Paving quality detection method for highway engineering

Abstract

The invention discloses a pavement quality detection method for highway engineering, and relates to the technical field of highway engineering quality detection, and the method comprises the steps: carrying out the segmentation of a road section, determining a road section detection element, developing a microcontroller through a dynamic inspection dimension, carrying out the embedded deployment of an intelligent inspection device, carrying out the development of a quality detection module through a static detection dimension, and carrying out the deployment of a road detection system. According to the method, an integrated detection framework is constructed, road laying quality detection under the cooperation of dynamic inspection and static detection is executed, a quality detection result is determined, and the technical problems that in the prior art, full-automatic, efficient and accurate quality monitoring is difficult to achieve through detection equipment and methods, manual intervention is large, and data processing is not timely are solved. A road paving quality detection method combining dynamic inspection and static detection is provided, and accurate capture of road section detection elements and real-time feedback of quality detection are realized through cooperative work of intelligent inspection equipment and a sensing array.

Description

Technical Field

[0001] The present invention relates to the technical field of highway engineering quality inspection, and particularly relates to a method for inspecting the paving quality of highway engineering. Background Art

[0002] In highway engineering, the inspection of paving quality is an important link to ensure the construction quality and safety of roads. At present, the methods for inspecting highway paving quality are mostly manual inspections or partial automation means, usually relying on manual patrols and local sensor data collection. There are problems such as low efficiency, poor real-time performance, and insufficient accuracy, making it difficult to achieve comprehensive quality monitoring. Especially in large-scale projects, relying on a single-dimensional inspection method often cannot comprehensively evaluate the paving quality of sections.

[0003] Therefore, in the prior art, there are the following problems with the method for inspecting the paving quality of highway engineering. The existing inspection equipment and methods are difficult to achieve full-automatic, efficient, and accurate quality monitoring, and there are problems such as a lot of manual intervention and untimely data processing. Summary of the Invention

[0004] This application provides a method for inspecting the paving quality of highway engineering, which is used to solve the technical problems in the prior art that the existing inspection equipment and methods are difficult to achieve full-automatic, efficient, and accurate quality monitoring, and there are problems such as a lot of manual intervention and untimely data processing.

[0005] In view of the above problems, this application provides a method for inspecting the paving quality of highway engineering. The method includes: retrieving engineering drawings, performing segment division of sections under traffic condition changes, and determining section inspection elements, where each divided section corresponds to a set of section inspection elements; for the engineering cycle, based on the section inspection elements, developing a microcontroller in a dynamic patrol dimension and embedding it in an intelligent patrol device, and developing a quality inspection module in a static inspection dimension and deploying it in a road inspection system, where the intelligent patrol device is provided with an external expansion interface; establishing communication interaction among the sensor array, the intelligent patrol device, and the road inspection system, constructing an integrated inspection architecture, performing highway paving quality inspection under the coordination of dynamic patrol and static inspection, and determining the quality inspection result, where the execution of dynamic patrol and static inspection is relatively independent and coordinated.

[0006] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0007] A method for detecting the laying quality of highway engineering provided by an embodiment of the present application retrieves engineering drawings, performs segment division under changing road conditions, and determines segment detection elements. Among them, each divided segment corresponds to a set of segment detection elements. For the project cycle, according to the segment detection elements, a microcontroller is developed in the dynamic patrol dimension and embedded in the intelligent patrol device, and a quality detection module is developed in the static detection dimension and deployed in the road detection system. Among them, the intelligent patrol device is provided with an external expansion interface. Establish communication interaction among the sensor array, the intelligent patrol device and the road detection system, construct an integrated detection architecture, perform highway laying quality detection under the coordination of dynamic patrol and static detection, and determine the quality detection result. Among them, the execution of dynamic patrol and static detection is relatively independent and coordinated. It is used to solve the technical problems in the prior art that it is difficult for detection devices and methods to achieve full-automatic, efficient, and accurate quality monitoring, and there are many manual interventions and untimely data processing. Provide a highway laying quality detection method combining dynamic patrol and static detection, and through the collaborative work of the intelligent patrol device and the sensor array, realize the accurate capture of segment detection elements and the real-time feedback of quality detection. Description of the Drawings

[0008] Figure 1 It is a schematic flow chart of a method for detecting the laying quality of highway engineering provided by the present application;

[0009] Figure 2 It is a schematic flow chart of the development of the microcontroller in a method for detecting the laying quality of highway engineering provided by the present application. Detailed Embodiments

[0010] The present application provides a method for detecting the laying quality of highway engineering to solve the technical problems in the prior art that it is difficult for detection devices and methods to achieve full-automatic, efficient, and accurate quality monitoring, and there are many manual interventions and untimely data processing.

[0011] Embodiment: As Figure 1 shown, the present application provides a method for detecting the laying quality of highway engineering, and the method includes:

[0012] S1: Retrieve engineering drawings, perform segment division under changing road conditions, and determine segment detection elements. Among them, each divided segment corresponds to a set of segment detection elements.

[0013] In the embodiment of the present application, the engineering drawings contain key information such as the design requirements, segment planning, construction technology, and pavement structure of the highway, and all laying details will be marked in the drawings. When retrieving the engineering drawings, it is necessary to ensure the accuracy and integrity of the obtained drawings, especially the specific structures of each section of the road surface, bridge, tunnel, etc.

[0014] Furthermore, the road is segmented according to the changes in road conditions. Among them, the segmentation of road sections takes into account factors such as pavement structure and terrain characteristics, and is segmented based on the distinctiveness of road conditions for targeted detection under specific road conditions. In actual operation, tools such as Geographic Information System (GIS) are used to assist in segmenting road sections. According to road types, such as elevated road sections and urban traffic sections; according to road states, such as linear and curved road sections; for road sections with special geographical features, such as bridges and ramps, more specific targeted detection elements are usually set for different road sections to ensure that the quality of each road surface can be comprehensively monitored.

[0015] After completing the segmentation of road sections, corresponding detection elements are then determined for each segmented road section, which may specifically include pavement evenness, subgrade bearing capacity, geometric characteristics, etc. The element standards are different for different road sections, so the specific quality evaluation criteria are also different. At the same time, there are also personalized detection elements based on road condition characteristics. For example, in the road section of a bridge, the detection of pavement compressive strength and fatigue performance is usually increased, while in ordinary road sections such as urban streets, the monitoring mainly focuses on evenness, etc. The setting of detection elements for each segmented road section should be adjusted according to actual construction and usage requirements, and the detection elements determined for each road section are summarized and recorded in a digital database for subsequent data analysis and quality assessment.

[0016] In summary, by retrieving engineering drawings, segmenting road sections in combination with actual situations, and determining corresponding detection elements for each segmented road section, the subsequent quality inspection work is ensured to be more refined.

[0017] S2: For the engineering cycle, based on the road section detection elements, a microcontroller is developed in the dynamic inspection dimension and embedded in the intelligent inspection device, and a quality inspection module is developed in the static detection dimension and deployed in the road detection system, where the intelligent inspection device is provided with an external expansion interface.

[0018] In the embodiment of the present application, the engineering cycle is the complete cycle of road paving construction. First, a suitable microcontroller is developed based on the detection elements of each road section. The development of the microcontroller needs to consider the detection requirements of specific road sections and the actual progress of the project, that is, it is deployed based on the detection element-quality standard. During the engineering cycle, the paving progress and construction environment of the road are constantly changing, so the developed microcontroller needs to have the flexibility to adapt to different detection dimensions. In the dynamic inspection dimension, the microcontroller is mainly responsible for data collection and autonomous analysis under real-time monitoring. It can adjust parameters such as the collection frequency and collection method in a timely manner according to the changes in the detection elements of different engineering cycles of road sections to ensure that the most accurate data can be obtained at different construction stages.

[0019] Further, the microcontroller is embedded and deployed in the intelligent inspection device. The embedded deployment ensures that the microcontroller can be highly integrated directly with the hardware system of the intelligent inspection device, enabling rapid response and automated operation of the device. That is, the intelligent inspection device is driven by autonomous requirements to perform functions such as real-time data collection, processing, and autonomous decision-making. By embedding the microcontroller in the intelligent inspection device, automatic inspection of highway sections can be achieved, and various types of data related to the sections can be obtained in real time.

[0020] In addition, to enhance flexibility and scalability, the intelligent inspection device will be provided with an external expansion interface. The external interface can be regarded as an edge data processing node for sensing and monitoring of this section of the road. It is connected to the sensing devices of this section of the road and performs preprocessing before data integration and transmission back. For example, the external interface can be connected to temperature and humidity sensors, ground pressure sensors, vibration sensors, etc. to monitor changes in the road state in real time and obtain more diverse data. The introduction of the external expansion interface standardizes the overall detection system, avoids transmission redundancy of direct sensing data, can effectively improve the interaction efficiency and quality, and enhances the adaptability of detection and the stability of long-term operation.

[0021] Meanwhile, in the static detection dimension, for the quality inspection requirements of highway paving, a quality detection module is developed and deployed in the road detection system. These quality detection modules are responsible for detecting and analyzing the distributed sensing and collected data, ensuring the accuracy and integrity of the data, identifying potential defects in the highway paving process, and providing real-time quality assessment.

[0022] In this application, through the combination of two dimensions of dynamic inspection and static detection, and the deployment of the microcontroller and the quality detection module, all-round monitoring of highway paving quality is ensured. The external expansion interface of the intelligent inspection device provides greater flexibility, can be regarded as the function of an edge-side data node, and improves the transmission standardization of the distributed sensing array. Thus, a more efficient and accurate quality detection process is achieved.

[0023] Furthermore, as Figure 2 shown, according to the section detection elements of the section, a microcontroller is developed in the dynamic inspection dimension. Step S2 of this application includes:

[0024] For the section detection elements of the first segmented section, determine the first dynamic inspection elements and the first static detection elements, where the elements include monitoring elements - quality index elements; according to the first dynamic inspection elements, develop a first micro detector, and embed and deploy the first micro detector in the first intelligent inspection device; lower the first intelligent inspection device to the first segmented section.

[0025] Further, a first quality detection branch is developed according to the first static detection element; the first quality detection branch is deployed in the road detection system, wherein the quality detection branches of each segmented section are integrally deployed in the quality detection module within the road detection system.

[0026] In this application, the first segmented section is any segmented section, and according to the detection elements of the first segmented section, it is divided into dynamic inspection elements and static detection elements. The dynamic inspection elements are the part of the elements with relative changes in position, which are executed by intelligent inspection devices. For example, factors such as road surface conditions and construction progress, while the static detection elements focus more on the elements with full periodicity and fixed field of view, such as the monitoring of static characteristics such as road surface structure and bearing capacity. These elements together constitute the comprehensive detection index of the section, providing sufficient data support for subsequent quality evaluation.

[0027] Further, corresponding micro-detectors are developed according to the dynamic inspection elements of the first segmented section. Among them, a monitoring component is deployed in the intelligent inspection device, and the trigger sampling and quality detection of the monitoring component are used as the training objectives. In a feasible embodiment, the sampling rules are deployed according to the monitoring elements, and the built-in monitoring component of the device is triggered for acquisition, serving as the sampling node. According to the quality index elements, based on the quality conditions of this road condition, the quality annotation is performed on the sampled data, serving as the sample data. Through the way of sample learning, a quality detection node is constructed, and the sampling node and the quality detection node are cascaded as the first micro-detector of the first segmented section.

[0028] Furthermore, the micro-detector is deployed in the first intelligent inspection device in an embedded form, and the first intelligent inspection device is used to perform dynamic inspection on the divided first segmented section. High-efficiency and automated real-time monitoring can be achieved.

[0029] Similarly, for each segmented section, the segmentation based on the monitoring elements is performed respectively, a microcontroller is constructed for the dynamic inspection elements, and it is deployed in the intelligent inspection device and sent down to the corresponding section to perform dynamic inspection management.

[0030] In the embodiment of this application, in terms of static detection, a first quality detection branch is developed according to the static detection elements of the first segmented section. In a feasible embodiment, the way of sample learning is adopted, with the quality evaluation of the static monitoring elements as the decision-making objective. By annotating the sample sensing data as the training data and performing supervised learning until convergence, the first quality detection branch is determined.

[0031] Similarly, for each segmented road section, a quality inspection branch is constructed respectively based on the corresponding static inspection elements. To ensure the efficiency of the entire road inspection system, the quality inspection branches of each segmented road section will be uniformly integrated into the quality inspection module within the road inspection system. Among them, the quality inspection module is a system data block that executes quality inspection decisions, enabling the quality monitoring data of all road sections to be summarized on a unified platform, allowing for a comprehensive quality assessment and monitoring of each road section, facilitating subsequent quality control and defect warning.

[0032] Through the above steps, combined with dynamic patrol inspection and static inspection, the reasonable construction and deployment of micro-detectors and quality inspection branches ensure the all-round monitoring and accurate assessment of segmented road sections. This multi-level and comprehensive inspection system provides a strong guarantee for the quality of highway paving.

[0033] Furthermore, step S2 of this application includes: each segmented road section contains at least one intelligent patrol inspection device; an external interface is opened on the intelligent patrol inspection device to expand the data processing component; the external interface is connected to the sensor array as the convergence interface for road section detection data, and the data processing component performs data preprocessing and encapsulation of the sensor array, where the sensor array is distributedly deployed in the highway paving scenario to perform scenario monitoring.

[0034] In the embodiment of this application, in each segmented road section, due to the distinctiveness of inspection elements, adaptive microcontrollers are respectively constructed and deployed, and at least one intelligent patrol inspection device is used to conduct patrol inspection of this segmented road section to ensure the orientation of patrol inspection for each road section. The intelligent patrol inspection device is responsible for dynamic patrol inspection in the entire road inspection system. Based on the built-in microprocessor, it collects various types of data of the road section in real time as the field of view changes and performs autonomous quality inspection.

[0035] In this application, considering the data volume and data redundancy of the sensor array distributedly deployed in road sections, taking the intelligent patrol inspection device as the transfer processing node, an external interface is opened and a data processing component is deployed. The sensing data collected by the sensor array is first imported into the data processing component of the intelligent patrol inspection device based on the external interface, and after performing preprocessing and encapsulation on it, it is then transmitted back to the quality inspection module within the road inspection system for quality analysis.

[0036] Among them, the setting of the external interface allows the intelligent patrol inspection device to perform data interaction with external components, and the external components in this application refer to the sensor array deployed in the road section area. For example, the sensor array can include various types of devices such as temperature sensors, humidity sensors, pressure sensors, and vibration sensors, and these sensors are configured and distributed at each key monitoring point according to the inspection requirements of the road section.

[0037] Establishing the interaction of the external interface between the sensing array and the intelligent inspection device plays the role of data aggregation. This means that the data collected by all sensors distributed at various positions on the road section can be transmitted to the intelligent inspection device through the external interface and undergo preliminary processing and encapsulation. The data processing component preprocesses these collected data, removes redundant information, formats and classifies important data, and then encapsulates it to ensure the accuracy, effectiveness, and integrity of the data, and then performs data feedback based on the quality detection module. For example, data from different sensors can be sorted by timestamp to ensure that real-time data is not lost and can be transmitted in the specified format.

[0038] In a feasible embodiment, the data processing component is constituted by directional training. Guided by the preprocessing requirements of road data, multiple preprocessing layers are deployed, such as data screening, data classification, data encapsulation, etc. The multiple preprocessing layers are cascaded and supervised for training to obtain the data processing component.

[0039] The deployment of the sensing array in the highway paving scenario is distributed, that is, according to the characteristics of the road section and the monitoring requirements, the sensing type and monitoring location are determined, and monitoring is carried out at different positions on the road. This distributed deployment can comprehensively cover all detection elements of the road, and adopts the methods of dynamic inspection and directional sensing analysis to ensure that the paving quality of each road section is accurately evaluated.

[0040] In summary, the combination of the intelligent inspection device and the external interface, as well as the cooperation with the sensing array, not only realizes the efficient aggregation and processing of road section monitoring data, but also enhances the flexibility and scalability of monitoring and detection.

[0041] Furthermore, step S2 of this application includes: performing dynamic inspection with the self-inspection and self-detection of the intelligent inspection device; performing static inspection with the sensing array - external interface - data processing component - quality monitoring module; coordinating the dynamic inspection and the static inspection to construct an integrated monitoring architecture.

[0042] In the embodiment of this application, dynamic inspection is first performed through its self-inspection and self-detection functions. Self-inspection and self-detection mean that the intelligent inspection device can independently drive for dynamic mobile monitoring and quality detection, specifically driven by the built-in microcontroller to ensure the normal operation of the device during the inspection process.

[0043] Among them, the microcontroller drives the built-in components of the intelligent inspection device to collect data of the road section in real time, including but not limited to dynamic changes such as road surface conditions, temperature and humidity, and vibration. Then the data is transmitted back to the microcontroller to perform quality detection, forming an execution loop of self-inspection - self-detection.

[0044] Preferably, based on real-time analysis of the detection, the intelligent inspection device can quickly respond to changes in the road section, timely adjust the detection parameters and inspection methods to ensure that it can adapt to the real-time conditions of the road section. For example, when the device detects abnormal vibrations on the road surface, it may automatically adjust the acquisition frequency or activate specific components for in-depth analysis. This dynamic inspection mechanism ensures the continuity and accuracy of the inspection process, avoiding delays and errors caused by human intervention.

[0045] Meanwhile, the static inspection is completed by the collaborative work of the sensing array, external interface, data processing component and quality monitoring module. The static inspection focuses on the detection of the structural and quality indicators of the road section. The sensing array collects various data of the road section at different positions where the highway is laid through various sensors (such as pressure sensors, strain gauges, etc.). The data of these sensors are transmitted and aggregated to the external interface of the intelligent inspection device. The external interface not only provides a data access point but also ensures the stable transmission of data, preventing data loss or delay. Further trigger the data processing component extended at the external interface, and then preprocess these transmitted data, including data screening and standardization. After the processing is completed, data encapsulation is performed, and the processed data encapsulation package is transmitted back to the quality inspection module of the road detection system to trigger the branch of the corresponding road section for targeted quality analysis.

[0046] Specifically, according to the set quality standards, identify possible laying defects or non-compliant places in this road section, such as unqualified materials, insufficient structural strength, etc. Convert the analysis results into a specific quality assessment report for subsequent quality control and rectification. Through this process, the static inspection can complete a comprehensive quality assessment and fault warning without disturbing the highway construction process.

[0047] In this application, the collaborative work of dynamic inspection and static inspection constructs an integrated monitoring architecture. In this architecture, the dynamic inspection can provide real-time road surface condition inspection and feedback, while the static inspection provides in-depth detection for the long-term stability and quality of the road section. The two complement each other to ensure that every detail in the highway laying process can be accurately monitored and timely processed. This integrated monitoring architecture effectively improves the monitoring ability of highway laying quality and also reduces the inconvenience and risks brought by traditional manual inspections.

[0048] S3: Establish the communication interaction between the sensing array, intelligent inspection device and road detection system, construct an integrated detection architecture, perform highway laying quality detection under the coordination of dynamic inspection and static detection, and determine the quality detection results, where the execution of dynamic inspection and static detection is relatively independent and coordinated.

[0049] In the embodiments of the present application, it is first necessary to establish communication interactions among the sensing array, the intelligent inspection device, and the road detection system. The core purpose of this process is to ensure the smooth transfer of data streams and the coordinated operation among various components.

[0050] Among them, the sensing array is deployed at different positions on the road and is responsible for collecting various types of real-time data of the road section. These sensors transmit the data in real time to the external interface of the intelligent inspection device through wireless communication, optical fiber, or other suitable transmission methods. Among them, based on the extended data processing components, the external interface preliminarily processes the data from the sensing array and ensures the accuracy and integrity of the data.

[0051] Furthermore, based on the communication interaction between the intelligent inspection device and the road detection system, it ensures that the data of the sensing array can flow from the on-site sensing array to the peripheral interface. After being preprocessed and encapsulated, it is finally fed back to the quality inspection system. For this purpose, the intelligent inspection device will establish a real-time connection with the road detection system through the external interface to ensure the stability and timeliness of data during transmission.

[0052] Once the data reaches the road detection system, it triggers the built-in quality inspection module to further analyze and evaluate the quality of the data, and generate a quality inspection report for the road paving. Through this kind of communication interaction, an integrated detection architecture is constructed, and the system can process and make decisions on data at different levels, thereby improving the overall detection efficiency and accuracy.

[0053] Among them, the intelligent inspection device performs relatively independent self-inspection and self-detection. According to the communication interaction between the intelligent inspection device and the road detection system, the overall analysis of inspection detection and sensing detection can be realized.

[0054] In the present application, this integrated detection architecture supports the coordinated operation of dynamic inspection and static detection. Dynamic inspection is mainly responsible for real-time detection and monitoring of the road surface state, focusing on capturing the immediate changes in the road section, which are automatically sensed by the intelligent inspection device during the inspection process. Quality assessment is carried out based on real-time data, and the detection strategy is adjusted to ensure timely discovery of potential problems, such as uneven road surface, lane damage, etc.

[0055] At the same time, static detection focuses on the in-depth analysis of structural problems of the road section. This part of the detection is mainly completed by the sensing array. After the data is transmitted to the road detection system, detailed quality assessment and structural analysis are carried out.

[0056] In the mode of collaborative work between dynamic patrol inspection and static detection, although the two detection methods are independently executed, they can exert a synergistic effect in the overall system. Dynamic patrol inspection can immediately feedback the changes of the road section and provide real-time background information for static detection; while static detection provides a benchmark for dynamic patrol inspection to ensure comprehensive and long-term stability monitoring of the road section quality at different time points. The combination of the two can not only improve the detection efficiency of highway paving quality, but also ensure the comprehensiveness and accuracy of monitoring.

[0057] Furthermore, for the highway paving quality detection under static detection, step S3 of this application includes:

[0058] According to the sensing array, perform sensing difference frequency triggering to determine highway sensing data; according to the road section of the highway sensing data, import it into the external interface of the local intelligent patrol inspection device, assist the embedded data processing component, perform regularization and encapsulation under data redundancy removal, and determine the sensing data packet; transmit the sensing data packet back to the road detection system, trigger the embedded quality detection module, perform quality detection, and determine the first quality detection result.

[0059] In the embodiment of this application, sampling triggering processing is performed on multiple sensors in the sensing array by means of asynchronous sampling. Since the detection requirement types and construction actual situations are different for different sensing types and different positions, the sampling of the sensing array is adaptively configured according to the requirements. For example, different sampling rules are set for different sensing types and different positions, such as different sampling frequencies, etc. Difference frequency triggering ensures high-precision and effective sensing data acquisition, can reduce data redundancy in the acquisition stage, and provides accurate original data for subsequent data processing.

[0060] Next, according to the obtained highway sensing data, with the external interface of the intelligent patrol inspection device deployed in this road section as the transmission target, import the data into the external interface of the local intelligent patrol inspection device. The external interface of the intelligent patrol inspection device serves as the hub of data interaction, transmits the data collected by the sensing array to the data processing component expanded by the external interface. Subsequently, further process the incoming data, perform preprocessing such as data redundancy removal and regularization, and encapsulate the preprocessed data. Among them, encapsulation is to pack the processed data into a format suitable for transmission to form a complete sensing data packet. The data packet contains all valid data points to ensure that the integrity and consistency of information are not affected when it is transmitted back to the road detection system.

[0061] Subsequently, the sensing data packets are sent back to the road detection system. Specifically, through a stable communication channel, the data packets are transmitted to the quality detection module in the road detection system. The quality detection module is embedded in the detection system and is responsible for receiving and parsing the backhaul sensing data packets and performing quality detection based on preset quality standards. The quality detection process includes data comparison, outlier identification, standard compliance judgment, etc. By comparing the actual data with the preset standard values, it is determined whether the paving quality of the road section meets the standards.

[0062] Finally, the quality detection module will obtain the first quality detection result, that is, the quality detection result for the data collected by the sensing array, and feedback it to the relevant personnel. It can provide a basis for highway paving quality assessment and maintenance decision-making. If non-compliant areas are found in the detection results, subsequent rectification or re-inspection processes will be triggered to ensure that the highway paving quality meets the specified requirements.

[0063] In summary, the quality detection process realizes efficient and accurate automatic monitoring, ensuring real-time detection and evaluation of highway paving quality. It not only improves the detection efficiency but also greatly enhances the accuracy and reliability of the detection data.

[0064] Furthermore, to perform highway paving quality detection under the coordination of dynamic patrol and static detection and determine the quality detection result, step S3 of this application includes:

[0065] By performing self-patrol and self-detection of the intelligent patrol device, determine the second quality detection result; fuse the first quality detection result and the second quality detection result as the quality detection result.

[0066] In the embodiment of this application, the intelligent patrol device performs self-patrol and self-detection functions. Based on the embedded microcontroller, during the dynamic movement of the intelligent patrol device, the monitoring components self-configured by the device are sampled and triggered and sent back to the microcontroller for quality detection analysis to determine the second quality detection result. Among them, the second quality detection result is the quality detection result in the dimension of dynamic patrol.

[0067] Next, fuse the first quality detection result and the second quality detection result to obtain the final quality detection result. The first quality detection result comes from the sensing array data, and the second quality detection result comes from dynamic patrol, which mainly evaluates the immediate status and changes of the road section. By fusing the two, a more comprehensive and integrated quality assessment can be formed.

[0068] In a feasible embodiment, the fusion process adopts the method of weighted average and temporal integration, that is, for the first quality inspection result and the second quality inspection result corresponding to the same quality index, the results at the same time node are weighted and averaged. Exemplarily, the weighting is carried out according to the influence degree of the dynamic dimension; the results at different time nodes are integrated in a time series.

[0069] Among them, the first quality inspection result and the second quality inspection result can complement each other, comprehensively cover the quality characteristics of the road section, determine accurate and comprehensive quality inspection results, and provide a comprehensive quality assessment report for engineering construction personnel. This result can be used for subsequent quality control, defect investigation, engineering optimization and other work.

[0070] Further, after determining the first quality inspection result, the steps of this application also include:

[0071] Identify the first quality inspection result, determine the directional re-inspection requirement; according to the directional re-inspection requirement, generate a patrol guidance instruction, and send the patrol guidance instruction to the intelligent patrol device to drive the execution of the patrol control under the directional feedback.

[0072] In the embodiment of this application, the first quality inspection result can reveal potential defects or non-compliant areas existing in the highway paving process, such as uneven road surface, insufficient bearing capacity, etc. After identifying these problems, according to the severity and risk assessment of the inspection results, it is decided whether re-inspection is needed, and the specific direction and scope of the re-inspection are determined.

[0073] Among them, the directional re-inspection requirement is based on the problems found in the first quality inspection result. For example, if the inspection result shows that there is a flatness problem in a certain section of the road surface, or the material quality of a certain part does not meet the standard, the system will judge that directional re-inspection of this area is required. Because the sensor array is deployed at fixed positions and cannot monitor fine-grained features.

[0074] This process not only focuses on the specific defect location, but also takes into account the possible influence range and severity to ensure the accuracy and effectiveness of the re-inspection.

[0075] Further, according to the directional re-inspection requirement, a patrol guidance instruction is generated. The patrol guidance instruction is a specific instruction for the intelligent patrol device to perform the directional re-inspection task. The instruction content includes the specific location of the re-inspection, the parameters that need to be focused on for inspection, the steps of the re-inspection, and the execution order of the re-inspection, etc. The instruction will guide the intelligent patrol device to conduct targeted directional re-inspection of the road section to ensure that the problems are accurately identified and resolved in a timely manner. Preferably, when generating the patrol guidance instruction, the system will flexibly adjust the instruction content in combination with the specific situation of the road section and the re-inspection requirement to ensure the efficient execution of the patrol task.

[0076] In summary, the detection circuit is optimized to achieve precise directional re-inspection, ensuring that after problems are discovered, the problem areas can be concentratedly processed quickly and effectively. This flexible re-inspection control not only improves the accuracy of detection but also can adjust the inspection plan through timely feedback, enhancing the intelligent level of highway quality detection.

[0077] Further, after determining the quality inspection result, the steps of this application further include:

[0078] Identifying the engineering drawing and determining the quality slack; using the quality slack as a constraint to determine the laying project defects based on the quality inspection result; and alarming the laying project defects.

[0079] Further, after alarming the laying project defects, the steps of this application further include:

[0080] Determining the quality rectification method, where the quality rectification method includes the resumption of work laying method and the lower-level rectification method, and the lower-level rectification method is the laying compensation based on the lower-level cycle nodes of the project; receiving the alarm information and performing laying compensation processing on the laying project defects by executing any quality rectification method.

[0081] In the embodiment of this application, the engineering drawing provides the design specifications and construction requirements. By analyzing the drawing in detail, the quality slack is determined. The quality slack refers to the allowable deviation range of the section laying quality during the highway laying process. According to the engineering design standard, the quality slack is usually set according to material specifications, construction techniques, and pavement structure requirements, describing the allowable degree of deviation of highway quality from the standard during the construction process.

[0082] Next, quality defect positioning is performed with the quality slack as a constraint, that is, when the deviation found in the quality inspection result during the highway laying process exceeds the set quality slack, the corresponding laying project defects are identified. For example, if problems such as uneven road surface, insufficient bearing capacity, or non-compliant material thickness occur, it is determined whether a warning needs to be issued based on the comparison between the detection data and the slack, that is, when the quality defect is greater than the quality slack, an alarm process needs to be executed.

[0083] Further, an alarm signal is immediately sent. The content of the alarm includes information such as the type, severity, and location of the defect, ensuring that relevant staff can receive the information in time and take measures.

[0084] Further, after warning about the defects in the paving project, the steps of the present application further include determining the quality rectification method. The quality rectification method is divided into the resumption of paving method and the lower-level rectification method. The resumption of paving method usually refers to reworking on sections with serious defects. In the actual implementation process, the resumption of paving method is applicable to situations where the defects are relatively serious and cannot be remedied by repair measures.

[0085] Among them, the lower-level rectification method corrects the quality deviation by adjusting and compensating the lower-level cycle nodes of the project. The lower-level rectification method usually repairs relatively minor quality problems in the section during the subsequent construction process through methods such as partial remedy, reinforcement, or detail repair.

[0086] Specifically, after receiving the warning information, corresponding paving compensation processing is performed according to the selected quality rectification method. In a preferred embodiment, when performing the compensation processing, a suitable rectification strategy is selected according to the actual situation of the project and the nature of the defects. For sections that need to resume paving, it may be necessary to re-arrange the construction plan. For example, additional rework nodes are added to rework on the defects of the section; while for the case of using the lower-level rectification method, the system will, on the existing basis, perform compensation through methods such as detail repair and material supplementation when executing the next construction node to ensure that the quality of the section meets the standards.

[0087] In summary, with a flexible quality rectification method, the system can quickly and effectively repair problems when defects in the paving project occur, ensuring the stability and reliability of the highway paving quality. This not only improves the quality control efficiency during the construction process but also guarantees the long-term service performance of the road.

[0088] A paving quality detection method for highway engineering provided by the present application has the following technical effects:

[0089] 1. Segment sections under changing road conditions in combination with engineering drawings, and configure independent section detection elements for each segmented section. Differentiated detection is carried out for the road conditions of different sections, such as subgrade, pavement, bridges and tunnels, etc., avoiding a one-size-fits-all detection method and improving the accuracy of detection. For example, the expansion joints displacement is monitored keyly for the elevated bridge section, and the water seepage situation is monitored keyly for the tunnel section, realizing the optimal allocation of detection resources.

[0090] 2. Develop embedded microcontrollers and deploy them in intelligent inspection equipment to achieve high-frequency and mobile inspections. Develop quality inspection modules and deploy them in road inspection systems to achieve full-section, long-term monitoring. Build an integrated inspection architecture through communication and interaction between sensor arrays, intelligent inspection equipment, and road inspection systems. Dynamic inspections can quickly respond to sudden problems, and sensor detection can monitor stability indicators such as roadbed settlement and stress distribution over a long period of time. The two work together to ensure the timeliness of detection and the comprehensiveness of data. For example, when dynamic inspections find that the crack expansion rate in a certain area is abnormal, the static inspection module can be immediately triggered to perform high-precision three-dimensional modeling to provide data support for defect repair.

[0091] 3. Distributed deployment of sensor arrays in highway paving scenarios to perform scene monitoring. The intelligent inspection equipment expands the interface, opens an external interface, connects the sensor array, and serves as the aggregation interface for road section detection data. It also expands the data processing component to perform data preprocessing and packaging. The deep integration of the sensor array and the intelligent inspection equipment realizes real-time data collection, preprocessing and transmission, reduces data redundancy, and improves detection efficiency.

[0092] Through the above-mentioned detailed description of a method for detecting the paving quality of a highway project in this specification, those skilled in the art can clearly know the method for detecting the paving quality of a highway project in this embodiment. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the description of the method part.

[0093] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for detecting the paving quality of a highway project, characterized in that: The method comprises: Retrieving engineering drawings, segmenting the road sections under changing road conditions, and determining the road section detection elements, wherein each segmented road section corresponds to a set of road section detection elements; According to the road section detection elements, a microcontroller is developed in the dynamic inspection dimension and embedded in the intelligent inspection equipment for the engineering cycle, and a quality inspection module is developed in the static inspection dimension and deployed in the road inspection system, wherein the intelligent inspection equipment is provided with an external expansion interface; Establish communication interaction among sensor arrays, intelligent inspection equipment and road detection systems, build an integrated detection architecture, perform highway paving quality inspection under the coordination of dynamic inspection and static inspection, and determine the quality inspection results. Among them, the execution of dynamic inspection and static inspection is relatively independent and coordinated.

2. A method for detecting the paving quality of a highway project as claimed in claim 1, characterized in that: According to the road section detection elements, a microcontroller is developed in a dynamic inspection dimension, including: For the road segment detection elements of the first segmented road segment, determine a first dynamic inspection element and a first static detection element, wherein the elements include a monitoring element-quality indicator element; Develop a first micro-detector according to the first dynamic inspection element, and embed the first micro-detector in a first intelligent inspection device; The first intelligent inspection device is deployed to the first divided road section.

3. A method for detecting the paving quality of a highway project as claimed in claim 2, characterized in that: Developing a first quality detection branch based on the first static detection element; The first quality detection branch is deployed in a road detection system, wherein the quality detection branch of each segmented road section is integrated and deployed in a quality detection module in the road detection system.

4. A method for detecting the paving quality of a highway project as claimed in claim 3, characterized in that: Each segmented road section contains at least one intelligent inspection device; Opening an external interface on the intelligent inspection device and expanding the data processing component; The external interface is connected to the sensor array as an aggregation interface for road section detection data, and the data processing component performs data preprocessing and packaging of the sensor array, wherein the sensor array is distributedly deployed in a highway paving scene to perform scene monitoring.

5. A method for detecting the paving quality of a highway project as claimed in claim 4, characterized in that: Perform dynamic inspections by using the self-inspection and self-testing of the intelligent inspection equipment; Static inspection is performed using the sensor array-external interface-data processing component-quality monitoring module; The dynamic inspection and the static inspection are coordinated to build an integrated monitoring architecture.

6. A method for detecting the paving quality of a highway project as claimed in claim 4, characterized in that: Perform static testing of road paving quality, including: According to the sensor array, performing sensor difference frequency triggering to determine highway sensor data; According to the road section of the highway sensor data, the external interface of the local intelligent inspection device is imported to assist the embedded data processing component to perform regularization and packaging under data de-redundancy to determine the sensor data packet; The sensing data packet is transmitted back to the road detection system, triggering the embedded quality detection module to perform quality detection and determine a first quality detection result.

7. A method for detecting the paving quality of a highway project as claimed in claim 6, characterized in that: Perform road paving quality inspection in coordination with dynamic inspection and static inspection to determine the quality inspection results, including: Determine a second quality test result by performing self-test and self-inspection of the intelligent inspection device; The first quality detection result and the second quality detection result are integrated as a quality detection result.

8. A method for detecting the paving quality of a highway project as claimed in claim 7, characterized in that: After the first quality test result is determined, it includes: Identify the first quality inspection result and determine the need for targeted re-inspection; According to the directional re-inspection requirement, a patrol guidance instruction is generated, and the patrol guidance instruction is sent to the intelligent patrol device to drive the patrol control under directional feedback.

9. A method for detecting the paving quality of a highway project as claimed in claim 1, characterized in that: After determining the quality test results, including: identifying the engineering drawing and determining mass relaxation; Taking the quality relaxation as a constraint, determining the paving engineering defects based on the quality inspection results; An alarm is issued for defects in the paving project.

10. A method for detecting the paving quality of a highway project as claimed in claim 9, characterized in that: After the paving engineering defects are warned, the following steps are included: Determine the quality correction method, wherein the quality correction method includes the resumption of paving method and the lower-level correction method, and the lower-level correction method is the paving compensation based on the lower-level cycle nodes of the project; Receiving the alarm information, and executing any quality correction method to perform paving compensation processing on the paving engineering defects.

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