A system and method for real-time sensing and hierarchical alarm triggering of pavement collapse

Abstract

This invention provides a real-time perception and graded alarm triggering system and method for road subsidence, belonging to the field of road safety monitoring technology. It includes multiple data collectors, at least one area controller, a data platform, and an alarm module. The multiple data collectors are installed at equal intervals along the road's extension direction on highway crash barriers. Each data collector includes a main control unit, an inertial measurement unit, a first communication unit, and a power supply unit. By installing multiple data collectors at equal intervals on the crash barriers and utilizing the area controller to perform time and location correlation analysis on each data collection point, this invention can effectively distinguish between vehicle traffic vibrations moving along the road and continuous abnormal vibrations in fixed sections from multi-point combined spatiotemporal vibration patterns. This eliminates vehicle interference data at the source, significantly reducing the false alarm rate and making subsidence risk perception truly practical for on-site engineering.

Description

Technical Field

[0001] This invention relates to the field of road safety monitoring technology, specifically to a real-time perception and graded alarm triggering system and method for road surface collapse. Background Technology

[0002] During long-term use, highways are affected by factors such as repeated vehicle loads, rainwater erosion, groundwater erosion, underground pipeline leakage, internal cavities in the roadbed, insufficient compaction of fill layers, underground engineering construction, and geological changes, which may lead to problems such as roadbed settlement, pavement voids, local cracking, and pavement collapse.

[0003] Road surface subsidence typically involves a development process. In some cases, cavities or loose areas first form within the roadbed, which then expand under the influence of vehicle loads and environmental factors, eventually causing the road surface to suddenly sink or collapse. If changes in road conditions are not detected and alerts are not issued in time, it can easily lead to vehicle damage, traffic congestion, and in severe cases, even injuries or fatalities.

[0004] Existing methods for detecting road subsidence mainly include manual inspections, regular inspections by road inspection vehicles, video surveillance, and the installation of sensors inside the road surface.

[0005] Manual inspections and road inspection vehicles are typically conducted on a predetermined schedule, making it difficult to continuously monitor road conditions and potentially failing to detect potential collapses between inspections. Video surveillance is susceptible to factors such as nighttime lighting, rain, snow, fog, obstructions, and monitoring angles, and it struggles to detect internal road surface cavities and structural changes preceding collapses. Installing sensors within the road surface requires excavation of existing road surfaces, making installation and maintenance challenging.

[0006] Using accelerometers to detect road vibrations can reduce road excavation and construction. However, vibration sources in highway environments are complex. Significant vibrations can be generated by large trucks, ordinary cars, continuous traffic flow, vehicles passing through road joints, and vehicles colliding with or impacting highway guardrails. Judging solely based on the vibration amplitude detected by a single sensor can easily lead to misinterpreting normal vibrations from passing vehicles as road anomalies, resulting in false alarms.

[0007] Furthermore, a single detection point can only reflect vibration changes at a local location, making it difficult to determine the extent of the anomaly's impact or whether it is spreading along the road. Existing monitoring devices also suffer from a lack of coordination between multiple detection points, a single alarm level, and an inability to take different measures based on the severity of the anomaly.

[0008] Therefore, there is a need for a system and method that can be directly installed on highway crash barriers, continuously collect road vibration data, identify vehicle traffic interference, make joint judgments on multiple detection points, and trigger different levels of alarms based on the degree of road collapse risk. Summary of the Invention

[0009] To address the aforementioned technical problems, this invention provides a real-time perception and graded alarm triggering system and method for road collapse. This system can effectively distinguish between vehicle traffic vibrations moving along the road and continuous abnormal vibrations in fixed sections from multi-point combined spatiotemporal vibration patterns, thereby eliminating vehicle interference data at the source and reducing false alarm rates.

[0010] The technical solution adopted in this invention is as follows: A real-time sensing and graded alarm triggering system for road collapse includes multiple data collectors, at least one area controller, a data platform, and an alarm module. Multiple data acquisition units are installed at equal intervals along the road extension direction on the highway crash barrier. Each data acquisition unit includes a main control unit, an inertial measurement unit, a first communication unit, and a power supply unit. The inertial measurement unit includes one or more inertial measurement components, and each inertial measurement component includes a triaxial accelerometer and a triaxial angular velocity meter. The data acquisition device is used to acquire triaxial acceleration data and triaxial angular velocity data at the corresponding installation position according to a preset sampling frequency, and to obtain at least one of vibration frequency, vibration amplitude, spectrum data, dynamic acceleration, vibration-induced torque, and abnormal vibration characteristics based on the triaxial acceleration data and the triaxial angular velocity data. The data collector is also used to compare the abnormal vibration characteristics with the pre-stored vehicle traffic vibration characteristics and vehicle impact vibration characteristics, identify the vehicle traffic interference data and vehicle impact interference data in the collected data, and remove or correct the identified interference data to obtain the target monitoring data. The area controller is used to receive target monitoring data and abnormal vibration characteristics sent by multiple collectors through the first communication unit, perform single-point anomaly analysis on the data sent by a single collector, and perform time correlation analysis and location correlation analysis based on the installation location, anomaly occurrence time and abnormal vibration characteristics of multiple collectors to obtain the area anomaly result; The area controller is also used to determine the road collapse risk level based on the single-point anomaly analysis results, the area anomaly results, and the preset collapse judgment rules, and to control the alarm module to execute an alarm action corresponding to the road collapse risk level. The data platform is used to receive the collected data, analysis results, and alarm events sent by the area controller, store the collected data, analysis results, and alarm events, and obtain the status change information of the road to be monitored based on historical data arranged according to the collection time.

[0011] Furthermore, the number of the inertial measurement units is one to four; When there are two or more inertial measurement units, the data acquisition unit compares the data obtained by each inertial measurement unit at the same acquisition time, determines the vibration changes detected by two or more inertial measurement units as valid vibration data, and marks the vibration changes detected by only one inertial measurement unit as data to be checked.

[0012] Furthermore, the vehicle traffic interference data and vehicle impact interference data are identified, including: Extract at least one of the following from the collected data: vibration amplitude, frequency component, vibration intensity in different frequency ranges, vibration duration, rate of change of acceleration, rate of change of angular velocity, and data variation relationship in different measurement directions; The extracted data is compared with pre-stored vehicle traffic vibration characteristics and vehicle impact vibration characteristics; When the comparison result meets the vehicle traffic vibration characteristics or vehicle impact vibration characteristics, the collected data for the corresponding time period is marked as interference data. The vehicle traffic vibration characteristics include vibrations that pass through multiple data collectors sequentially along the vehicle's travel direction and weaken or disappear after the vehicle leaves; the vehicle impact vibration characteristics include vibration peaks that rapidly increase and then decrease within a preset time period.

[0013] Furthermore, the first communication unit communicates with the area controller using at least one of LoRa, Wi-Fi, StarFlash, or Bluetooth. The area controller sends collected data, analysis results, alarm events, and device operating status to the data platform via at least one of a fourth-generation mobile communication network and a wired network.

[0014] Furthermore, the installation distance between adjacent collectors is equal, and the area controller is used to receive data sent by one to 1,500 collectors, and to save the device number, installation location, installation order and adjacency relationship of each collector.

[0015] Furthermore, the time correlation analysis and location correlation analysis include: Obtain the start time, duration, installation location, and installation sequence of each data acquisition device exhibiting abnormal vibration characteristics; Determine whether multiple data collectors malfunction within a preset time period, whether the malfunctioning data collectors are adjacent or consecutively distributed, and whether the malfunction spreads from the installation location of one data collector to the installation locations of adjacent data collectors. The abnormal results in the region are determined based on the number of abnormal data collectors, the distance between adjacent abnormal data collectors, the intensity of abnormal vibration, and the duration of abnormality.

[0016] Furthermore, the collapse determination rules include at least one of the following: single-point abnormal amplitude, abnormal duration, spectrum data change, abnormal change rate, number of collectors with abnormalities, abnormal coverage area, abnormal intensity after interference data processing, and historical data change trend. The road surface collapse risk levels include suspected abnormality level, continuous abnormality level, multi-point abnormality level, and high-risk collapse level.

[0017] Furthermore, the suspected anomaly level corresponds to recording abnormal events and sending inspection prompts; The continuous anomaly level corresponds to sending alarm information to road maintenance personnel and increasing the sampling frequency of the anomaly collector and its adjacent collectors; The aforementioned multi-point anomaly levels correspond to sending alarm information to road management personnel and triggering on-site audible and visual alarms; The high-risk collapse level corresponds to sending an emergency alarm message and outputting at least one of the following disposal instructions: speed limit, traffic control, risk section isolation, and risk section closure.

[0018] This invention also proposes a method for real-time sensing and graded alarm triggering of road collapse, comprising the following steps: Multiple data collectors are installed at equal intervals along the road extension direction on the highway crash barrier to collect triaxial acceleration data and triaxial angular velocity data at each installation location according to a preset sampling frequency. Based on the triaxial acceleration data and the triaxial angular velocity data, at least one of the following is obtained: vibration frequency, vibration amplitude, spectrum data, dynamic acceleration, torque caused by vibration, and abnormal vibration characteristics. The abnormal vibration characteristics are compared with the pre-stored vehicle traffic vibration characteristics and vehicle impact vibration characteristics. The vehicle traffic interference data and vehicle impact interference data in the collected data are identified, and the identified interference data are removed or corrected to obtain the target monitoring data. Single-point anomaly analysis is performed on the target monitoring data of a single data acquisition device, and time correlation analysis and location correlation analysis are performed based on the installation location, anomaly occurrence time and abnormal vibration characteristics of multiple data acquisition devices to obtain regional anomaly results; The road surface collapse risk level is determined based on the results of single-point anomaly analysis, regional anomaly results, and preset collapse judgment rules. Execute the corresponding alarm action according to the road collapse risk level; The collected data, analysis results, and alarm events are sent to the data platform for storage, and the status change information of the monitored road is obtained based on historical data arranged according to the collection time.

[0019] Furthermore, the road surface collapse risk level is determined based on the single-point anomaly analysis results, the regional anomaly results, and the preset collapse judgment rules, including: Acquire target monitoring data from the corresponding data collector within a preset historical time period; The normal vibration range for the corresponding installation location is determined based on the target monitoring data; Determine the degree of change in the current target monitoring data relative to the normal vibration range; The road collapse risk level is determined based on the degree of change, duration of the anomaly, number of data collectors exhibiting anomalies, coverage area of ​​the anomaly, and historical data trends.

[0020] The beneficial effects of this invention are: This invention, by installing multiple data collectors equidistantly on the crash barrier and using a regional controller to perform time and location correlation analysis on each data collection point, can effectively distinguish between vehicle traffic vibrations moving along the road and abnormal vibrations that persist in fixed sections from the spatiotemporal vibration patterns of multiple points. This eliminates vehicle interference data at the source, thereby significantly reducing the false alarm rate and making the collapse risk perception truly practical for on-site engineering. Attached Figure Description

[0021] Figure 1 This is a flowchart of the real-time sensing and graded alarm triggering method for road collapse of the present invention; Figure 2 This is a general framework diagram of the real-time perception and graded alarm triggering system for road collapse of the present invention; Figure 3 This is a framework diagram of the data collector and area controller of the present invention. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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 skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] Example 1 like Figures 1-3As shown in the figure, this embodiment provides a system for monitoring highway pavement collapse, including multiple data collectors, a regional controller, a data platform, and an alarm module.

[0024] Multiple data collectors are installed at equal intervals along the road's extension on the highway guardrail. In this embodiment, the installation distance between two adjacent data collectors is 20 meters.

[0025] Within the same monitoring section, all data acquisition devices are installed using the same or similar methods, with consistent installation height and measurement direction. The data acquisition devices maintain a stable connection to the highway crash barrier, ensuring that vibrations generated by the road and surrounding structures are transmitted to the inertial measurement unit within the data acquisition device.

[0026] Each data collector has a unique device number. The area controller stores the device number, installation location, road mileage location, installation sequence, adjacent data collector numbers, and distance between adjacent data collectors for each data collector.

[0027] The first measurement direction of the data collector is set along the road extension direction, the second measurement direction is set along the road width direction, and the third measurement direction is set vertically.

[0028] Each data acquisition unit includes a main control unit, an inertial measurement unit, a first communication unit, and a power supply unit.

[0029] The main control unit uses a microcontroller and runs a real-time operating system. The main control unit is equipped with a data acquisition program, a data processing program, an interference identification program, and a data transmission program.

[0030] The inertial measurement unit (IMU) comprises two IMU components, each including a triaxial accelerometer and a triaxial angular velocity meter. The two IMU components are housed inside the data logger and maintain the same measurement orientation.

[0031] The main control unit compares the data acquired by the two inertial measurement units at the same acquisition time. When both inertial measurement units detect the same or similar vibration changes, the vibration change is determined as valid vibration data.

[0032] When only one inertial measurement unit shows a significant change, while the other inertial measurement unit does not show a corresponding change, the corresponding data is marked as data to be checked, and a device check mark is added to the data sent to the area controller.

[0033] The first communication unit uses LoRa communication. The power supply unit includes a battery, a solar panel, and a charge / discharge control circuit. The solar panel charges the battery, which in turn supplies power to the main control unit, the inertial measurement unit, and the first communication unit.

[0034] In other embodiments, the first communication unit may also use Wi-Fi, Starflash, or Bluetooth communication methods.

[0035] The data acquisition unit collects triaxial acceleration data and triaxial angular velocity data according to a preset sampling frequency.

[0036] The main control unit performs zero-point correction, removal of obvious error values, and filtering on the collected data, and obtains vibration amplitude, vibration frequency, spectrum data, dynamic acceleration, rate of change of angular velocity, and time of occurrence of abnormal vibration.

[0037] When the processed data is within the normal vibration range of the corresponding installation location, the data acquisition unit sends the processing results to the area controller according to the normal communication cycle.

[0038] When the processed data exceeds the normal vibration range, the data acquisition unit shortens the data transmission cycle and sends the data before, during, and after the anomaly to the area controller.

[0039] The area controller receives data from multiple data collectors and determines the installation location and sequence corresponding to the data based on the device number.

[0040] The area controller first performs single-point anomaly analysis on the data from a single data acquisition unit to determine whether the current data exceeds the normal vibration range of the corresponding installation location, whether the anomaly lasts for more than a preset time, and whether the acceleration and angular velocity data are abnormal at the same time.

[0041] When a data collector malfunctions, the area controller retrieves data from that data collector and its adjacent data collectors before and after it, and compares the time of occurrence of the malfunction, the duration of the malfunction, the intensity of the malfunction vibration, and the positional relationship of the data collectors.

[0042] The area controller determines, based on the comparison results, whether the anomaly is caused by moving vibrations due to vehicle traffic or by continuous abnormal vibrations occurring in a fixed road section.

[0043] The area controller transmits collected data, target monitoring data, analysis results, alarm events, and equipment operating status to the data platform via the fourth-generation mobile communication network.

[0044] The data platform stores data according to the collector device number, installation location, and collection time, and displays the working status, monitoring data, and road collapse risk level of each collector through the display interface.

[0045] When the area controller determines that there is a risk of road collapse, the control alarm module executes the corresponding alarm action.

[0046] This embodiment forms a continuous monitoring section along the road by installing multiple data collectors at equal intervals on the highway crash barrier. This eliminates the need to excavate the road surface and allows for multi-point data comparison based on the defined positional relationships of each data collector.

[0047] Example 2 like Figures 1-3 As shown, this embodiment, based on the system of Embodiment 1, explains the identification and processing of vehicle traffic interference and vehicle impact interference, as well as the judgment of single-point anomalies.

[0048] When a vehicle passes through the section of road to be monitored, the vibrations generated by the road are transmitted to the highway crash barrier and detected by multiple data collectors installed on the highway crash barrier.

[0049] The data collector acquires triaxial acceleration and triaxial angular velocity data before, during, and after the vehicle passes by.

[0050] The area controller determines the order in which vibrations pass through each data collector based on the installation location and data collection time of the multiple data collectors.

[0051] When vibrations pass through multiple data collectors sequentially in the direction of vehicle travel, and the time interval between vibrations detected by adjacent data collectors corresponds to the movement of the vehicle, and the corresponding vibrations weaken or disappear after the vehicle leaves, the group of vibrations is identified as vehicle traffic vibrations.

[0052] The data acquisition unit or area controller extracts the following data from the data collected during vehicle passage: vibration amplitude, main frequency components, vibration intensity in different frequency ranges, vibration duration, rate of change of acceleration, rate of change of angular velocity, data variation relationship in different measurement directions, and time interval between vibrations detected by adjacent data acquisition units.

[0053] The above data is compared with pre-stored vehicle traffic vibration characteristics.

[0054] When the current vibration passes through multiple data collectors sequentially along the vehicle's direction of travel, the duration of the vibration is within the time range corresponding to the vehicle's passage, and the vibration disappears after the vehicle leaves, the data for the corresponding time period is marked as vehicle passage interference data.

[0055] For large trucks, the vibration amplitude and duration are usually greater than those of ordinary cars. The system does not judge road collapse based solely on vibration amplitude, but also considers the vibration direction, the response sequence of adjacent data collectors, and the vibration state after the vehicle leaves.

[0056] When a vehicle passes over a road joint, a road bump, or experiences a momentary collision, the data collector may detect significant instantaneous vibrations.

[0057] The area controller extracts vibration peak value, peak rise time, peak fall time, vibration duration, and vibration intensity changes between different data acquisition devices.

[0058] When the vibration peak value increases rapidly in a short period of time and then decreases, the vibration duration is short, and the corresponding vibration does not continue after the impact ends, the corresponding data is marked as vehicle impact interference data.

[0059] If a vehicle impact occurs near a data acquisition unit, the data acquisition unit closer to the impact location will detect stronger vibrations, while the vibrations detected by data acquisition units farther away from the impact location will gradually decrease. The area controller can use this relationship to help identify vehicle impact interference.

[0060] For identified vehicle traffic interference data and vehicle impact interference data, one of the following methods can be used for processing: Remove from the data used for road surface collapse assessment; The original data will be retained, but it will not be used as a direct basis for road collapse alarms. The interference period was corrected based on data before and after the interference occurred; Reduce the role of this data in assessing road collapse risk.

[0061] The target monitoring data is obtained after the above processing.

[0062] The area controller acquires the target monitoring data corresponding to each data collector and compares it with the normal vibration range of the corresponding installation location of the data collector.

[0063] When the target monitoring data meets one or more of the following conditions, it is determined that the data acquisition device has a single-point anomaly: the vibration amplitude continuously exceeds the normal vibration range, the duration of the anomaly exceeds the preset time, the anomaly still exists after the vehicle leaves, the spectrum data continues to change relative to historical normal data, the three-axis acceleration data and the three-axis angular velocity data both show anomalies, and the degree of change of the current target monitoring data relative to the normal vibration range continues to increase.

[0064] When only one data collector exhibits a minor anomaly and the anomaly lasts for a short period, the corresponding anomaly is identified as a suspected anomaly, and data acquisition continues from that data collector and its adjacent data collectors.

[0065] When the same data collector shows an anomaly in multiple consecutive monitoring periods, or when the anomaly persists after the vehicle leaves, the corresponding anomaly will be identified as a persistent anomaly.

[0066] This embodiment identifies vehicle traffic interference by analyzing the movement sequence, duration, and changes in the vehicle's state after it leaves, avoiding judgment based solely on vibration amplitude and thus reducing false alarms caused by the passage of large trucks and ordinary cars.

[0067] Example 3 This embodiment, based on Embodiment 1 and Embodiment 2, explains the joint judgment of multiple data collectors, the determination of risk levels, and the long-term analysis of the data platform.

[0068] On the highway section to be monitored, multiple data collectors are installed at equal intervals along the road's extension direction on the highway crash barrier, with an installation distance of 20 meters between adjacent data collectors.

[0069] The area controller receives target monitoring data and single-point anomaly analysis results sent by each data collector within a preset time period.

[0070] When any data collector experiences a single point of failure, the area controller uses that data collector as the center to obtain data from the adjacent data collectors before and after it.

[0071] For example, when the tenth data collector in the installation sequence malfunctions, the area controller obtains data from the eighth to twelfth data collectors for comparison.

[0072] The area controller determines whether multiple data collectors have malfunctioned within the same preset time period based on the collection time in the data sent by each data collector.

[0073] Time-related analysis includes one or more of the following: Determine if the start times of multiple anomalies are close; Determine if the durations of multiple anomalies overlap; Determine if adjacent data collectors experience sequential anomalies; Determine whether the anomalies of multiple data collectors persist; Determine whether the time of the anomaly coincides with the time the vehicle travels.

[0074] If multiple data collectors show short-term vibrations sequentially in the direction of vehicle travel, and the vibrations disappear after the vehicle leaves, then this set of data will be treated as vehicle traffic interference data.

[0075] If multiple adjacent data collectors exhibit anomalies within a short period of time, and the anomalies persist even after the vehicle leaves, location correlation analysis is performed on the corresponding data.

[0076] The area controller determines whether the abnormal collectors are distributed continuously based on the installation order and location of each collector.

[0077] Location association analysis includes one or more of the following: Are the collectors that malfunctioned adjacent to each other? The distance between the collectors that are malfunctioning; Are the anomalies concentrated in specific road sections? Does the abnormal coverage area expand over time? Has the location of the anomaly center changed? Does the intensity of abnormal vibration decrease from the center to both sides?

[0078] When a localized cavity forms beneath a road section, the collector closest to the cavity may be the first to exhibit persistent anomalies. As the cavity expands, adjacent collectors may also begin to show anomalies.

[0079] The area controller determines whether the risk of road collapse has increased based on the increase in the number of abnormal data collectors, the extension of the abnormal duration, and the expansion of the abnormal coverage area.

[0080] The abnormal coverage area can be determined based on the distance between the collectors located at both ends of the abnormal section.

[0081] For example, if three consecutive data collectors malfunction and the distance between adjacent data collectors is 20 meters, the area controller determines the corresponding affected area based on the installation locations of the two data collectors located at the ends of the malfunctioning section.

[0082] The data platform or regional controller acquires target monitoring data generated by each collector during historical periods when no abnormalities occurred on the road.

[0083] Historical target monitoring data are categorized according to different time periods, traffic flows, or weather conditions within a day, and the normal range of vibration amplitude, spectrum data, dynamic acceleration, and angular velocity changes are statistically analyzed separately.

[0084] When historical data includes confirmed vehicle traffic interference, vehicle impact interference, equipment failure, or road surface anomaly events, the corresponding data will not be used to determine the normal vibration range.

[0085] The area controller compares the current target monitoring data with the normal vibration range of the corresponding installation location to determine the extent to which the current data exceeds the normal vibration range.

[0086] The area controller determines the road subsidence risk level based on the following data: Single-point abnormal amplitude, abnormal duration, spectral data changes, abnormal change rate, number of data acquisition devices with abnormalities, abnormal coverage area, abnormal intensity after interference data processing, degree of change of current data relative to normal vibration range, and historical data change trend.

[0087] In this embodiment, the risk of road collapse is divided into four levels: 1. Suspected abnormality level When a data acquisition device exhibits a slight anomaly, the anomaly lasts for a short period, or the current data slightly exceeds the normal vibration range, it is classified as a suspected anomaly.

[0088] The corresponding alarm actions include recording abnormal events, displaying abnormal prompts on the data platform, and sending inspection prompts to road patrol personnel.

[0089] 2. Persistent Abnormality Level When the same data logger shows abnormalities for multiple consecutive monitoring periods, the abnormality persists after the vehicle leaves, or the degree of change of the current data relative to the normal vibration range continues to increase, it is determined to be a continuous abnormality level.

[0090] The corresponding alarm actions include sending alarm information to road maintenance personnel, increasing the sampling frequency of the abnormal collector and its adjacent collectors, shortening the data analysis cycle of the area controller, and prompting maintenance personnel to conduct on-site inspections.

[0091] 3. Multiple anomaly levels When multiple adjacent data collectors exhibit abnormalities within a preset time period, the abnormalities are continuously distributed along the road direction, the abnormal coverage area gradually expands, or multiple data collectors remain in an abnormal state after the vehicle leaves, it is determined to be a multi-point abnormality level.

[0092] The corresponding alarm actions include sending alarm information to road management personnel, triggering on-site audible and visual alarms, marking risky road sections on the data platform, and outputting speed limit or lane control prompts.

[0093] 4. High-risk subsidence level When the intensity of abnormal vibration detected by multiple adjacent data collectors increases rapidly, the abnormal coverage area expands in a short period of time, the acceleration and angular velocity data show significant abrupt changes, or the abnormality of multiple data collectors continues for more than the preset high-risk judgment time, it is determined to be a high-risk collapse level.

[0094] The corresponding alarm actions include sending emergency alarm information, activating on-site audible and visual alarms, and outputting at least one of the following disposal instructions: speed limit, traffic control, isolation of risky road sections, and closure of risky road sections.

[0095] The area controller continues to monitor the abnormal road section after an alarm is triggered.

[0096] When the intensity of abnormal vibration increases, the duration of abnormality increases, the number of abnormal data acquisition devices increases, or the coverage area of ​​abnormality expands, the current alarm will be upgraded to a higher level.

[0097] When the abnormal data returns to the normal vibration range, the system does not immediately cancel the alarm. Instead, it maintains normal operation for several consecutive monitoring periods before lowering the alarm level or canceling the alarm.

[0098] For multiple anomaly levels and high-risk collapse levels, manual confirmation conditions can be set. The system continues to retain alarm records and risk markers until road management personnel complete the on-site inspection.

[0099] The data platform stores the following data according to the data acquisition device number, installation location, and acquisition time: Raw triaxial acceleration data, raw triaxial angular velocity data, target monitoring data, vehicle traffic interference markers, vehicle impact interference markers, single-point anomaly analysis results, regional anomaly results, road collapse risk level, alarm events and alarm handling results, and equipment operating status.

[0100] The data platform statistically analyzes the vibration at each collection location over different time periods and determines the normal vibration range for the corresponding installation location based on historical data.

[0101] If the vibration intensity at a certain installation location has not yet reached the immediate alarm condition, but continues to increase over a long period of time, the data platform marks the location as a deteriorating condition location and sends an inspection prompt to the road management personnel.

[0102] The data platform can also compare data from different months, quarters, or years to determine whether road conditions are gradually deteriorating, the earliest time an anomaly occurred, whether the number of anomalies has increased, whether the duration of anomalies has lengthened, whether the scope of anomalies has expanded, and whether the risk level is trending upward.

[0103] This embodiment eliminates vehicle vibrations moving along the road by using the time and positional relationships between multiple data collectors, and identifies continuous anomalies at fixed locations and situations where the anomaly coverage area expands, thereby achieving graded alarm for road collapse risk.

[0104] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing a particular logical function or process, and the scope of the preferred embodiments of the invention includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as will be understood by those skilled in the art to which embodiments of the invention pertain.

[0105] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: electrical connections having one or more wires (electronic devices), portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and programmable read-only memory (EPROM or flash memory), fiber optic devices, and portable solid-state drives or hard disk drives. Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0106] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), microcontrollers (MCUs), etc.

[0107] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0108] Furthermore, the functional units in the various embodiments of the present invention can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0109] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A real-time sensing and graded alarm triggering system for road subsidence, characterized in that, It includes multiple data collectors, at least one area controller, a data platform, and an alarm module; Multiple data acquisition units are installed at equal intervals along the road extension direction on the highway crash barrier. Each data acquisition unit includes a main control unit, an inertial measurement unit, a first communication unit, and a power supply unit. The inertial measurement unit includes one or more inertial measurement components, and each inertial measurement component includes a triaxial accelerometer and a triaxial angular velocity meter. The data acquisition device is used to acquire triaxial acceleration data and triaxial angular velocity data at the corresponding installation position according to a preset sampling frequency, and to obtain at least one of vibration frequency, vibration amplitude, spectrum data, dynamic acceleration, vibration-induced torque, and abnormal vibration characteristics based on the triaxial acceleration data and the triaxial angular velocity data. The data collector is also used to compare the abnormal vibration characteristics with the pre-stored vehicle traffic vibration characteristics and vehicle impact vibration characteristics, identify the vehicle traffic interference data and vehicle impact interference data in the collected data, and remove or correct the identified interference data to obtain the target monitoring data. The area controller is used to receive target monitoring data and abnormal vibration characteristics sent by multiple collectors through the first communication unit, perform single-point anomaly analysis on the data sent by a single collector, and perform time correlation analysis and location correlation analysis based on the installation location, anomaly occurrence time and abnormal vibration characteristics of multiple collectors to obtain the area anomaly result; The area controller is also used to determine the road collapse risk level based on the single-point anomaly analysis results, the area anomaly results, and the preset collapse judgment rules, and to control the alarm module to execute an alarm action corresponding to the road collapse risk level. The data platform is used to receive the collected data, analysis results, and alarm events sent by the area controller, store the collected data, analysis results, and alarm events, and obtain the status change information of the road to be monitored based on historical data arranged according to the collection time.

2. The real-time perception and graded alarm triggering system for road collapse according to claim 1, characterized in that, The number of inertial measurement units is one to four; When there are two or more inertial measurement units, the data acquisition unit compares the data obtained by each inertial measurement unit at the same acquisition time, determines the vibration changes detected by two or more inertial measurement units as valid vibration data, and marks the vibration changes detected by only one inertial measurement unit as data to be checked.

3. The real-time perception and graded alarm triggering system for road collapse according to claim 1, characterized in that, Identifying the vehicle traffic interference data and vehicle impact interference data includes: Extract at least one of the following from the collected data: vibration amplitude, frequency component, vibration intensity in different frequency ranges, vibration duration, rate of change of acceleration, rate of change of angular velocity, and data variation relationship in different measurement directions; The extracted data is compared with pre-stored vehicle traffic vibration characteristics and vehicle impact vibration characteristics; When the comparison result meets the vehicle traffic vibration characteristics or vehicle impact vibration characteristics, the collected data for the corresponding time period is marked as interference data. The vehicle traffic vibration characteristics include vibrations that pass through multiple data collectors sequentially along the vehicle's travel direction and weaken or disappear after the vehicle leaves; the vehicle impact vibration characteristics include vibration peaks that rapidly increase and then decrease within a preset time period.

4. The real-time perception and graded alarm triggering system for road collapse according to claim 1, characterized in that, The first communication unit communicates with the area controller using at least one of LoRa, Wi-Fi, StarFlash, or Bluetooth. The area controller sends collected data, analysis results, alarm events, and device operating status to the data platform via at least one of a fourth-generation mobile communication network and a wired network.

5. The real-time perception and graded alarm triggering system for road collapse according to claim 1, characterized in that, The installation distance between adjacent collectors is equal. The area controller is used to receive data sent by one to 1,500 collectors and to save the device number, installation location, installation order and adjacency relationship of each collector.

6. The real-time perception and graded alarm triggering system for road collapse according to claim 5, characterized in that, The time correlation analysis and location correlation analysis include: Obtain the start time, duration, installation location, and installation sequence of each data acquisition device exhibiting abnormal vibration characteristics; Determine whether multiple data collectors malfunction within a preset time period, whether the malfunctioning data collectors are adjacent or consecutively distributed, and whether the malfunction spreads from the installation location of one data collector to the installation locations of adjacent data collectors. The abnormal results in the region are determined based on the number of abnormal data collectors, the distance between adjacent abnormal data collectors, the intensity of abnormal vibration, and the duration of abnormality.

7. The real-time perception and graded alarm triggering system for road collapse according to claim 1, characterized in that, The collapse determination rules include at least one of the following: single-point abnormal amplitude, abnormal duration, spectrum data change, abnormal change rate, number of collectors with abnormalities, abnormal coverage area, abnormal intensity after interference data processing, and historical data change trend. The road surface collapse risk levels include suspected abnormality level, continuous abnormality level, multi-point abnormality level, and high-risk collapse level.

8. The real-time perception and graded alarm triggering system for road collapse according to claim 7, characterized in that: The suspected anomaly level corresponds to the recording of abnormal events and the sending of inspection prompts; The continuous anomaly level corresponds to sending alarm information to road maintenance personnel and increasing the sampling frequency of the anomaly collector and its adjacent collectors; The aforementioned multi-point anomaly levels correspond to sending alarm information to road management personnel and triggering on-site audible and visual alarms; The high-risk collapse level corresponds to sending an emergency alarm message and outputting at least one of the following disposal instructions: speed limit, traffic control, risk section isolation, and risk section closure.

9. A method for real-time sensing and graded alarm triggering of road surface collapse, characterized in that, Includes the following steps: Multiple data collectors are installed at equal intervals along the road extension direction on the highway crash barrier to collect triaxial acceleration data and triaxial angular velocity data at each installation location according to a preset sampling frequency. Based on the triaxial acceleration data and the triaxial angular velocity data, at least one of the following is obtained: vibration frequency, vibration amplitude, spectrum data, dynamic acceleration, torque caused by vibration, and abnormal vibration characteristics. The abnormal vibration characteristics are compared with the pre-stored vehicle traffic vibration characteristics and vehicle impact vibration characteristics. The vehicle traffic interference data and vehicle impact interference data in the collected data are identified, and the identified interference data are removed or corrected to obtain the target monitoring data. Single-point anomaly analysis is performed on the target monitoring data of a single data acquisition device, and time correlation analysis and location correlation analysis are performed based on the installation location, anomaly occurrence time and abnormal vibration characteristics of multiple data acquisition devices to obtain regional anomaly results; The road surface collapse risk level is determined based on the results of single-point anomaly analysis, regional anomaly results, and preset collapse judgment rules. Execute the corresponding alarm action according to the road collapse risk level; The collected data, analysis results, and alarm events are sent to the data platform for storage, and the status change information of the monitored road is obtained based on historical data arranged according to the collection time.

10. The method for real-time perception and graded alarm triggering of road collapse according to claim 9, characterized in that, The road surface collapse risk level is determined based on the single-point anomaly analysis results, the regional anomaly results, and the preset collapse judgment rules, including: Acquire target monitoring data from the corresponding data collector within a preset historical time period; The normal vibration range for the corresponding installation location is determined based on the target monitoring data; Determine the degree of change in the current target monitoring data relative to the normal vibration range; The road collapse risk level is determined based on the degree of change, duration of the anomaly, number of data collectors exhibiting anomalies, coverage area of ​​the anomaly, and historical data trends.

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