Bridge monitoring method, device, system and storage medium based on monitoring equipment

Abstract

The present application relates to a bridge monitoring method, device, system and storage medium based on a monitoring device, the method comprising: acquiring displacement data, crack data and vibration data collected by a plurality of monitoring devices deployed on a bridge structure; sequentially performing feature change calculation on the displacement data, the crack data and the vibration data to obtain displacement change rate, crack width change amount and structure vibration offset amount; performing state recognition on the displacement change rate, the crack width change amount and the structure vibration offset amount based on a preset early warning condition to obtain structure state information; and performing state analysis and early warning construction according to the structure state information to obtain an early warning report. The present application can overcome the one-sidedness of traditional single monitoring means by simultaneously acquiring three types of heterogeneous monitoring data, i.e., displacement, crack and vibration, and performing fusion analysis, thereby achieving more comprehensive evaluation of the health status of the bridge structure.

Description

Technical Field

[0001] This invention relates to the technical field of bridge monitoring, and in particular to a bridge monitoring method, device, system, and storage medium based on monitoring equipment. Background Technology

[0002] Currently, bridge monitoring practices widely rely on periodic manual inspections and distributed data collection using single-type sensors. This method has significant limitations: on the one hand, manual inspections are inefficient and time-consuming, making it difficult to capture sudden structural changes, and are subject to subjective judgment differences; on the other hand, analyzing a single physical quantity in isolation cannot comprehensively reflect the overall health status and damage evolution mechanism of the bridge structure, easily leading to misjudgments or omissions. Summary of the Invention

[0003] The main objective of this invention is to provide a bridge monitoring method, device, system, and storage medium based on monitoring equipment. This invention can simultaneously acquire three types of heterogeneous monitoring data—displacement, cracks, and vibration—and perform fusion analysis on them, thereby overcoming the limitations of traditional single monitoring methods and achieving a more comprehensive assessment of the health status of bridge structures.

[0004] To achieve the above objectives, the present invention provides a bridge monitoring method based on monitoring equipment, comprising: Acquire displacement, crack, and vibration data collected by multiple monitoring devices deployed on the bridge structure; The displacement data, crack data, and vibration data are sequentially subjected to characteristic change calculations to obtain the displacement change rate, crack width change, and structural vibration offset. Based on preset early warning conditions, the displacement change rate, the crack width change, and the structural vibration offset are identified to obtain structural state information. Based on the structural state information, state analysis and early warning construction are performed to obtain an early warning report.

[0005] Furthermore, the acquisition of displacement data, crack data, and vibration data collected by multiple monitoring devices deployed at the bridge structure locations includes: The monitoring equipment synchronously collects the raw displacement sequence output by the GNSS receiver, the raw crack width data output by the crack gauge, and the raw triaxial vibration data output by the vibration sensor according to a preset time period. The elevation coordinate values ​​corresponding to each sampling time are extracted from the original displacement sequence to form the displacement data; The crack data is formed by extracting the measurement value corresponding to each sampling time from the raw crack width data; The vibration data is generated by selecting the corresponding axial acceleration component value from the triaxial vibration raw data based on the preset principal vibration direction of the bridge structure.

[0006] Further, the step of sequentially calculating the characteristic changes of the displacement data, the crack data, and the vibration data to obtain the displacement change rate, the crack width change, and the structural vibration offset includes: The displacement rate is obtained by calculating the difference between adjacent points in the elevation coordinate sequence of the displacement data based on the first set time interval, and by averaging all the differences between adjacent points. The crack data is subjected to a three-point sliding median filter to obtain a width filter sequence. The difference between the first and last values ​​of the width filter sequence in a second set time interval is calculated to obtain the crack width change. The vibration data is segmented into equal-length intervals and subjected to time-frequency transformation to obtain a segmented vibration spectrum. The highest frequency point in the segmented vibration spectrum is identified, and the absolute value of the difference between the highest frequency point and the preset reference frequency is calculated to obtain the structural vibration offset.

[0007] Further, the step of segmenting the vibration data into equal-length intervals and performing time-frequency transformation to obtain the segmented vibration spectrum includes: The vibration data is divided into a continuous and non-overlapping data segment according to the equal-length intervals; For each of the data segments of the first type, a Hanning window sequence with the same length as the data segment of the first type is generated, and each data point in the data segment of the first type is multiplied by the window coefficient at the corresponding position in the Hanning window sequence to obtain the windowed data segment; Perform a spectral transformation on each windowed data segment and calculate the square of the amplitude corresponding to each frequency point in each complex spectrum to obtain the power spectrum. Integrate all the power spectra to obtain the vibration segment spectrum.

[0008] Furthermore, the process of identifying the displacement rate of change, the crack width change, and the structural vibration offset based on preset early warning conditions to obtain structural state information includes: When the displacement change rate is higher than the rate threshold of the preset warning condition, a first abnormality flag is generated; otherwise, the displacement change rate is marked as normal. When the change in crack width exceeds the width change threshold of the preset early warning condition, a second abnormality flag is generated; otherwise, the change in crack width is marked as normal. When the structural vibration offset is greater than the frequency offset threshold of the preset early warning condition, a third abnormality identifier is generated; otherwise, the structural vibration offset is marked as normal. Based on the mapping conditions of the preset early warning conditions, the first abnormal identifier, the second abnormal identifier, and the third abnormal identifier are integrated into the structural status information.

[0009] Furthermore, the step of performing state analysis and early warning construction based on the structural state information to obtain an early warning report includes: The structural status information is matched with a preset early warning rule base to determine the early warning level. If the structural status information is completely consistent with any combination of identifiers in the preset early warning rule base, the early warning level of the identifier combination is marked as the current early warning level of the structural status information; Based on the displacement change rate, crack width change, and structural vibration fundamental frequency offset corresponding to the current warning level, a warning record is obtained; Based on the current warning level, the corresponding warning report template is extracted from the preset warning rule base; According to the current warning level, all the warning records are sequentially filled into the warning report template to obtain the warning report.

[0010] Furthermore, based on the displacement change rate, crack width change, and structural vibration fundamental frequency offset corresponding to the current warning level, a warning record is obtained, including: Obtain the monitoring location identifier corresponding to the monitoring device that triggered the current warning level, and obtain the acquisition timestamps of the displacement data, the crack data, and the vibration data; Based on the current warning level, the corresponding handling prompt information is extracted from the preset warning rule base; The warning record is generated by combining the current warning level, the displacement change rate, the crack width change, the structural vibration fundamental frequency offset, the monitoring location identifier, the acquisition timestamp, and the handling prompt information according to a predetermined recording format.

[0011] The present invention also provides a bridge monitoring device based on monitoring equipment, applied to any one of the bridge monitoring methods based on monitoring equipment described above, comprising: The acquisition module is used to acquire displacement data, crack data, and vibration data collected by multiple monitoring devices deployed on the bridge structure. The analysis module is used to perform characteristic change calculations on the displacement data, crack data and vibration data in sequence to obtain the displacement change rate, crack width change and structural vibration offset. The association module is used to identify the state of the displacement change rate, the crack width change and the structural vibration offset based on preset early warning conditions, so as to obtain structural state information. The processing module is used to perform state analysis and early warning construction based on the structural state information, and to obtain an early warning report.

[0012] The present invention also provides a bridge monitoring system based on monitoring equipment, comprising: Memory, used to store programs; A processor is configured to execute the program to implement the steps of a bridge monitoring method based on a monitoring device as described in any of the preceding claims.

[0013] The present invention also provides a storage medium storing computer instructions for causing a computer to perform any of the methods described above.

[0014] The present invention provides a bridge monitoring method, device, system, and storage medium based on monitoring equipment, which has the following beneficial effects: By simultaneously acquiring and fusing heterogeneous monitoring data on displacement, cracks, and vibration, the limitations of traditional single-monitoring methods are overcome, enabling a more comprehensive assessment of the bridge's structural health. Real-time characteristic change calculations are performed on multi-source monitoring data to directly obtain key indicators such as displacement change rate, crack width change, and structural vibration offset. This transforms massive amounts of raw data into characteristic parameters directly usable for condition assessment, significantly improving data processing efficiency and the timeliness of condition perception. Automated condition identification and tiered early warning construction based on preset warning conditions for these characteristic parameters transforms manual experience-based judgment into standardized analytical logic, reducing the risk of missed and false alarms and providing structured early warning reports for maintenance decisions. Attached Figure Description

[0015] Figure 1 This is a flowchart of a bridge monitoring method based on monitoring equipment provided by the present invention; Figure 2 This is a structural diagram of a bridge monitoring device based on monitoring equipment provided by the present invention; Figure 3 This is a structural diagram of a bridge monitoring system based on monitoring equipment provided by the present invention.

[0016] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0018] The present invention will now be further described in conjunction with the accompanying drawings and specific embodiments.

[0019] Reference Figure 1 As shown, the present invention provides a bridge monitoring method based on monitoring equipment, comprising: Step S1: Acquire displacement data, crack data, and vibration data collected by multiple monitoring devices deployed on the bridge structure; Specifically, at pre-designated key monitoring points on the bridge structure, such as the mid-span of the main girder, supports, pier tops, and known crack locations, three types of specialized monitoring equipment are physically deployed and fixed: a GNSS receiver (MAS-GNSS-SP-Z integrated monitoring receiver (dual-frequency professional type)) for capturing millimeter-level three-dimensional displacement, a crack gauge (MAS-JBLF20 integrated crack gauge) for measuring crack propagation width, and a vibration monitoring device (MAS-YTZD integrated vibration monitoring system) for sensing the structural dynamic response. These devices are calibrated and oriented according to engineering specifications during physical installation to ensure that their measurement axes are aligned with the main mechanical directions of the bridge structure. The data acquisition process relies on a unified system clock to synchronously issue acquisition commands to the three types of equipment, thereby ensuring that the obtained raw displacement sequence, crack width reading sequence, and triaxial acceleration sequence have a consistent time reference in each acquisition cycle. The raw data undergoes preliminary refinement: from the complex positioning information containing latitude, longitude, and elevation output from the GNSS receiver, the most characteristic quantity reflecting the vertical deformation of the bridge—the elevation coordinate value—is extracted to form displacement data; from the electrical signal output by the crack gauge, the corresponding physical width value is directly parsed to form crack data; for the triaxial acceleration collected by the vibration sensor, the acceleration component value of the corresponding axial direction is selected according to the first-order vibration mode direction of the bridge structure (usually vertical or horizontal), and vibration noise in irrelevant directions is filtered out, thereby forming vibration data reflecting the overall dynamic characteristics of the structure.

[0020] Step S2: Perform characteristic change calculations on the displacement data, crack data, and vibration data in sequence to obtain the displacement change rate, crack width change, and structural vibration offset. Specifically, for displacement data, the elevation coordinate sequence of continuous displacement data is processed within a pre-defined calculation time window. The elevation difference between each adjacent sampling point within this window is calculated to obtain a set of instantaneous changes, and then the arithmetic mean of these instantaneous changes is calculated. This average value is defined as the displacement change rate. For crack data, the characteristic change calculation focuses on the crack propagation trend. A three-point sliding median filter is applied to the continuous crack width reading sequence in the crack data, that is, each point and its preceding and following adjacent points are taken in sequence, and the median of the three is taken as the filtered value for that point. Subsequently, over a longer time interval, the starting and ending values ​​of the filtered sequence are taken, and the difference between the two is calculated. This difference is defined as the crack width change. For vibration data, the characteristic change calculation aims to capture changes in the structure's natural frequency. The continuous acceleration signal in the vibration data is segmented into fixed time intervals. Each segment is windowed (e.g., using a Hanning window) and then subjected to spectral analysis to convert the time-domain signal into a power spectrum in the frequency domain. From this spectrum, the frequency point with the highest energy concentration is precisely identified, i.e., the dominant frequency of the current time interval. The absolute difference between this dominant frequency and the reference frequency measured under healthy bridge conditions is calculated. This difference is defined as the structural vibration offset.

[0021] Step S3: Based on preset early warning conditions, perform state identification on the displacement change rate, the crack width change, and the structural vibration offset to obtain structural state information; Specifically, a set of early warning condition parameters is invoked, including independent judgment thresholds for displacement change rate, crack width change, and structural vibration offset. After the state recognition process is initiated, the real-time calculated displacement change rate is compared with the corresponding rate threshold. If the current rate exceeds the threshold, a specific numerical or symbolic identifier representing an abnormal displacement (first anomaly identifier) ​​is generated; if it does not exceed the threshold, a corresponding identifier representing normal displacement is generated. This is applied in parallel to the comparison of crack width change with the crack width change threshold, and structural vibration offset with the frequency offset threshold, generating second and third identifiers representing crack and vibration states, respectively. Thus, three judgment results are generated. An information integration operation is then performed. These three identifiers are treated as a combined whole and matched against a predefined state mapping table. This mapping table defines the higher-level structural state information uniquely corresponding to all possible identifier combinations (e.g., "normal, abnormal, normal"). This information is typically a status code or state description representing the overall health level (e.g., Level 1 early warning state, Level 2 attention state, normal state).

[0022] Step S4: Perform state analysis and early warning construction based on the structural state information to obtain an early warning report.

[0023] Specifically, based on the specific state level indicated by the structural status information, a search and matching process is performed in a pre-defined early warning rule knowledge base. This rule base defines the correspondence between state levels and early warning levels (such as yellow, orange, and red alerts), and also links to standardized report templates applicable to each early warning level, along with corresponding emergency response tips. Upon successful matching, the current early warning level is determined, and the corresponding report template is invoked. Simultaneously, the source information triggering the early warning—including specific displacement change rates, crack width changes, structural vibration offset values, the physical location identifiers of the monitoring equipment that generated this data, and the precise timestamps of data acquisition—is automatically packaged and merged with the early warning level and the response tips extracted from the rule base, generating standardized early warning records. These records are sorted in descending order of the severity of the early warning level to ensure that the most urgent situations are at the top of the report. Following the predetermined structure of the selected template, the sorted list of early warning records, relevant feature parameter details, time and location information, and response suggestions are automatically populated into the corresponding fields of the template, assembling to generate an early warning report document.

[0024] This invention provides a bridge monitoring method based on monitoring equipment. By simultaneously acquiring and fusing three types of heterogeneous monitoring data—displacement, cracks, and vibration—it overcomes the limitations of traditional single-monitoring methods and achieves a more comprehensive assessment of the bridge's structural health. Through real-time characteristic change calculations on multi-source monitoring data, key indicators such as displacement change rate, crack width change, and structural vibration offset are directly obtained. This transforms massive amounts of raw data into characteristic parameters that can be directly used for condition determination, significantly improving data processing efficiency and the timeliness of condition perception. By automating condition identification and hierarchical early warning construction based on preset warning conditions for the aforementioned characteristic parameters, manual experience-based judgment is transformed into standardized analytical logic, reducing the risk of missed and false alarms and providing structured early warning reports for maintenance decisions.

[0025] In one embodiment, acquiring displacement data, crack data, and vibration data collected by multiple monitoring devices deployed at the bridge structure location includes: The monitoring equipment synchronously collects the raw displacement sequence output by the GNSS receiver, the raw crack width data output by the crack gauge, and the raw triaxial vibration data output by the vibration sensor according to a preset time period. Among them, triaxial vibration raw data refers to the continuous signal of acceleration changing over time collected by the vibration sensor along the three mutually perpendicular axes of X, Y, and Z.

[0026] The elevation coordinate values ​​corresponding to each sampling time are extracted from the original displacement sequence to form the displacement data; Among them, the elevation direction coordinate value refers to the height component that is separated from the three-dimensional geocentric coordinates (or local engineering coordinates) output by the GNSS receiver and is perpendicular to the horizontal plane. This component directly reflects the vertical settlement or uplift deformation of the bridge.

[0027] The crack data is formed by extracting the measurement value corresponding to each sampling time from the raw crack width data; The vibration data is generated by selecting the corresponding axial acceleration component value from the triaxial vibration raw data based on the preset principal vibration direction of the bridge structure.

[0028] Among them, the preset main vibration direction refers to the spatial direction in which the structure has the largest vibration displacement under the main vibration mode (which can be the first-order vertical or transverse vibration mode) as determined in advance based on the dynamic characteristic analysis of the bridge structure (such as finite element modal analysis or on-site dynamic testing).

[0029] The method provided in this embodiment achieves multi-dimensional collaborative perception of bridge displacement, apparent damage, and dynamic response by simultaneously acquiring displacement sequences from GNSS receivers, width data from crack gauges, and triaxial acceleration data from vibration sensors, and aligning them according to a unified time reference. This overcomes the limitations of traditional single-monitoring methods that offer only a limited perspective. By extracting elevation coordinates, physical width, and acceleration components in the principal vibration direction from the raw data to form a standardized monitoring data sequence, the heterogeneous sensor outputs are transformed into analytical objects with clear structural mechanical significance, laying a data foundation for subsequent quantitative fusion analysis. By calculating the rate of change of displacement data, the net change after filtering of crack data, and the fundamental frequency shift of vibration data, continuous raw observation data are condensed into key characteristic parameters that can directly quantify the evolution trend of structural state, significantly improving the timeliness and relevance of state assessment.

[0030] In one embodiment, the step of sequentially calculating the characteristic changes of the displacement data, the crack data, and the vibration data to obtain the displacement change rate, the crack width change, and the structural vibration offset includes: The displacement rate is obtained by calculating the difference between adjacent points in the elevation coordinate sequence of the displacement data based on the first set time interval, and by averaging all the differences between adjacent points. The crack data is subjected to a three-point sliding median filter to obtain a width filter sequence. The difference between the first and last values ​​of the width filter sequence in a second set time interval is calculated to obtain the crack width change. Specifically, starting from the second data point of the crack data (since the first point has no preceding neighbor), the width values ​​of the current point, its preceding point, and its following point are sequentially taken to form a three-point set. The three values ​​in this three-point set are sorted, and the median value is determined. This median value is output as the new filtered value for the current point. This operation slides forward until the penultimate data point is processed (since the last point has no following neighbor). The first and last points of the sequence can be processed by copying neighboring points or directly retaining them. After this process, a width-filtered sequence is generated. Subsequently, to evaluate the crack development over a longer period, a second set time interval is determined, such as 24 hours or one week. Within this interval, the two filtered width values ​​in the width-filtered sequence corresponding to the start and end times of this interval are located. The algebraic difference between the end value and the start value is the crack width change. This change directly reflects the net increase or decrease in crack width within the evaluated second set time interval.

[0031] The vibration data is segmented into equal-length intervals and subjected to time-frequency transformation to obtain a segmented vibration spectrum. The highest frequency point in the segmented vibration spectrum is identified, and the absolute value of the difference between the highest frequency point and the preset reference frequency is calculated to obtain the structural vibration offset.

[0032] The method provided in this embodiment calculates the average difference between adjacent points based on displacement data within a first set time interval, thereby obtaining a smooth, instantaneous displacement change rate. This transforms continuous location information into a quantitative indicator of strength and direction that directly characterizes the structural deformation trend, improving the timeliness of settlement or uplift anomaly identification and the reliability of trend judgment. By applying a three-point sliding median filter to the crack data and calculating the difference between the first and last values ​​within a second set time interval, the method can extract the net change reflecting the true crack development trend while effectively suppressing outliers and instantaneous environmental interference, thus enhancing the robustness of crack monitoring data and the accuracy of long-term assessment.

[0033] In one embodiment, the step of segmenting the vibration data into equal-length intervals and performing time-frequency transformation to obtain the segmented vibration spectrum includes: The vibration data is divided into a continuous and non-overlapping data segment according to the equal-length intervals; For each of the data segments of the first type, a Hanning window sequence with the same length as the data segment of the first type is generated, and each data point in the data segment of the first type is multiplied by the window coefficient at the corresponding position in the Hanning window sequence to obtain the windowed data segment; Specifically, for each data segment of category I, a dedicated Hanning window sequence needs to be generated first. Based on the length of the data segment (e.g., 1024 points), 1024 window coefficients are calculated according to the mathematical definition of the Hanning window. These coefficients form a symmetrical sequence with small values ​​at both ends and a large value in the middle. Point-to-point multiplication is then performed. The first acceleration data point in the data segment is taken, and its value is multiplied by the first window coefficient in the Hanning window sequence. The product is used as the first new data point in the windowed data segment. Next, the second data point in the original data segment is taken and multiplied by the second window coefficient in the Hanning window sequence to obtain the second new data point. This operation is strictly performed in sequence until the last data point in the original data segment is multiplied by the last window coefficient in the Hanning window sequence. After this series of multiplication operations, the original data segment is transformed into a windowed data segment. The role of the Hanning window coefficient is to gradually attenuate the data amplitude at both ends of the data segment, so that the data segment smoothly approaches zero at the boundaries.

[0034] Perform a spectral transformation on each windowed data segment and calculate the square of the amplitude corresponding to each frequency point in each complex spectrum to obtain the power spectrum. Integrate all the power spectra to obtain the vibration segment spectrum.

[0035] Specifically, each windowed data segment is sequentially fed into the spectrum calculation unit. A spectrum transformation operation is performed on this data segment. This operation, based on the principle of the Discrete Fourier Transform, decomposes the time-varying acceleration sequence within the data segment into a representation of the sum of sine and cosine components at different frequencies, outputting a complex spectrum. This spectrum is a complex array whose length is typically related to the data segment length. The k-th complex number in the array corresponds to a specific frequency fk determined by the sampling rate. The real and imaginary parts of this complex number jointly encode the amplitude and phase information of the sine wave at frequency fk in the signal. Post-processing is then performed on this complex spectrum to extract energy information. Each element in the complex array is traversed, and for each complex number, the sum of the squares of its real and imaginary parts is calculated; this result represents the square of the complex number's amplitude. This calculation is repeated for all frequency points in the spectrum to obtain the power spectrum of the current data segment. This process is performed independently for each windowed data segment, generating a corresponding power spectrum for each segment. All power spectra generated in chronological order are arranged sequentially, indexed by the start time of their corresponding data segments. This arrangement forms a segmented vibration spectrum with time (or segment number) on the horizontal axis, frequency on the vertical axis, and power values ​​representing intensity.

[0036] The method provided in this embodiment divides continuous vibration data into continuous and non-overlapping data segments at equal intervals, thus providing processing units of uniform length and regular timing for subsequent spectral analysis. This allows the observation of vibration characteristics to be based on stable and comparable time windows, which is beneficial for capturing the short-time characteristics and evolution of structural dynamic response. By applying a length-matched Hanning window function to each data segment and performing point-to-point weighted multiplication, the two ends of the data segment are smoothly attenuated to zero before spectral transformation, effectively suppressing the spectral energy leakage phenomenon caused by data truncation. This results in more concentrated and accurate frequency components calculated subsequently, improving the accuracy and reliability of dominant frequency identification.

[0037] In one embodiment, the step of identifying the structural state information based on preset early warning conditions regarding the displacement change rate, the crack width change, and the structural vibration offset to obtain structural state information includes: When the displacement change rate is higher than the rate threshold of the preset warning condition, a first abnormality flag is generated; otherwise, the displacement change rate is marked as normal. When the change in crack width exceeds the width change threshold of the preset early warning condition, a second abnormality flag is generated; otherwise, the change in crack width is marked as normal. When the structural vibration offset is greater than the frequency offset threshold of the preset early warning condition, a third abnormality identifier is generated; otherwise, the structural vibration offset is marked as normal. Based on the mapping conditions of the preset early warning conditions, the first abnormal identifier, the second abnormal identifier, and the third abnormal identifier are integrated into the structural status information.

[0038] Specifically, the system calls and loads the mapping conditions defined in the preset warning conditions. These conditions are represented by a status mapping lookup table or a set of logical judgment rules. For example, a simple mapping table might define: when all three identifiers are normal, the mapping is to structural status information: Level 1 (Safe); when only the first abnormal identifier appears, the mapping is to structural status information: Level 2 (Attention); when the first and third abnormal identifiers appear simultaneously, the mapping is to structural status information: Level 3 (Warning); when all three identifiers appear, the mapping is to structural status information: Level 4 (Severe Warning). The integration process involves using a specific combination of the three currently obtained identifiers as the query key and performing a precise match in the aforementioned mapping table or rules. Upon successful matching, the system extracts and outputs the structural status information uniquely corresponding to that combination.

[0039] The method provided in this embodiment, by comparing the displacement change rate with a preset rate threshold in real time and generating a first anomaly identifier when the limit is exceeded, can timely and automatically capture the accelerated deformation trend of the bridge exceeding the normal range. This effectively separates slowly developing settlement or sudden displacement problems from background noise, improving the sensitivity and response speed of deformation anomaly identification. By comparing the crack width change with a preset width change threshold and generating a second anomaly identifier, it can reliably distinguish between normal expansion and contraction reflecting material temperature effects and abnormal expansion characterizing structural damage. This improves the objectivity and accuracy of qualitative judgment of bridge apparent damage and reduces reliance on human experience. By integrating the three identifiers representing displacement, cracks, and vibration states into unified structural state information according to preset mapping conditions, it can fuse scattered anomaly signals from different monitoring dimensions into a comprehensive safety level conclusion, thereby overcoming the one-sidedness of single-indicator judgment.

[0040] In one embodiment, the step of performing state analysis and early warning construction based on the structural state information to obtain an early warning report includes: The structural status information is matched with a preset early warning rule base to determine the early warning level. The warning levels adopt a tiered system, such as L0 (normal monitoring), L1 (yellow warning), L2 (orange warning), and L3 (red warning), with each level corresponding to different response procedures and information notification scope.

[0041] If the structural status information is completely consistent with any combination of identifiers in the preset early warning rule base, the early warning level of the identifier combination is marked as the current early warning level of the structural status information; Specifically, each record in the preset early warning rule base is checked one by one. For each record, the stored identifier combination is strictly compared with the currently input, actual structural state information using strings or codes. The comparison process checks whether the lengths of the two are the same and whether each corresponding character or number is equal. Only when all conditions are met is it considered a complete match. Once a record in the rule base is found to have an identifier combination that meets the condition of "completely matching" the current structural state information, that record is considered a valid match. From this successfully matched record, the value of its predefined early warning level field is read. This value is extracted and assigned to the current early warning level representing the result of this analysis cycle. If no completely matching record is found after traversing the entire rule base, it means that the current structural state is not covered by the predefined rules. In this case, an exception handling process can be triggered, such as assigning a default unknown level or triggering a manual review notification.

[0042] Based on the displacement change rate, crack width change, and structural vibration fundamental frequency offset corresponding to the current warning level, a warning record is obtained; Based on the current warning level, the corresponding warning report template is extracted from the preset warning rule base; According to the current warning level, all the warning records are sequentially filled into the warning report template to obtain the warning report.

[0043] The method provided in this embodiment compares the displacement change rate, crack width change, and structural vibration offset with independent thresholds in preset early warning conditions and generates corresponding abnormal or normal indicators. This enables parallel and independent precise capture and labeling of abnormalities in three dimensions: bridge deformation, apparent damage, and internal dynamic characteristics. This decomposes the complex structural condition monitoring task into multiple objectively identifiable sub-problems, improving the granularity and clarity of condition perception. By integrating the three independent indicators representing displacement, cracks, and vibration states into unified structural condition information based on mapping conditions in preset early warning conditions, it can comprehensively interpret and fuse potentially independent abnormal signals from different physical sources according to predefined safety logic. This overcomes the possibility of misjudgment or omission that may occur with a single monitoring indicator, achieving a more comprehensive and consistent qualitative assessment of the overall safety status of the bridge.

[0044] In one embodiment, an early warning record is obtained based on the displacement change rate, crack width change, and structural vibration fundamental frequency offset corresponding to the current early warning level, including: Obtain the monitoring location identifier corresponding to the monitoring device that triggered the current warning level, and obtain the acquisition timestamps of the displacement data, the crack data, and the vibration data; Based on the current warning level, the corresponding handling prompt information is extracted from the preset warning rule base; The warning record is generated by combining the current warning level, the displacement change rate, the crack width change, the structural vibration fundamental frequency offset, the monitoring location identifier, the acquisition timestamp, and the handling prompt information according to a predetermined recording format.

[0045] Specifically, according to the record format requirements, each data item undergoes necessary formatting conversions: numerical data is converted into strings with specified precision and decimal places; timestamps are converted into a unified date and time string format; and reserved characters in text data are correctly escaped. Following the field order defined in the format, the formatted current warning level string is placed first, followed by the monitoring location identifier string, the formatted acquisition timestamp string, the displacement change rate string, the crack width change string, the structural vibration fundamental frequency offset string, and finally the handling prompt information text string. Specified delimiters are inserted between each field according to the format requirements. Once all field values ​​are concatenated in sequence, a standardized, structured data string or data object is generated, which is the final warning record.

[0046] The method provided in this embodiment, by comparing displacement change rate, crack width change, and structural vibration offset with preset independent thresholds in parallel and generating corresponding abnormal or normal indicators, enables independent and precise real-time monitoring and status marking of three core parameters reflecting structural geometric deformation, apparent damage, and dynamic characteristics. This overcomes the one-sidedness of relying on a single indicator for judgment and achieves multi-dimensional and three-dimensional synchronous perception of the bridge's safety status. By integrating the three independent indicators representing displacement, crack, and vibration status into a unified structural status information based on preset mapping conditions, it can correlate and fuse abnormal signals from different physical sources that may have different time-varying characteristics according to a predetermined safety logic. This elevates scattered local status judgments into a comprehensive conclusion characterizing the overall risk level of the structure, providing a clear and consistent input basis for subsequent decision-making.

[0047] Reference Figure 2 As shown, the present invention also provides a bridge monitoring device based on monitoring equipment, applied to any of the bridge monitoring methods based on monitoring equipment described above, comprising: The acquisition module is used to acquire displacement data, crack data, and vibration data collected by multiple monitoring devices deployed on the bridge structure. The analysis module is used to perform characteristic change calculations on the displacement data, crack data and vibration data in sequence to obtain the displacement change rate, crack width change and structural vibration offset. The association module is used to identify the state of the displacement change rate, the crack width change and the structural vibration offset based on preset early warning conditions, so as to obtain structural state information. The processing module is used to perform state analysis and early warning construction based on the structural state information, and to obtain an early warning report.

[0048] This invention provides a bridge monitoring device based on monitoring equipment. By simultaneously acquiring three types of heterogeneous monitoring data—displacement, cracks, and vibration—and fusing and analyzing them, it overcomes the limitations of traditional single-monitoring methods and achieves a more comprehensive assessment of the bridge's structural health. Through real-time characteristic change calculations on multi-source monitoring data, key indicators such as displacement change rate, crack width change, and structural vibration offset are directly obtained. This transforms massive amounts of raw data into characteristic parameters that can be directly used for condition determination, significantly improving data processing efficiency and the timeliness of condition perception. By automating condition identification and hierarchical early warning construction based on preset warning conditions for the aforementioned characteristic parameters, manual experience-based judgment is transformed into standardized analytical logic, reducing the risk of missed and false alarms and providing structured early warning reports for maintenance decisions.

[0049] Reference Figure 3 As shown, the present invention also provides a bridge monitoring system based on monitoring equipment, characterized in that it includes: Memory, used to store programs; A processor is configured to execute the program to implement the steps of a bridge monitoring method based on a monitoring device as described in any of the preceding claims.

[0050] In this embodiment, the processor and memory can be connected via a bus or other means. The memory may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as read-only memory, flash memory, hard disk, or solid-state drive. The processor may be a general-purpose processor, such as a central processing unit, digital signal processor, application-specific integrated circuit, or one or more integrated circuits configured to implement embodiments of the present invention.

[0051] The present invention also provides a storage medium storing computer instructions for causing a computer to perform any of the methods described above.

[0052] It should be noted that those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the system and each module described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0053] The above description is only a preferred embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A bridge monitoring method based on monitoring equipment, characterized in that, include: Acquire displacement, crack, and vibration data collected by multiple monitoring devices deployed on the bridge structure; The displacement data, crack data, and vibration data are sequentially subjected to characteristic change calculations to obtain the displacement change rate, crack width change, and structural vibration offset. Based on preset early warning conditions, the displacement change rate, the crack width change, and the structural vibration offset are identified to obtain structural state information. Based on the structural state information, state analysis and early warning construction are performed to obtain an early warning report.

2. The bridge monitoring method based on monitoring equipment according to claim 1, characterized in that, The acquisition of displacement data, crack data, and vibration data collected by multiple monitoring devices deployed at the bridge structure locations includes: The monitoring equipment synchronously collects the raw displacement sequence output by the GNSS receiver, the raw crack width data output by the crack gauge, and the raw triaxial vibration data output by the vibration sensor according to a preset time period. The elevation coordinate values ​​corresponding to each sampling time are extracted from the original displacement sequence to form the displacement data; The crack data is formed by extracting the measurement value corresponding to each sampling time from the raw crack width data; The vibration data is generated by selecting the corresponding axial acceleration component value from the triaxial vibration raw data based on the preset principal vibration direction of the bridge structure.

3. The bridge monitoring method based on monitoring equipment according to claim 1, characterized in that, The step of sequentially performing characteristic change calculations on the displacement data, crack data, and vibration data to obtain the displacement change rate, crack width change, and structural vibration offset includes: The displacement rate is obtained by calculating the difference between adjacent points in the elevation coordinate sequence of the displacement data based on the first set time interval, and by averaging all the differences between adjacent points. The crack data is subjected to a three-point sliding median filter to obtain a width filter sequence. The difference between the first and last values ​​of the width filter sequence in a second set time interval is calculated to obtain the crack width change. The vibration data is segmented into equal-length intervals and subjected to time-frequency transformation to obtain a segmented vibration spectrum. The highest frequency point in the segmented vibration spectrum is identified, and the absolute value of the difference between the highest frequency point and the preset reference frequency is calculated to obtain the structural vibration offset.

4. The bridge monitoring method based on monitoring equipment according to claim 3, characterized in that, The step of segmenting the vibration data into equal-length intervals and performing time-frequency transformation to obtain the segmented vibration spectrum includes: The vibration data is divided into a continuous and non-overlapping data segment according to the equal-length intervals; For each of the data segments of the first type, a Hanning window sequence with the same length as the data segment of the first type is generated, and each data point in the data segment of the first type is multiplied by the window coefficient at the corresponding position in the Hanning window sequence to obtain the windowed data segment; Perform a spectral transformation on each windowed data segment and calculate the square of the amplitude corresponding to each frequency point in each complex spectrum to obtain the power spectrum. Integrate all the power spectra to obtain the vibration segment spectrum.

5. The bridge monitoring method based on monitoring equipment according to claim 1, characterized in that, The structural state information is obtained by identifying the displacement change rate, the crack width change, and the structural vibration offset based on preset early warning conditions, including: When the displacement change rate is higher than the rate threshold of the preset warning condition, a first abnormality flag is generated; otherwise, the displacement change rate is marked as normal. When the change in crack width exceeds the width change threshold of the preset early warning condition, a second abnormality flag is generated; otherwise, the change in crack width is marked as normal. When the structural vibration offset is greater than the frequency offset threshold of the preset early warning condition, a third abnormality identifier is generated; otherwise, the structural vibration offset is marked as normal. Based on the mapping conditions of the preset early warning conditions, the first abnormal identifier, the second abnormal identifier, and the third abnormal identifier are integrated into the structural status information.

6. The bridge monitoring method based on monitoring equipment according to claim 1, characterized in that, The step of performing state analysis and early warning construction based on the structural state information to obtain an early warning report includes: The structural status information is matched with a preset early warning rule base to determine the early warning level. If the structural status information is completely consistent with any combination of identifiers in the preset early warning rule base, the early warning level of the identifier combination is marked as the current early warning level of the structural status information; Based on the displacement change rate, crack width change, and structural vibration fundamental frequency offset corresponding to the current warning level, a warning record is obtained; Based on the current warning level, the corresponding warning report template is extracted from the preset warning rule base; According to the current warning level, all the warning records are sequentially filled into the warning report template to obtain the warning report.

7. The bridge monitoring method based on monitoring equipment according to claim 6, characterized in that, Based on the displacement change rate, crack width change, and structural vibration fundamental frequency offset corresponding to the current warning level, a warning record is obtained, including: Obtain the monitoring location identifier corresponding to the monitoring device that triggered the current warning level, and obtain the acquisition timestamps of the displacement data, the crack data, and the vibration data; Based on the current warning level, the corresponding handling prompt information is extracted from the preset warning rule base; The warning record is generated by combining the current warning level, the displacement change rate, the crack width change, the structural vibration fundamental frequency offset, the monitoring location identifier, the acquisition timestamp, and the handling prompt information according to a predetermined recording format.

8. A bridge monitoring device based on monitoring equipment, characterized in that, The bridge monitoring method based on monitoring equipment according to any one of claims 1-7 includes: The acquisition module is used to acquire displacement data, crack data, and vibration data collected by multiple monitoring devices deployed on the bridge structure. The analysis module is used to perform characteristic change calculations on the displacement data, crack data and vibration data in sequence to obtain the displacement change rate, crack width change and structural vibration offset. The association module is used to identify the state of the displacement change rate, the crack width change and the structural vibration offset based on preset early warning conditions, so as to obtain structural state information. The processing module is used to perform state analysis and early warning construction based on the structural state information, and to obtain an early warning report.

9. A bridge monitoring system based on monitoring equipment, characterized in that, include: Memory, used to store programs; A processor is configured to execute the program to implement the various steps of a bridge monitoring method based on a monitoring device as described in any one of claims 1-7.

10. A storage medium, characterized in that, The computer contains computer instructions for causing the computer to perform the method according to any one of claims 1 to 7.

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