20855results about "Roads maintainence" patented technology

The invention discloses an asphalt pavement health state monitoring system and method, and belongs to the technical field of traffic infrastructure monitoring. The system comprises the following modules: a multi-source data acquisition module used for realizing real-time acquisition of pavement state parameters; the data processing module is used for performing space-time alignment, quality evaluation, exception handling and standardization on the acquired multi-source data; the multi-scale feature extraction module is used for extracting features from the microscopic diseases, the road section states and the network level, and constructing a multi-scale feature representation system; the dynamic graph analysis module is used for constructing a layered dynamic graph structure and realizing unified modeling and analysis of the road network health state; the health assessment module is used for realizing real-time assessment, deterioration trend prediction and risk early warning of the road surface health state; and the decision visualization module is used for displaying the monitoring data, the prediction result and the early warning information, and automatically generating maintenance decision suggestions based on the evaluation result.

The invention relates to the field of road compactness monitoring, in particular to a road compactness real-time regulation and control method and system based on digital twinning, and the method comprises the steps: collecting vibration acceleration, temperature and position data, and generating a time-space aligned multi-source fusion feature data set after processing; inputting a pre-trained LSTM model to construct a dynamically updated digital twinborn body, and outputting a three-dimensional compaction energy spectrum; dispersing the atlas and calculating parameters, and generating a compaction degree deviation matrix; a regulation and control instruction is generated and issued based on matrix optimization; and according to the measured data and the predicted value residual error, triggering re-optimization and calibrating the sensor. According to the method, the problems of non-uniform compaction quality and over-high energy consumption caused by poor adaptability, decision lag and error coupling of a traditional static model are solved.

The invention relates to the technical field of road surface monitoring and control, and discloses a deformation monitoring and control method and system for a road surface and a storage medium. The method comprises the following steps: carrying out multi-level sensing data acquisition on a road surface; preprocessing the data to obtain a time series data set; inputting an LSTM network to predict a deformation risk; determining a dominant factor generation grading strategy; converting the instructions into execution instructions and responding according to priorities; and constructing a knowledge graph based on feedback, modeling as a Markov process, and training a deep Q network to realize adaptive regulation and control. According to the method, accurate identification of the pavement deformation state, advanced prediction of the deformation trend, accurate analysis of the deformation reason and adaptive optimization of the control strategy are realized, so that the road maintenance efficiency is improved, the service life of the road is prolonged, and the driving safety is guaranteed.

The invention relates to a pavement structure damage detection method and device, a storage medium and electronic equipment. The method comprises the following steps: acquiring image detection data, radar detection data and sound wave detection data of a to-be-detected road surface; performing structural damage dual-channel identification on the image detection data, the radar detection data and the sound wave detection data to obtain initial structural damage detection data of the to-be-detected road surface; according to the preliminary structural damage detection data, determining physical model use guide information and physical model setting parameters corresponding to the to-be-detected road surface; and according to the physical model use guide information and the physical model setting parameters, performing mechanical analysis and fluctuation propagation analysis on the to-be-detected pavement by using each physical analysis model to obtain pavement structure damage detection data of the to-be-detected pavement. By adopting the method, the accuracy and reliability in pavement structure damage detection can be effectively improved.

The invention provides a distributed optical fiber-based soil roadbed deformation monitoring method and monitoring system, and the method comprises the steps: obtaining a distributed optical fiber sensing data set of a target soil roadbed, dividing the target soil roadbed into a plurality of monitoring regions with different deformation characteristics according to the deformation intensity distribution of an optical fiber strain data sequence, and carrying out the monitoring of the deformation of the target soil roadbed. And performing coupling analysis processing on the optical fiber strain data sequence and the temperature compensation data sequence of each monitoring area to generate a multi-dimensional deformation feature set of the monitoring area, and generating deformation early warning information of the target soil roadbed according to a space-time matching result of the multi-dimensional deformation feature set and a preset deformation threshold condition. And generating a soil roadbed deformation optimization strategy based on the deformation early warning information, and feeding back the soil roadbed deformation optimization strategy to the roadbed maintenance system to trigger reinforcement response operation. The method can effectively improve the active control capability of the health state maintenance of the soil roadbed.

A method, belonging to the field of road disease prevention technologies, for constructing a simulation model for roadbed diseases, a test method, and a system, where a simulation model for roadbed diseases is first constructed, and based on the model, an experimental method is performed to simulate diseases such as roadbed settlement, cracks, loosening, and pipeline breakage. Data of multi-sensing devices is associated with different diseases in different control groups, data statuses of various roadbed diseases in complex scenarios are acquired, and data patterns are summarized through control tests, to obtain sensor thresholds when the diseases occur in actual roadbed conditions, thereby providing a basis for road disease prevention.

The invention relates to the technical field of surface measurement, in particular to a road surface flatness rapid detection method based on a laser radar, which comprises the following steps: collecting vehicle attitude data to form a three-dimensional vector, mapping laser data to a space coordinate system, identifying a projection difference adjustment track, detecting a disturbance generation distribution area, and transversely distributing a translation direction line. Uniformly projecting to construct a reference line, extracting an echo and time index recombination time sequence segment, analyzing a point number trend to screen a stable segment, and extracting symmetric points to compare an included angle to generate a closed zone. According to the method, the attitude vectors of the vehicle in rolling, pitching and yawing states are obtained, the laser echo distance measurement data are mapped to the absolute space coordinate system, and the included angle difference between the distance measurement direction and the ground direction is accurately calculated, so that the space matching precision of a measurement path is remarkably improved, and a longitudinal section analysis result is closer to a real road state; and the space integrity, the track smoothness and the section structure rationality of the whole measurement process are comprehensively optimized.

The present invention relates to the technical field of flatness detection devices, and in particular to a road flatness detection device and detection method. Its technical solution includes: a frame and an extension frame slidably mounted on the frame, the frame and the extension frame constitute a vehicle frame, and also includes: a roadblock shielding component mounted on the vehicle frame, when the wheel assembly component contacts the concave and convex surface and drives the vehicle frame to tilt, the roadblock shielding component drives the detection component to move in the opposite direction of the tilting direction, and controls the ground clearance of the detection component to always remain equal. The present invention uses the roadblock shielding component to move the measuring wheel located in the middle of the frame downward when one end of the frame rotates, and the downward movement distance is half of the rising height of the rising end of the frame, which can avoid the influence of the rising or falling end of the frame on the measuring wheel, and thus can effectively improve the accuracy of the measuring wheel when measuring irregular roads, and can effectively improve the accuracy of calculating the road surface flatness data.

The invention provides a hot in-place recycling asphalt mixture and a construction method, and relates to the technical field of asphalt mixtures, and the hot in-place recycling asphalt mixture is obtained by recycling old asphalt pavement materials in a high proportion, reducing new material consumption and carbon emission, realizing resource recycling and green construction and introducing a regenerant to recover the performance of aged asphalt. The high-temperature rut resistance, the low-temperature crack resistance, the fatigue resistance and the interface bonding strength of the mixture are synergistically improved by matching with the styrene butadiene rubber modifier, the basalt fiber, the nano silicon dioxide and other functional materials, and the mixture is ensured to be uniform and free of segregation through precise feeding sequence, high-pressure atomization spraying and forced stirring parameter control. The defects of gray materials, oil balls and the like are avoided, the compactness, the flatness and the overall structure stability of the regenerated pavement are improved, and the problems of performance degradation and insufficient durability of a traditional regenerated mixture are solved.

The invention provides a Transform and CNN fused crack detection and structure evaluation system and method. The system comprises an image preprocessing module, a crack feature extraction module, a crack positioning and classification module, a crack boundary refinement module and a structure integrity evaluation module. Through combination of the CNN and the Vision Transform, local and global features in the image can be extracted at the same time, and the precision of crack detection is enhanced. The dynamic attention mechanism is used for refining fracture boundaries and improving fracture positioning and recognition effects. And the structure health assessment module combines crack information and structure stress analysis, performs structure risk assessment by using a support vector machine or a random forest, and outputs a structure health state and a repair suggestion. The invention further provides an evaluation scheme of the system. The method improves the precision and robustness of crack detection, has higher multi-scale detection capability, noise robustness and real-time performance, and is suitable for automatic monitoring and health management of civil infrastructures.

The invention discloses a backfill soil foundation compaction quality on-site detection method and system. The method comprises the steps that instantaneous acceleration signals of a vibrating wheel in the soil compaction construction process are collected in real time through a three-axis acceleration sensor; the acceleration signal comprises a three-axis acceleration component; recording the number of construction times through construction equipment, collecting position information of a construction area by using a GPS (Global Positioning System), and synchronously binding the acceleration signal with the number of construction times and the position information through timestamps to form a data set corresponding to the position of the construction area; performing spectral analysis on the acceleration signal in the data set, and extracting a dominant frequency amplitude and a first harmonic amplitude to generate a filtered acceleration signal; the filtered acceleration signals are input into a training single-hidden-layer BP neural network, and the soil dry density is calculated in combination with the number of construction times; based on the ratio of the calculated soil dry density to the standard maximum dry density, the soil compactness in the construction area is determined in combination with the position information, and a construction area compactness distribution diagram is generated through the upper computer to optimize the construction strategy.

The invention relates to the technical field of measurement and monitoring of road engineering variables, in particular to an asphalt pavement paving quality management system, which comprises a data acquisition module configured to acquire real-time meteorological data, mixture temperature parameters and pavement quality monitoring data; the viscosity analysis module is used for determining the dynamic viscosity adjustment range of the asphalt material based on the real-time meteorological data and the temperature parameters of the mixture; the temperature control module is used for regulating and controlling the mixing temperature according to the viscosity change of the asphalt material and generating a target paving temperature curve; the power optimization module is used for matching a dynamic adjustment strategy of the heating power of the screed of the paver based on the target paving temperature curve; by means of the system, meteorological and construction data are monitored in real time, parameters such as asphalt viscosity and screed power are dynamically regulated and controlled, closed-loop optimization is achieved, the paving quality is improved, and intelligent construction is achieved.

Disclosed are various embodiments for a sensor enabled geogrid for the monitoring and detection of subgrade deformation in infrastructure such as roadways, railways, working platforms, and marine applications. The system and methods contain a sensor enabled geogrid, inertial measurement units (IMUs), one or more sensors, a data collection apparatus such as a sensor pod, an information transmission apparatus such as a gateway device, a communications network, and a computing device capable of performing analytics on information from the IMU's and other sensors. The disclosure further includes methods of processing information received from a sensor enabled geogrid by a sensor pod. In the example, the sensor pod transmits received information to a gateway device for transmitting to a backend computing system. The backend computing system then performs an analysis on the information to determine variance from an initial sensor position, and alerts of possible infrastructure failure.

The invention belongs to the technical field of road paving, and particularly relates to a road paving system based on a multi-head self-attention mechanism, which comprises a compaction robot, a paving robot, a multi-modal data sensing layer, an AI dynamic decision core and intelligent execution equipment, the AI dynamic decision core fuses construction time sequence data and a spatial topological relation through a space-time diagram neural network to realize construction progress prediction and multi-device cooperative control, and the intelligent execution device comprises a self-adaptive screed control unit, a dynamic material distribution system, a compaction robot cluster and a non-uniform material compensation control device. According to the method, autonomous optimization and dynamic correction of the whole process of paving, compacting and detecting can be achieved, manual intervention is reduced, the intelligent level is high, the flatness control precision can be improved, the construction efficiency can be improved, material waste can be reduced, and the engineering cost can be reduced.

Methods, apparatus, and storage medium for providing real-time asphalt density and / or moisture content prediction with ground penetrating radar. A method includes using raw data from a ground penetrating radar sensing an asphalt concrete at a location; processing the raw data to obtain processed data; determining an asphalt density of the asphalt concrete at the location based on the processed data according to an asphalt density prediction model; determining a compaction status of the asphalt concrete at the location based on the asphalt density and a target compaction threshold; and outputting the compaction status of the asphalt concrete at the location to an operator for determining whether to continue or stop compacting the asphalt concrete at the location. In another method, moisture content for cold recycling and existing asphalt concrete pavement is predicted in real-time from using raw from data of ground penetrating radar mounted on a vehicle.

The invention belongs to the technical field of pavement construction detection, and provides a municipal road asphalt concrete pavement construction detection method, which comprises the following steps: S1, installing a plurality of optical sensing devices, and collecting pavement images and spectral data in real time; s2, carrying out fusion processing on the collected data; s3, processing the three-dimensional data to generate a three-dimensional model of the road surface; s4, analyzing the image data, automatically identifying pavement defects and evaluating the severity of the pavement defects; s5, performing spectral analysis and fusing data to assist in judging the quality and uniformity of the material; s6, comparing a detection result with a design standard, and generating a construction quality evaluation report; according to the invention, construction detection is carried out by comprehensively applying an optical sensing technology and a data processing algorithm, the efficiency and quality of construction monitoring are improved, the maintenance cost is reduced, and the safety and durability of a road are guaranteed.

The invention relates to a roadbed compaction quality detection method and system based on multi-dimensional data, and the method comprises the steps: obtaining sensor data of a roller of a road roller in real time, and obtaining pavement images and positioning data of a plurality of continuous time points; when the road surface is flattened, the roadbed structure is gradually stable, so that the corresponding pressure data and vibration data are gradually stable. By analyzing the stability of the pressure data and the vibration data, the stability of the pressure data and the vibration data is determined. According to the method, vibration data, stable data and temperature data of a road section at a stable time point are extracted, and then a target data reference range corresponding to a corresponding temperature grade and a roadbed material is found from a pre-constructed data model, so that the target data reference range can verify the vibration data and the stable data at the stable time point; therefore, whether the road roller performs the road rolling operation in a reasonable range or not is judged. In addition, the road surface is detected by using the road surface image.

The invention relates to the field of sampling, in particular to a drilling and sampling device for road construction. The sampler comprises a frame and a sampling assembly arranged on the frame, the sampling assembly comprises a drilling cylinder and an inner cylinder, a plurality of drilling tools are hinged to the lower end of the drilling cylinder, the inner cylinder is coaxially inserted into the drilling cylinder, the inner cylinder is of a grating structure and comprises a first cylinder body and a second cylinder body, and a film is arranged in the inner cylinder. When a road surface part is drilled, the drilling tool is in a horizontal state, the contact area between the drilling tool and the road surface is large, large cutting supporting force can be kept, a drilling barrel is prevented from being stressed and deformed, when a roadbed part is drilled, the drilling tool is in an upright state, the contact area between the drilling tool and the roadbed is small, the cutting speed is increased, and the cutting efficiency is improved, so that different drilling requirements are met; meanwhile, when the roadbed part is cut, the inner cylinder is inserted into the roadbed in advance to support the roadbed, after drilling is finished, the thin film is pulled open to wrap the sample core, it is guaranteed that the distribution state of all layers of structures of the sample core is accurate, and the authenticity of the sample is guaranteed.

The present invention relates to a mobile line marking robot with visual odometry, making it less susceptible to poor GNSS signals.

An apparatus for screeding concrete to produce a level finished surface includes a frame assembly having a front end and rear ends and a pair of spaced vertically oriented stabilization legs supporting a generally horizontal front member. An extendable boom assembly is provided having front and rear ends, and an exterior boom section pivotably secured to the frame assembly proximate said rear end. The extendable boom assembly is also adjustably mounted on said front member to allow generally lateral motion of the boom.

The invention relates to the field of highway construction, in particular to an intelligent asphalt pavement rolling control method and system, and the method comprises the steps: deploying machine vision equipment to collect an image of a just-paved asphalt mixture, recognizing the segregation degree in combination with a convolutional neural network, and generating a segregation distribution thermodynamic diagram with geographic coordinates; the road roller is integrated with a positioning sensor, a temperature sensor, a vibration sensor and a speed sensor, relevant parameters are collected, and the real-time compaction degree is calculated. The thermodynamic diagram and the compaction degree are subjected to space-time matching, optimal operation parameters are calculated through a dynamic coupling model on the basis of data such as the segregation degree and the temperature of a target area, the optimal operation parameters are wirelessly sent to a road roller control system to adjust speed and vibration parameters, and a road roller feeds back the new compaction degree after execution to form closed-loop control. The problem that separation and compaction control are disjointed in the prior art is solved, separation information and the compaction process are deeply fused, and underpressure of a separation area and overpressure of a uniform area are avoided.

The invention provides an asphalt pavement compactness detection method based on partial least squares regression, which comprises the following steps: acquiring a rolling acceleration signal of a vibratory roller to obtain an equifrequency component, and calculating a corresponding compactness value CMV; temperature data T of the asphalt pavement are collected, and the actual asphalt pavement temperature is obtained through calculation; positioning data of the vibratory roller are collected, and the rolling speed V of the roller is calculated; the method comprises the following steps: performing interpolation on a CMV calculation abnormal point caused by the change of the working state of a road roller, and estimating an actual CMV value of the CMV abnormal point by calculating an average value of a plurality of known CMV values near a target point by adopting a moving average method based on the integrity of an asphalt pavement; and carrying out partial least square regression on the equifrequency component, CMV, T and V variables. The method is a nondestructive testing method, comprehensive and accurate compaction degree evaluation is provided, the compaction state of the asphalt pavement is sensed in advance, and compaction degree detection errors caused by change of the working state of a road roller are eliminated.

The invention discloses an automatic lineation method, device and equipment for a lineation robot and a storage medium. The method comprises the steps that first position information of the lineation robot is obtained in real time based on a global satellite navigation system; acquiring a road image in front of the marking robot, and analyzing the road image to obtain second position information of the marking robot relative to the road center point; combining the first position information and the second position information to confirm the accurate position of the scribing robot; and controlling the marking robot to automatically travel based on the accurate position and the preset planned path, and executing road marking operation. According to the invention, the position of the marking robot in the road is accurately positioned through the positioning information of the global satellite navigation system and the acquired road image in front of the marking robot, and then the marking robot is controlled to automatically advance according to the preset planned path and execute the marking operation according to the accurate positioning, so that the marking operation can be accurately completed; and the manpower consumption is reduced.

The invention relates to the technical field of road detection and measurement, and discloses a full-scale pavement three-dimensional contour accurate scanning and measuring system, which comprises a multi-mode laser scanning subsystem used for acquiring pavement three-dimensional point cloud data in a full-scale range, and the subsystem comprises a dual-wavelength laser and an optical coherence tomography module, the road surface height information is acquired through the two-wavelength interference signals; the data processing module comprises a denoising unit and a point cloud data reconstruction unit; the surface reconstruction module is used for generating a three-dimensional pavement contour for the point cloud data based on a gradient diffusion model, and enhancing pavement edge features by controlling a gradient threshold; and the feature extraction module is used for extracting crack feature parameters based on the fractal geometric model. By adopting the technical scheme of combining a dual-wavelength laser scanning technology with optical coherence tomography, high-precision acquisition of road height information is realized, and the technical bottleneck of insufficient measurement precision in a complex road environment is solved through precise calculation of interference signal phase difference.

The invention relates to the technical field of road engineering and artificial intelligence, and discloses a traffic road disease detection system and method based on a cloud edge-end architecture, and the system comprises: 1, a vehicle-mounted multi-mode optical sensing terminal which is used for synchronously collecting pavement images, spectrums and three-dimensional data; the vehicle-mounted edge calculation unit is used for constructing a digital twin baseline of the road surface grid unit and executing unique double-path parallel analysis, on one hand, the health degree attenuation degree of the current state compared with the baseline is quantified, and on the other hand, whether the change is caused by a natural disease or a manual maintenance event is judged through a feature signature recognition engine; and the cloud management platform is used for storing historical health degree data and predicting a future attenuation trend through a time sequence model. According to the method, the problems that early compound diseases are difficult to recognize and the maintenance behavior is easily misreported as the pain point of the diseases in the prior art are solved, the crossing from passive detection to active prediction is realized, and the accuracy of road detection and the scientificity of maintenance decision are remarkably improved.

The invention belongs to the technical field of road surface detection, and particularly relates to an anti-freezing road surface flatness detection device which comprises a detection frame and a PLC installed on the inner wall of the lower side of the detection frame, and the left side wall of the detection frame is fixedly connected with a display control box. Before the flatness of the anti-freezing pavement with the embossed surface is detected, the pavement embossed surface is firstly measured and analyzed in detail, the bumping degree caused by the embossed surface is detected, and then the bumping caused by the embossed surface is compensated, so that accurate flatness data can be obtained in the subsequent measurement process; according to the anti-freezing pavement embossing detection device, the abrasion degree of pavement embossing can be automatically detected while the flatness of an anti-freezing pavement is detected, and when it is detected that the embossing is seriously abraded, an operator can be timely reminded of the situation, follow-up repairing by the operator is facilitated, and the friction force of the anti-freezing pavement is guaranteed.

A connecting mechanism is installed on the rear portion of a machine frame and used for being connected with a flat-bed trailer for loading a prefabricated track plate and driving the machine frame and the flat-bed trailer to move synchronously, a horizontal guide rail is horizontally arranged in the advancing direction of the machine frame, and a walking mechanism is installed on the horizontal guide rail and can move in a reciprocating mode along the horizontal guide rail. The lifting tool module is mounted on the walking mechanism, can do lifting motion and transverse rotation relative to the walking mechanism, can penetrate through the rack under the driving of the walking mechanism to lift the prefabricated track plate from the flat-bed trailer, and releases the lifted prefabricated track plate to the position over the pavement to be paved; according to the intelligent laying machine for the prefabricated road plate, the flat-bed trailer loaded with the prefabricated road plate is driven by the driving mechanism to move synchronously with the rack, the prefabricated road plate on the flat-bed trailer is lifted to the position over a road surface to be laid through the lifting tool module to be released, and the lifting tool module has the multiple functions of intelligent leveling, locking, vibrating, lifting and the like; therefore, the requirement for efficient laying of the prefabricated road plate is met, and high-quality intelligent operation is achieved.

The invention discloses a road roller intelligent control method based on a road surface compaction quality real-time state, an upper computer mainly judges compaction states and quality such as compaction degree, strength and modulus in a road surface compaction process in different rolling stages in situ through an in-situ detection vehicle, and a lower computer mainly aims at parameters fed back by the in-situ detection vehicle. According to the method, road surface compaction states and rolling process models in different rolling stages are learned and predicted, target function optimization considering the compaction degree, strength, modulus and the like is obtained, and the vibration frequency, amplitude, running speed, rolling times and the like of the road roller are adjusted in time, so that accurate regulation and control of the road surface compaction quality in different rolling stages are achieved. On the basis of comprehensively detecting the compaction quality of the asphalt pavement, automatic optimization of a rolling process considering target functions such as the compaction degree, the strength and the modulus can be completed, and the method has the advantages that pressing, detection and adjustment are carried out simultaneously, and the method is accurate and reliable.

A slip form paving machine includes a machine frame (10), a plurality of ground engaging wheels or tracks (30,30F,30R) and front and rear height adjustable lifting columns (32,32F,32R) supporting the machine frame from the ground engaging wheels or tracks, the lifting columns being adjustable to adjust a longitudinal inclination of the machine frame in a paving direction (12). A slip form mold (24) is supported from the machine frame for molding a mass of concrete (16A) into a formed not yet hardened concrete slab as the paving machine moves forward in the paving direction. A swelling sensor (220) is arranged to detect a swelling of the formed not yet hardened concrete slab relative to the machine frame behind the slip form mold. A method of controlling the slip form paving machine is also disclosed.

The invention relates to the technical field of road surface detection, and particularly discloses a road surface water seepage detection device for road construction, which comprises a measuring cylinder, a first valve, a second valve, a base, a rotating assembly and a supporting seat, the bottom side of the measuring cylinder is provided with a water outlet, and the bottom side of the base is provided with a groove; a first mounting hole and a second mounting hole which are communicated with the groove are formed in the top side of the base, the first mounting hole is communicated with one port of the first valve, the other port of the first valve is communicated with a water outlet of the measuring cylinder, and the second mounting hole is communicated with one port of the second valve; according to the road surface water seepage detection device for road construction, liquid paraffin is adopted for blocking a road surface outside the water seepage range, operation is easy, time is short, and meanwhile the influence of road surface runoff on water seepage detection is reduced.