032] In this embodiment, the preset connectivity threshold is the critical distance for determining whether two abnormal measuring points are spatially adjacent. Its value should be greater than the maximum distance between measuring points on the same seismic bracing system and less than the minimum installation distance between adjacent seismic bracing systems. The width of a single-pipe seismic bracing system is typically less than 1 meter, while the width of a portal or integrated seismic bracing system spanning multiple pipelines can reach 2 to 3 meters. The maximum spacing between lateral seismic bracing systems is 6 to 12 meters, and the maximum spacing between longitudinal seismic bracing systems is 12 to 24 meters. The installation distance between adjacent seismic bracing systems is significantly greater than the dimensions of the system itself. Based on these principles, the preset connectivity threshold is typically set between 2 and 4 meters. In this embodiment, it is set to 3 meters, which allows abnormal measuring points on the same bracing system to cluster together, while avoiding the accidental merging of measuring points on adjacent bracing systems. Optionally, for areas with smaller spacing between adjacent bracing systems, such as denser bracing at bends or halved spacing in reconstruction projects, the preset connectivity threshold can be appropriately lowered, or clustering can be assisted by combining the numbering information of the bracing systems to which each measuring point belongs.

[0033] The coefficient determination unit uses the ratio of clustering to synchronization as the spatial distribution discrimination coefficient. Environmental excitations such as interference from electromechanical equipment operation and earthquakes are transmitted along the building structure to multiple seismic supports, causing multiple spatially dispersed measuring points to be driven by common excitation and synchronize their waveforms. In this case, the clustering is low, the synchronization is high, and the spatial distribution discrimination coefficient is small. However, actual damage to connecting nodes only affects the supporting supports where they are located. Abnormal measuring points are spatially concentrated, and the response of each measuring point is mainly determined by local dynamic characteristics, resulting in relatively weak waveform synchronization. In this case, the clustering is high, the synchronization is low, and the spatial distribution discrimination coefficient is large. Since the numerator and denominator change in opposite directions under the two types of anomalies, their fusion in the form of a ratio further amplifies the differences in spatial distribution between overall and local anomalies, improving the discrimination and robustness of the discrimination.

[0034] Please see Figure 2 As shown, in this embodiment, the distribution discrimination module further includes: The distribution determination unit determines the anomaly as a global anomaly when the spatial distribution discrimination coefficient is less than a preset distribution threshold of 1.0; and determines the anomaly as a local anomaly when the spatial distribution discrimination coefficient is greater than or equal to the preset distribution threshold.

[0035] In this embodiment, the preset distribution threshold is determined through numerical simulation or field / laboratory tests: several overall abnormal operating conditions are constructed, such as starting water pumps, fans, and other electromechanical equipment, or applying simulated seismic excitation, and several local abnormal operating conditions are constructed, such as manually loosening the connecting bolts of a certain hanger. The spatial distribution discrimination coefficient under each operating condition is calculated, and an appropriate value between the upper limit of the coefficient under the overall abnormal operating condition and the lower limit of the coefficient under the local abnormal operating condition is taken as the preset distribution threshold. The preset distribution threshold is usually set between 0.5 and 2.0, and in this embodiment it is set to 1.0.

[0036] In a specific example, when a water pump starts on a floor, its vibration is transmitted along the structure, causing six measuring points scattered across different supports to be identified as abnormal. The calculated synchronicity C = 0.85, the six abnormal measuring points belong to four anomalous clusters, the largest cluster containing two measuring points, and the clustering degree G = 2 / 6 ≈ 0.33. Therefore, the spatial distribution discrimination coefficient L = 0.33 / 0.85 ≈ 0.39 < 1.0, indicating a systemic anomaly. As another example, a loose connecting bolt on a support causes four adjacent measuring points on it to be identified as abnormal. The calculated synchronicity C = 0.45, the four abnormal measuring points cluster in the same anomalous cluster, and the clustering degree G = 1.0. Therefore, L = 1.0 / 0.45 ≈ 2.22 > 1.0, indicating a localized anomaly.

[0037] In this embodiment, the interference attribution module includes: A frequency determination unit is used to obtain the dominant frequency of the vibration signal corresponding to the overall anomaly, calculate the frequency deviation between the dominant frequency and each characteristic frequency in the preset electromechanical equipment characteristic frequency library, and take the smallest frequency deviation as the minimum frequency deviation; if the minimum frequency deviation is greater than or equal to the preset frequency deviation upper limit of 2Hz, the frequency matching degree is determined to be zero; if the minimum frequency deviation is less than the preset frequency deviation upper limit, the difference between 1 and the ratio of the minimum frequency deviation to the preset frequency deviation upper limit is determined as the frequency matching degree. A stability determination unit is used to divide the vibration signal corresponding to the overall anomaly into multiple consecutive time windows, calculate the vibration energy of each time window, and calculate the coefficient of variation of the vibration energy of each time window; if the coefficient of variation is greater than or equal to a preset upper limit of the coefficient of variation, the stability is determined to be zero; if the coefficient of variation is less than the preset upper limit of the coefficient of variation of 0.3, the difference between 1 and the ratio of the coefficient of variation to the preset upper limit of the coefficient of variation is determined as the stability. An energy determination unit is used to calculate the energy deviation rate between the total energy value of the vibration signal corresponding to the overall anomaly and the vibration energy reference value during stable operation of the electromechanical equipment. The energy deviation rate is the ratio of the absolute value of the difference between the total energy value and the vibration energy reference value to the vibration energy reference value. If the energy deviation rate is greater than or equal to a preset energy deviation upper limit of 0.25, the energy matching degree is determined to be zero. If the energy deviation rate is less than the preset energy deviation upper limit, the difference between 1 and the ratio of the energy deviation rate to the preset energy deviation upper limit is determined as the energy matching degree. The attribution determination unit is used to determine the minimum value among the frequency matching degree, the stability degree, and the energy matching degree as the interference attribution confidence degree.

[0038] Specifically, the frequency determination unit performs spectral analysis (such as Fast Fourier Transform) on the vibration signal corresponding to the overall anomaly, and takes the frequency corresponding to the spectral peak with the largest amplitude as the dominant frequency of the spectrum. The preset electromechanical equipment characteristic frequency library is a collection of operating characteristic frequencies of various electromechanical equipment in the building, which is constructed as follows: for electromechanical equipment in the building that may cause vibration interference, such as water pumps, fans, elevator motors, and air conditioning units, their operating characteristic frequencies are measured under their rated operating conditions, or their operating characteristic frequencies, such as the rotational frequency and its harmonics of rotating machinery, are calculated based on their nameplate parameters, such as rotational speed, number of pole pairs, and number of blades, and each characteristic frequency is entered into the library; for equipment operating by frequency conversion, the characteristic frequency range of its typical operating frequency band is entered. It should be noted that the construction of this characteristic frequency library is a common technical means that can be completed by those skilled in the art based on equipment parameters and conventional spectrum testing, and will not be elaborated here.

[0039] In this embodiment, the preset frequency deviation upper limit is determined based on the normal fluctuation range of the characteristic frequency caused by load changes and speed fluctuations of the electromechanical equipment and the frequency resolution of the spectrum analysis. It is usually set between 1Hz and 5Hz. In this embodiment, it is set to 2Hz, which can accommodate the normal fluctuation of the equipment frequency while maintaining the accuracy of the identification of the interference source.

[0040] Specifically, the stationary determination unit divides the vibration signal corresponding to the overall anomaly into multiple continuous and non-overlapping time windows, calculates the vibration energy of each time window, takes the sum of the squares of the signal amplitudes within the window, and determines the coefficient of variation by the ratio of the standard deviation to the mean of the vibration energy in each time window. When electromechanical equipment is running continuously and stably, its vibration energy fluctuates less along the time axis, resulting in a smaller coefficient of variation; however, sudden excitations such as earthquakes and impacts cause energy mutations, significantly increasing the coefficient of variation. In this embodiment, the preset upper limit of the coefficient of variation is determined based on the statistical distribution of the coefficient of variation of vibration energy under stable operating conditions of the electromechanical equipment, taking its statistical upper limit as the mean plus three times the standard deviation; the preset upper limit of the coefficient of variation is usually set between 0.1 and 0.3, and in this embodiment it is set to 0.3, which can distinguish between the steady vibration of continuous operation of the electromechanical equipment and the violent energy fluctuations caused by sudden excitations.

[0041] Specifically, the energy determination unit calculates the total energy value of the vibration signal corresponding to the overall anomaly during the abnormal period, and determines the energy deviation rate between it and the vibration energy benchmark value when the electromechanical equipment is operating stably. The vibration energy benchmark value is the statistical average of multiple measurements of the total energy of the vibration signal over a period of equal length to the abnormal period under stable operating conditions of the electromechanical equipment. In this embodiment, the preset energy deviation upper limit is determined based on the statistical upper limit of the normal fluctuation of the relative deviation of the total energy under stable operating conditions of the electromechanical equipment, and is usually set between 0.1 and 0.4. In this embodiment, it is set to 0.25, which can accommodate the normal fluctuation of the energy of the electromechanical equipment while identifying significant energy anomalies caused by earthquakes, impacts, etc.

[0042] Furthermore, the attribution determination unit determines the minimum value among frequency matching degree, stationarity degree, and energy matching degree as the interference attribution confidence level. Electromechanical equipment operation interference simultaneously possesses stable characteristics in three dimensions: frequency characteristics, time stationarity, and energy magnitude. Sudden excitations such as earthquakes and impacts are unlikely to be similar to electromechanical equipment interference in all three dimensions simultaneously. When taking the minimum value of the three, if any dimension fails to meet the requirement, the confidence level will be lowered. Only when all three dimensions are met simultaneously will the confidence level be high, thereby avoiding the misjudgment of sudden excitations as electromechanical equipment interference and filtering them out, preventing missed detections.

[0043] In this embodiment, the interference attribution module further includes: The interference determination unit is used to determine that the overall anomaly originates from the operation interference of electromechanical equipment and filter out the overall anomaly when the interference attribution confidence is greater than or equal to the preset attribution threshold of 0.6; and to determine that the overall anomaly originates from external excitation when the interference attribution confidence is less than the preset attribution threshold, and to trigger the damage detection module to perform damage detection on each of the measuring points.

[0044] It should be noted that, in this invention, the external excitation refers to environmental excitations such as earthquakes, strong winds, and impacts acting on the overall building structure, excluding vibration interference caused by the operation of electromechanical equipment.

[0045] In this embodiment, the preset attribution threshold is determined based on the stringency requirements for interference filtering: a higher threshold means that interference is only filtered out when all three matching degrees are high, making it less likely to miss sudden stimuli; a lower threshold means that anomalies are more easily attributed to interference and filtered out. The preset attribution threshold is typically set between 0.5 and 0.8, and in this embodiment it is set to 0.6, which can reliably filter out normal interference from electromechanical equipment while retaining and transferring external sudden stimuli that do not conform to the characteristics of electromechanical equipment to damage detection.

[0046] In a specific example, spectral analysis of a certain overall anomaly revealed that the minimum frequency deviation between its dominant frequency and the characteristic frequency of a water pump in the reservoir was 0.5 Hz, with a frequency matching degree of 1 - 0.5 / 2 = 0.75. The energy was stable across time windows, with a stability of 0.8; the energy deviation rate was 0.08, with an energy matching degree of 1 - 0.08 / 0.25 = 0.68; and the interference attribution confidence score, being the minimum of the three (0.68 > 0.6), was determined to be interference from the operation of electromechanical equipment and was filtered out. Similarly, during an earthquake, the vibration signal frequency was chaotic, the energy abruptly changed, and the total energy far exceeded the energy benchmark for stable operation of electromechanical equipment. The frequency matching degree, stability, and energy matching degree all approached zero, and the interference attribution confidence score approached zero and was less than 0.6, indicating external excitation. This triggered the damage detection module to perform damage detection at each measuring point, achieving comprehensive post-earthquake damage assessment.

[0047] In this embodiment, the damage detection module includes: The frequency identification unit is used to perform modal identification on the vibration signal of the abnormal measuring point corresponding to the local anomaly to obtain the current natural frequency of the corresponding seismic support. The degradation calculation unit is used to determine the connection stiffness degradation coefficient by subtracting the square of the ratio of the current inherent frequency to the preset healthy fundamental frequency of 10Hz from 1.

[0048] Specifically, the frequency identification unit performs modal parameter identification on the vibration signals of abnormal measuring points corresponding to local anomalies, and extracts the current natural frequency f of the corresponding seismic bracing. Modal identification can employ working modal analysis methods under environmental excitation, such as frequency domain decomposition or random subspace methods. The input is the vibration response time series of the abnormal measuring points, and the output is the modal parameters of the seismic bracing: natural frequency, damping ratio, and mode shape. The first-order natural frequency is taken as the current natural frequency f. The response energy of the first-order mode under environmental excitation is the largest, and the identification result is the most reliable. It should be noted that the above modal identification method is a common technique used by those skilled in the art to identify the natural frequencies of a structure without artificial excitation or measurement of excitation force, and will not be elaborated here.

[0049] Specifically, let the current natural frequency be f, and the preset healthy fundamental frequency be f0, then the connection stiffness degradation coefficient D = 1 - (f / f0) 2 Seismic bracing can be simplified as a mass-spring system, where the natural frequency and connection stiffness f are proportional to the square root of k. Therefore, the relative degradation of the connection stiffness is 1 - (f / f0). 2 The connection stiffness degradation coefficient is numerically equal to the relative degradation rate of the connection stiffness: a connection stiffness degradation coefficient D=0 indicates no degradation of the connection stiffness, and the closer the connection stiffness degradation coefficient D is to 1, the more severe the degradation of the connection stiffness. The preset healthy fundamental frequency f0 is the reference value of the natural frequency of the same order as the current natural frequency f under the healthy state of the seismic bracing connection node, that is, the first-order natural frequency under the healthy state.

[0050] Modal identification is performed under healthy conditions after the seismic bracing is installed, the connection nodes are tightened, and it has been inspected and confirmed to be undamaged. This process is repeated several times, and the statistical mean is taken as f0. When measured data of the healthy condition is lacking, it can be set through numerical simulation based on the specifications of the seismic bracing and the mass of the pipeline it supports. It should be noted that the specific value of f0 depends on the structural form, specifications, and mass of the seismic bracing and the pipeline it supports. Furthermore, the natural frequency of the seismic bracing differs between the unloaded and fully loaded states of the pipeline. Therefore, it is advisable to set it according to the fully loaded state during calibration. For seismic bracing of common specifications in building electromechanical engineering, its first natural frequency is usually in the range of 5Hz to 30Hz. In this embodiment, it is set to 10Hz. This value is within the typical range of the first natural frequency of common specifications of seismic bracing and can sensitively reflect the degradation of connection stiffness using this as a health benchmark.

[0051] In this embodiment, the damage detection module further includes: The damage determination unit is used to determine that the local anomaly is damage to the connection node of the seismic bracing when the connection stiffness degradation coefficient is greater than or equal to a preset degradation threshold of 0.19; and to determine that the local anomaly is a non-damaging anomaly when the connection stiffness degradation coefficient is less than the preset degradation threshold.

[0052] In this embodiment, the preset degradation threshold is determined based on the normal fluctuation range of the natural frequency under healthy conditions and the decrease in natural frequency caused by the smallest detectable damage to the connection node: the lower limit constraint is the connection stiffness degradation coefficient corresponding to the fluctuation range of the natural frequency under healthy conditions from multiple identification results, and the upper limit constraint is the connection stiffness degradation coefficient corresponding to the smallest detectable damage measured by a connection node damage grading simulation test, such as artificially graded loosening of bolts. An appropriate value between the two is taken as the preset degradation threshold. The preset degradation threshold is usually set between 0.1 and 0.3. In this embodiment, it is set to 0.19, which corresponds to a natural frequency decrease of about 10% compared to the healthy fundamental frequency. This can filter out normal fluctuations in the natural frequency while capturing stiffness degradation caused by early loosening of the connection node.

[0053] In a specific example, assuming the healthy fundamental frequency of a seismic bracing system is f0=10Hz, and a local anomaly is identified by modal analysis to have a current natural frequency of f=8Hz, then the connection stiffness degradation coefficient D=1-(8 / 10). 2 =0.36>0.19, indicating damage to the connection node of the seismic bracing; if another identification shows f=9.5Hz, then D=1-(9.5 / 10). 2 ≈0.098<0.19, judged as non-invasive abnormality.

[0054] In this embodiment, the monitoring and control module includes: The difference determination unit is used to determine the difference between the connection stiffness degradation coefficient, which is determined to be the damage of the seismic bracing connection node, and the preset degradation threshold, and record it as the degradation difference; the sampling control unit is used to increase the sampling frequency of the corresponding measuring point according to the degradation difference, wherein the increase in the sampling frequency is positively correlated with the degradation difference, and input the vibration signal collected after increasing the sampling frequency to the attenuation analysis module.

[0055] Specifically, the degradation difference ΔD is the difference between the connection stiffness degradation coefficient D of the confirmed damage and the preset degradation threshold. Let the base sampling frequency be F0 and the adjusted sampling frequency be F1, then F1 = F0 × (1 + β × ΔD), where β is the positive correlation adjustment coefficient. The more severe the damage, the larger the degradation difference, and the greater the increase in sampling frequency, allowing for more precise capture of damage evolution details. For minor damage, only a moderate increase is needed to avoid unnecessary resource consumption, thus tilting monitoring resources towards measurement points with more severe damage.

[0056] In this embodiment, the value of the positive correlation adjustment coefficient β should be such that the adjusted sampling frequency does not exceed the upper limit of the maximum sampling frequency of the sampling device under the maximum expected degradation difference. β is usually set between 1 and 4, and is set to 2 in this embodiment. After increasing the sampling frequency, the acquired vibration signal is re-input to the attenuation analysis module to enter a new round of attenuation analysis, distribution discrimination and damage detection, thereby realizing closed-loop encrypted tracking of damage evolution.

[0057] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A seismic bracing safety early warning system, characterized in that, include: The vibration acquisition module is used to acquire vibration signals from several measuring points on various seismic bracing and hangers within the building at a sampling frequency. The attenuation analysis module is connected to the vibration acquisition module and is used to determine the vibration attenuation characterization value of each measuring point based on the vibration signal, and to determine whether there is an abnormality at the corresponding measuring point based on the vibration attenuation characterization value. A distribution discrimination module, which is connected to the attenuation analysis module, is used to determine the spatial distribution discrimination coefficient based on the spatial distribution of the abnormal measurement points when the abnormality exists, and to determine whether the abnormality is a global abnormality or a local abnormality based on the spatial distribution discrimination coefficient. An interference attribution module, which is connected to the distribution discrimination module, is used to determine whether the overall anomaly originates from interference in the operation of electromechanical equipment based on the interference attribution confidence level when the overall anomaly is determined. The damage detection module, which is connected to the distribution discrimination module, is used to determine whether the local anomaly is damage to the connection node of the seismic bracing and hanger based on the connection stiffness degradation coefficient when the local anomaly is determined. The monitoring and control module is connected to the damage detection module and the vibration acquisition module respectively, and is used to adjust the sampling frequency of abnormal measuring points according to the connection stiffness degradation coefficient when damage is determined to be at the connection node of the seismic bracing.

2. The seismic bracing safety early warning system according to claim 1, characterized in that, The attenuation analysis module includes: The autocorrelation calculation unit is used to perform normalized autocorrelation calculation on the vibration signal of each measuring point within a preset time window to obtain the autocorrelation function of each measuring point. The attenuation extraction unit is used to determine the attenuation characteristic quantity based on the attenuation rate of the autocorrelation function, and to determine the relative deviation between the attenuation characteristic quantity and the healthy attenuation baseline of the corresponding measurement point as the vibration attenuation characterization value, wherein the relative deviation is the ratio of the absolute value of the difference between the attenuation characteristic quantity and the healthy attenuation baseline to the healthy attenuation baseline.

3. The seismic bracing safety early warning system according to claim 2, characterized in that, The attenuation analysis module also includes: The anomaly determination unit is used to determine that there is no anomaly at the corresponding measuring point when the vibration attenuation characterization value is less than the preset attenuation threshold; and to determine that there is an anomaly at the corresponding measuring point when the vibration attenuation characterization value is greater than or equal to the preset attenuation threshold, and to identify the measuring point with the anomaly as an abnormal measuring point.

4. The seismic bracing safety early warning system according to claim 3, characterized in that, The distribution discrimination module includes: The synchronization determination unit is used to calculate the cross-correlation coefficients between the vibration signals of each of the abnormal measuring points during the same acquisition period, and to determine the arithmetic mean of the cross-correlation coefficients as the synchronization degree. The clustering determination unit is used to determine the spatial coordinates of each abnormal measuring point according to the installation position of each abnormal measuring point, determine two abnormal measuring points whose spatial distance is less than a preset connectivity threshold as adjacent measuring points, divide the abnormal measuring points with direct or indirect adjacent relationships into the same abnormal cluster according to the adjacent relationship, count the number of measuring points contained in each abnormal cluster, and determine the clustering degree as the ratio of the maximum value to the total number of abnormal measuring points. The coefficient determination unit is used to determine the spatial distribution discrimination coefficient based on the ratio of the aggregation degree to the synchronization degree.

5. The seismic bracing safety early warning system according to claim 4, characterized in that, The distribution discrimination module also includes: The distribution determination unit determines the anomaly as a global anomaly when the spatial distribution discrimination coefficient is less than a preset distribution threshold; and determines the anomaly as a local anomaly when the spatial distribution discrimination coefficient is greater than or equal to the preset distribution threshold.

6. The seismic bracing safety early warning system according to claim 5, characterized in that, The interference attribution module includes: A frequency determination unit is used to obtain the dominant frequency of the vibration signal corresponding to the overall anomaly, calculate the frequency deviation between the dominant frequency and each characteristic frequency in a preset electromechanical equipment characteristic frequency library, and take the smallest frequency deviation as the minimum frequency deviation; if the minimum frequency deviation is greater than or equal to a preset upper limit of frequency deviation, the frequency matching degree is determined to be zero; if the minimum frequency deviation is less than the preset upper limit of frequency deviation, the difference between 1 and the ratio of the minimum frequency deviation to the preset upper limit of frequency deviation is determined as the frequency matching degree. A stability determination unit is used to divide the vibration signal corresponding to the overall anomaly into multiple consecutive time windows, calculate the vibration energy of each time window, and calculate the coefficient of variation of the vibration energy of each time window; if the coefficient of variation is greater than or equal to a preset upper limit of the coefficient of variation, the stability is determined to be zero; if the coefficient of variation is less than the preset upper limit of the coefficient of variation, the difference between 1 and the ratio of the coefficient of variation to the preset upper limit of the coefficient of variation is determined as the stability. An energy determination unit is used to calculate the energy deviation rate between the total energy value of the vibration signal corresponding to the overall anomaly and the vibration energy reference value during stable operation of the electromechanical equipment. The energy deviation rate is the ratio of the absolute value of the difference between the total energy value and the vibration energy reference value to the vibration energy reference value. If the energy deviation rate is greater than or equal to a preset energy deviation upper limit, the energy matching degree is determined to be zero. If the energy deviation rate is less than the preset energy deviation upper limit, the difference between 1 and the ratio of the energy deviation rate to the preset energy deviation upper limit is determined as the energy matching degree. The attribution determination unit is used to determine the minimum value among the frequency matching degree, the stability degree, and the energy matching degree as the interference attribution confidence degree.

7. The seismic bracing safety early warning system according to claim 6, characterized in that, The interference attribution module further includes: The interference determination unit is used to determine that the overall anomaly originates from the operation interference of electromechanical equipment and filter out the overall anomaly when the interference attribution confidence is greater than or equal to a preset attribution threshold; and to determine that the overall anomaly originates from external excitation when the interference attribution confidence is less than the preset attribution threshold, and to trigger the damage detection module to perform damage detection on each of the measuring points.

8. The seismic bracing safety early warning system according to claim 5, characterized in that, The damage detection module includes: The frequency identification unit is used to perform modal identification on the vibration signal of the abnormal measuring point corresponding to the local anomaly to obtain the current natural frequency of the corresponding seismic support. The degradation calculation unit is used to determine the connection stiffness degradation coefficient by subtracting the square of the ratio of the current natural frequency to the preset healthy fundamental frequency from 1.

9. The seismic bracing safety early warning system according to claim 8, characterized in that, The damage detection module also includes: The damage determination unit is used to determine that the local anomaly is damage to the seismic bracing connection node when the connection stiffness degradation coefficient is greater than or equal to a preset degradation threshold; and to determine that the local anomaly is a non-damaging anomaly when the connection stiffness degradation coefficient is less than the preset degradation threshold.

10. The seismic bracing safety early warning system according to claim 9, characterized in that, The monitoring and control module includes: The difference determination unit is used to determine the difference between the connection stiffness degradation coefficient and the preset degradation threshold that is determined to be the damage of the seismic bracing connection node, and record it as the degradation difference. The sampling control unit is used to increase the sampling frequency of the corresponding measuring point according to the degradation difference, wherein the increase in the sampling frequency is positively correlated with the degradation difference, and the vibration signal collected after increasing the sampling frequency is input to the attenuation analysis module.

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