2468results about "Elasticity measurement" patented technology

The invention discloses a bridge detection method and system based on a digital twin technology, and relates to the field of bridge structure health monitoring. The method comprises the following steps: acquiring a strain distribution value, a vibration spectrum value and an environmental load spectrum value in real time through a sensor network deployed in a physical bridge, generating a structural response data set, and synchronizing the structural response data set to a digital twinborn body; calculating a damage index value and an accumulated damage quantity value based on the structural response data set; inputting the damage index value and the accumulated damage quantity value into a preset safety criterion, and calculating a safety margin coefficient value and a failure risk grade value; calculating a residual life prediction value based on the safety margin coefficient value and the environmental load spectrum value, and synchronously correcting a degradation rate value of the digital twin; and generating a priority maintenance instruction according to the failure risk grade value, the residual life prediction value and the safety margin coefficient value, and feeding back maintenance effect data to the digital twinborn body to complete updating after execution. The bridge operation and maintenance efficiency and safety are remarkably improved.

A structural-health-monitoring system is disclosed for real-time detection and autonomous maintenance of physical structures. The system includes a sensor network comprising at least one strain gauge and one tri-axial accelerometer mounted on the structure to generate real-time sensor signals. A perception module filters and normalizes the signals and extracts numerical features such as peak amplitude and dominant frequency. A digital-twin module maintains a finite-element model updated in response to the extracted features. A data-driven surrogate model predicts sensor behavior and refines itself using machine-learning techniques. An anomaly-detection module computes an anomaly score from model residuals or classifier outputs. Upon exceeding a threshold, a maintenance module initiates a maintenance action, including generating an inspection schedule or issuing a control signal to an autonomous inspection or repair device. A learning module continuously improves system performance using reinforcement learning based on historical outcomes. The system supports predictive diagnostics, robotic repair, and automated optimization for long-term structural integrity.

The invention discloses a bridge health prediction device based on a Beidou system and a monitoring analysis method, and relates to the field of bridge health monitoring. The method comprises the following steps: S1, deploying monitoring points at key structure nodes of a bridge, and collecting three-dimensional position information and multi-source data by using a Beidou system and a multi-type sensor; s2, constructing a time-varying displacement field and a continuous deformation tensor, fusing stress and strain to construct a structural fatigue factor, and introducing environmental disturbance to realize dynamic correction of the fatigue factor; s3, a health state function is constructed based on the stress response, the displacement gradient and the deformation tensor, a damage mapping function is constructed in combination with accumulated deformation and a historical threshold value, and a damage thermodynamic diagram is generated; and S4, finally fusing fatigue, health and damage indexes to evaluate bridge risks, and performing dynamic early warning. Through fusion of mechanical tensor features and environmental disturbance modeling, a multi-index linkage fatigue and damage assessment mechanism is constructed, and the precision, robustness and global perception ability of bridge health monitoring are improved.

A method for testing and evaluating lateral stiffness of small box girder bridges is provided. The method includes the following steps: a deflection sensor collects a deflection value of a measuring point based on a loading process of a loading vehicle; based on the deflection value of the measuring point and an information matrix of the loading vehicle, an influence line of longitudinal bridge deflection of each measuring point is obtained; based on the influence line of longitudinal bridge deflection, the influence line of lateral bridge deflection of small box girder bridge is obtained by interpolation method; and based on the influence line of lateral deflection of small box girder bridge, a stiffness evaluation result is obtained.

The invention belongs to the technical field of plate spring performance analysis and evaluation, and discloses a high-strength two-stage gradual-change-stiffness plate spring performance analysis and evaluation system and method.The method comprises the steps that plate spring initial mechanical data collection and heterogeneous load response integrated processing are conducted on the basis of a multi-dimensional vehicle-mounted test experiment, and plate spring integrated mechanical response data are generated; performing double-rigidity gradient recognition analysis to generate rigidity transformation critical data; performing critical region stress field deconstruction analysis to generate stress field distribution characteristic data; carrying out local microstructure change characterization to generate structural deformation data; constructing a multi-scale stress transfer link, and generating critical region stress transfer path data; performing fatigue damage accumulative mapping to generate accumulative feature data; constructing a fatigue life prediction model, and generating life prediction data; carrying out comprehensive performance index quantitative evaluation to generate a performance evaluation result; executing plate spring optimization improvement scheme generation and verification; and a scientific basis is provided for performance optimization of the two-stage gradual-change-rigidity plate spring.

A system, apparatus and method directed to detecting damage to an optical fiber of a medical device. The optical fiber includes one or more core fibers each including a plurality of sensors configured to (i) reflect a light signal based on received incident light, and (ii) alter the reflected light signal for use in determining a physical state of the multi-core optical fiber. The system also includes a console having non-transitory computer-readable medium storing logic that, when executed, causes operations of providing a broadband incident light signal to the multi-core optical fiber, receiving reflected light signals, receiving reflected light signals of different spectral widths of the broadband incident light by one or more of the plurality of sensors, identifying at least one unexpected spectral width or a lack of an expected spectral width, and determining the damage has occurred to the optical fiber based on the identification.

The invention discloses a whole-span bridge hoisting construction method. The method comprises the steps that prefabricated bridge components are transported to a construction site; in the construction preparation stage, a foundation monitoring mechanical model of a construction site is built, and the optimal position and operation parameters of a crane are determined; before hoisting, a laser emitting device is installed on a bridge component, a laser receiving device is installed at the front end of a crane suspension arm, and a plurality of laser reflection targets are arranged on the periphery of a preset installation position of a pier; in the lifting and translation processes, the laser positioning system monitors the spatial position and attitude information of the bridge component and the suspension arm in real time, and transmits the data to the control center in real time; and the control center compares the actual position deviation with the target position deviation in real time according to the preset hoisting path and the in-position precision requirement, and when the deviation exceeds the threshold value range, a control instruction is sent to a power system and a hydraulic control system of the crane. According to the method, the position and posture of the bridge component can be accurately monitored in real time, the action of the crane is timely and accurately regulated and controlled according to the deviation, and the construction precision and safety are improved.

A system for providing an interactive inspection map of an inspection surface inspected by an inspection robot includes an inspection circuit structured to interpret inspection data of the inspection surface from the inspection robot and a user interaction circuit structured to interpret a user focus value from a user device. The user focus value includes an activation state value. The system further includes an inspection visualization circuit structured to provide the interactive inspection map to the user device in response to the user focus value. The interactive inspection map is based on the inspection data. Also, the system includes an inspection data validation circuit that determines an inspection data validity description of the inspection data. The inspection data validity description is provided as a display layer on the interactive inspection map to indicate whether the inspection data is valid.

The invention discloses a mechanical property testing method for an inflatable wing, and belongs to the technical field of aerospace testing. The method comprises the following steps: S1, wing installation: clamping an inflatable wing on a test board, and enabling a chord plane of the inflatable wing to be perpendicular to a loading direction; s2, applying a load: driving a loading mechanism to apply a vertical load to the inflatable wing through an external universal tester; s3, data acquisition: synchronously acquiring a deflection curve and stress distribution data by using a displacement measurement unit and a strain detection unit; and S4, failure judgment: when monitoring that the shape of the deflection curve suddenly changes or the strain data exceeds a threshold value, judging that the inflatable wing is subjected to buckling failure, stopping loading and recording the maximum load. The test bench serves as an expansion platform of a universal tester, can be adapted to a large-size inflatable wing, does not need special equipment, reduces the cost, realizes cooperative monitoring of displacement and strain data, realizes closed-loop control of inflation air pressure-deformation-load, and remarkably improves the test precision and the data reliability.

The invention relates to a bridge modal parameter automatic identification method and system considering multi-channel information, and the method comprises the following steps: S1, directly analyzing a multi-channel monitoring signal through COV-SSI, generating a stability diagram, and automatically extracting a stability axis in combination with a DBSCAN clustering algorithm, thereby achieving the automatic identification of a modal frequency; s2, performing signal decomposition on the multi-channel monitoring data by adopting MvFIF to generate an intrinsic mode function (IMF) group with a mode alignment characteristic; s3, the instantaneous frequency and bandwidth of the IMF in the step S2 are calculated through HHT, IMF components containing target modal frequency are screened out, and linear reconstruction is carried out; s4, taking the multi-channel monitoring data reconstructed in the step S3 as system input of a COV-SSI algorithm, calculating a system matrix and an output matrix, and calculating a modal damping ratio by utilizing eigenvalue decomposition; according to the method, the spatial-temporal correlation among multi-channel data can be considered, and synchronous decomposition of multi-channel monitoring data is realized; and automatic and accurate identification of the structural modal parameters under different noise levels can be realized.

The invention relates to the technical field of bumper detection, in particular to an automobile bumper detection method and system, and the system comprises a rigid test bench, a multi-point adjustable impact loading module, a bumper surface deformation monitoring module, and a control and processing module. The to-be-tested automobile bumper is fixed on the test bench according to a preset mode, and the plurality of sensors are arranged based on a preset position; carrying out dynamic and static balance test on the to-be-tested automobile bumper according to the received control instruction, and carrying out corresponding index calculation; on the basis of static and dynamic test indexes, a quantitative report is generated, whether the balance of the bumper structure reaches the standard or not is automatically judged, complex static supporting and dynamic impact working conditions possibly encountered by the bumper on a vehicle can be effectively simulated in an integrated process, the static stability of the overall structure and the coordination under power impact of the bumper can be quantitatively evaluated, and the reliability of the bumper structure is improved. Therefore, the structural safety performance of the bumper can be reflected more truly.

The invention provides a municipal bridge damage defect detection method and a municipal bridge damage defect detection system, which are used for solving the problem that the quality and the accuracy of acquired data are difficult to guarantee due to the fact that vibration signals are easily interfered by environmental noise, such as vehicle load, wind load and the like. A bridge key part vibration signal data set is obtained, and a final damage area range is determined based on the vibration signal data set; whether the bridge is damaged or not is judged based on recognition of the vibration signals, so that the signal-to-noise ratio of monitoring data and the damage positioning precision are improved, a more accurate and reliable decision basis is provided for a bridge management department, and finally maintenance and reinforcement work of the bridge is effectively guided.

The invention relates to the field of bridge engineering, in particular to a bridge structure toughness dynamic evaluation method and system based on digital twinning, and the system firstly collects the environment, geometry and performance information of a bridge, and then establishes an accurate bridge digital twinning model; a bridge structure toughness prediction model is systematically constructed by using a space-time diagram convolutional network, and the performance degradation process of a bridge in extreme weather can be predicted; meanwhile, toughness evaluation indexes are formulated by the system, and accurate performance evaluation of real-time monitoring data is realized; through multi-source data fusion, the system improves the comprehensiveness and accuracy of data acquisition; the prediction model based on the space-time diagram convolutional network significantly improves the accuracy of performance degradation prediction; a scientific and efficient tool is provided for bridge maintenance and management, and safe operation of the bridge in extreme weather is effectively guaranteed.

The invention discloses a bridge dynamic deflection and dynamic strain data fusion method, and belongs to a bridge structure health monitoring technology. According to the method, deflection measuring points and strain measuring points are deployed at the bottom of a bridge according to rectangular grids established in the longitudinal and transverse directions; and then taking the span trend of the bridge as a longitudinal direction, taking a bridge cross section perpendicular to the span trend of the bridge as a position reference of a data fusion point, and determining the data fusion point based on the bridge cross section to realize fusion and mutual conversion of the strain data and the deflection data. Through data fusion, the dynamic deflection sudden change and the dynamic strain hysteresis effect are effectively associated, the structure damage feature omission ratio is remarkably reduced, and meanwhile early warning of micro damage is supported.

A computer implemented method for on-line monitoring a structure, the method comprising: receiving (151) at least dynamics data (204) of dynamic variables representing a dynamic response of the structure from a plurality of sensors (10), the dynamic response of the structure being generated when the structure has been subjected to an excitation; detecting an impulse (152) created by said excitation by identifying a free load response (208) of the structure from said at least dynamic data (204); obtaining (153) a set of poles (210) comprising pairs of a natural frequency and a damping factor of the structure from the free load response (208); generating (154), using a non-supervised machine learning algorithm, a probability-based baseline model for the structure using a plurality of said poles (210) obtained along a certain period of time, the probability-based baseline model associating in a probabilistic way the dynamic variables affecting the structure and providing a plurality of baseline parameters (214); every time a new impulse is detected and a new set of poles (211) are obtained from the free load response of said impulse, feeding (155) the new set of poles (211) to a concept drift algorithm to obtain a KPI (217) of the structure.

A hydraulic mechanical component strength testing apparatus and a testing method, relating to the technical field of mechanical component strength testing, for use in performing strength testing on mechanical components with different temperatures. The testing apparatus comprises a frame and a clamping assembly; the clamping assembly comprises two clamping plates and a clamping drive mechanism; a vertically-arranged hydraulic rod is arranged at the top of the frame; a placement platform fixedly connected to the bottom of the frame is arranged below the hydraulic rod; the two clamping plates are located above the placement platform; a placement seat for supporting a mechanical component is arranged between the two clamping plates; a hydraulic sensor for measuring the pressure borne by the placement seat is arranged between the placement seat and the placement platform; the placement platform is further provided with a display in signal connection with the hydraulic sensor; and the clamping plates are each provided with a heating assembly used for heating the mechanical component. The present invention can perform strength testing on mechanical components with different temperatures.

A bridge health state monitoring apparatus, which relates to the field of bridge monitoring. The bridge health state monitoring apparatus comprises: a data collection unit (1), a positioning antenna (2), an industrial switch (4), an intelligent video analysis unit (5), a vibration sensor (6) and a central platform (9). The data collection unit (1) is used for collecting information of a vehicle passing through a bridge, in order to obtain a video bitstream, and sending the video bitstream to the intelligent video analysis unit (5); the positioning antenna (2) is used for receiving position information provided by a satellite to locate the position of a bridge section and the position of the data collection unit (1); the vibration sensor (6) is used for detecting a vibration signal generated when the vehicle passes through the bridge section, and sending the vibration signal to the intelligent video analysis unit (5); the intelligent video analysis unit (5) is used for parsing the video bitstream and the vibration signal, and sending the parsed video bitstream and the parsed vibration signal to the central platform (9); and the central platform (9) is used for receiving, storing and presenting vibration data information of each section of the bridge, and is further used for storing the video bitstream. The bridge health state monitoring apparatus can accurately reflect the health state of bridges. Further provided is a bridge health state monitoring method.

Disclosed in the present invention are a method and system for determining reasonable vertical stiffness of a long-span new highway bridge. The method comprises: by means of a finite element model for an initial design scheme of a long-span new highway bridge, calculating a vertical deflection-to-span ratio and a beam end vertical rotation angle of the bridge under the characteristic combination of a permanent load, a live load, a temperature action, and a wind load; performing checking calculation on indicators for driving safety and comfort on the bridge, indicators for the usage of a beam end bearing and an expansion joint, and indicators for a vertical curve of a route after vertical deformation of a main girder; taking the requirements for the driving safety and comfort on the bridge, the requirements for the usage of the beam end bearing and the expansion joint, and the requirements for the vertical curve of the route after the vertical deformation of the main girder as constraints to decrease or increase bridge design parameters in the finite element model; and determining, as the minimum value of the reasonable vertical stiffness of the bridge, the maximum vertical deflection-to-span ratio and the maximum beam end vertical rotation angle in all schemes satisfying the constraints. The present invention can provide a reliable reference for the reasonable design, economy, and safety of long-span new highway bridges.

The invention relates to the technical field of bridge engineering detection, in particular to a distributed optical fiber strain sensing detection system for a bridge engineering dynamic and static load test, and the system comprises a distributed optical fiber strain sensing module which is used for obtaining the strain information of different positions of a bridge; the dynamic and static load signal acquisition and conversion module is used for converting the strain signal into a strain electric signal suitable for transmission and processing; the temperature compensation module is used for carrying out temperature compensation on the strain signal according to the change of the collected environment temperature; the data processing and analyzing module is used for processing and analyzing the strain electric signal subjected to temperature compensation so as to obtain the strain distribution condition and related parameters of the bridge structure under the action of dynamic and static loads; and the monitoring and early warning module is used for monitoring the state of the bridge in real time according to the result obtained by the data processing and analyzing module and sending out an early warning signal when the strain of the bridge is abnormal. The problem that in the prior art, comprehensive, high-precision and real-time dynamic and static load strain monitoring cannot be carried out on bridge engineering is solved.

System and method for monitoring vehicular traffic on a bridge, including receiving digital data representing the response of the bridge to a traffic event, where the digital data has been collected during the traffic event, from displacement sensors and accelerometers mounted on the superstructure of the bridge, wherein the digital data from the displacement sensors embody bending responses of the bridge, the digital data from the accelerometers embody acceleration responses of the bridge, and the digital data from the sensor are synchronised in the same time space, providing a parametric model which uses modal parameters to simulate generalized boundary conditions and two-dimensional behaviour of the bridge; using the parametric model to process the digital data to solve for deformation of the bridge and characteristics of the vehicle traffic, and generating an output that describes the deformation of the bridge and characteristics of the vehicle traffic.

The invention relates to a fault diagnosis system and method based on expansion joint voiceprint and vibration, and the system comprises a sensor which is disposed at a bridge expansion joint and is used for obtaining a sound signal and a vibration signal when a vehicle passes through the bridge expansion joint; the gateway is used for judging whether the vehicle passes through the bridge expansion joint based on the vibration signal; extracting time-domain features and frequency-domain features of sound signals and time-domain features and frequency-domain features of vibration signals when a vehicle passes through the bridge expansion joint; and according to the time domain feature and the frequency domain feature of the sound signal and the time domain feature and the frequency domain feature of the vibration signal, judging whether the bridge expansion joint has a fault or not. According to the invention, the method reduces the cost of manual inspection of the expansion joint through the sum judgment of the sound signal and the vibration signal of the vehicle passing through the bridge expansion joint, and improves the automation degree and accuracy of fault judgment.

A system for identifying a failure of the primary load path in an actuator. The actuator includes a screw shaft and a nut assembly moveable along the screw shaft. The nut assembly comprises a primary nut for transmitting load through the actuator along a primary load path, and a secondary nut for transmitting load through the actuator along a secondary load path. The nut assembly is configured such that, in normal operation, the secondary nut is not engaged with the screw shaft and load is transmitted through the actuator along the primary load path, and such that, upon failure of the primary load path, the secondary nut is configured to engage the screw shaft and transmit load through the actuator along the secondary load path. The system includes a strain gauge configured to be mounted to the actuator and to measure vibrations of the actuator.

The invention provides a bridge fracture monitoring method and system based on distributed optical fibers, and relates to the technical field of bridge monitoring, and the method comprises the steps: firstly constructing a stress response association mapping table of the distributed optical fibers and a bridge structure, and recording the information of a layout position, a sensing range parameter, a response sensitivity curve and the like; then, dynamically adjusting the acquisition frequency based on the stress response association mapping table, generating a strain and environment association data set with an acquisition frequency identifier, performing environment interference stripping processing on the strain and environment association data set, and forming a space strain deviation feature set after environment correction; the spatial strain deviation feature set and a time dimension strain data change trend are subjected to correlation modeling, a response sensitivity curve is combined to generate a space-time strain evolution feature with a sensitivity weight, an abnormal evolution section is marked through a multi-fiber cooperative verification mechanism, and a bridge fracture monitoring result containing a verification result is generated. Therefore, the bridge fracture condition can be accurately and comprehensively monitored.

The invention relates to the technical field of bearing rigidity detection, and discloses a bearing rigidity testing device, which comprises a fixed seat sleeve, the driving part is used for providing rotation power for the to-be-tested bearing; a twisting assembly; the detection assembly is used for detecting the rigidity change of the bearing under the condition that the bearing bears constant pressure in multiple directions; and the driving piece is connected with the bearing through a twisting assembly. According to the bearing rigidity testing device, certain pressure can be applied to multi-directional positions of the bearing through the arranged detection assembly, large-range wrapping and pressing on the bearing can be achieved through the arrangement of the testing piece, meanwhile, pressing on the one-way position can also be achieved, and therefore the actual complex working condition of the bearing is simulated; and then the display device is used for marking and recording the deformation parameters of the bearing, so that the rigid change form of the bearing in a complex environment can be directly displayed, detection personnel can observe the rigid change form, and finally the accuracy of bearing detection is improved.

The invention relates to the field of building structure data processing, in particular to a building structure health monitoring method based on machine learning. The method comprises the steps that a distributed federated learning architecture is adopted, local models generate synthetic sensing data by adopting a dynamic self-learning-based SMOTE algorithm, and a self-encoding neural network based on accelerated convergence in each local model is trained; the central server carries out parameter aggregation and then updates the global model; acquiring new building sensing data, performing feature dimension reduction on the new building sensing data by adopting the trained self-encoding neural network based on accelerated convergence, and then classifying the new building sensing data after feature dimension reduction by adopting a Softmax function. The existing building structure health monitoring method has the problems of low classification accuracy and high possibility of large-batch data leakage. The building structure health monitoring method based on machine learning provided by the invention is high in classification accuracy, and is not liable to cause large-batch data leakage.

The invention describes a testing apparatus (1) for use in a wind turbine rotor blade manufacturing facility, comprising a pulling means (10) adapted to pull an adherent strip (3T) from a surface of a rotor blade (2); a positioning arrangement (11) configured to maintain a predetermined pull angle (x) between the adherent strip (3T) and the surface of the rotor blade (2) during a test procedure; and a support frame (12) for holding the pulling means (10) and positioning arrangement (11), which support frame comprises a clamping arrangement (14) adapted to clamp about the leading edge (2LE) of the rotor blade (2). The invention further describes a method of performing a test procedure on a wind turbine rotor blade (2) using the inventive testing apparatus (1).

The invention discloses a method for evaluating the performance of a friction pendulum type seismic mitigation and isolation support in a service state. The method comprises the following steps: S1, carrying out horizontal sliding displacement and vertical force detection on the friction pendulum type seismic mitigation and isolation support in service; s2, according to the detected data, the sliding interface friction coefficient mu of the service friction pendulum type seismic mitigation and isolation support is calculated; s3, according to the obtained sliding interface friction coefficient mu of the in-service friction pendulum type seismic mitigation and isolation support, anti-seismic performance indexes of the friction pendulum type seismic mitigation and isolation support are calculated, and the anti-seismic performance indexes comprise the horizontal rigidity and the effective damping ratio coefficient; and S4, according to the influence of the sliding interface state change and the horizontal rigidity change on the seismic damage state of the bridge structure, the anti-seismic safety risk of the friction pendulum type seismic mitigation and isolation support in the sliding interface state is graded. By means of the method, the sliding interface state and the specific friction characteristic of the friction pendulum type seismic mitigation and isolation support in the service state can be obtained, and therefore the anti-seismic performance of the friction pendulum type seismic mitigation and isolation support can be evaluated.

A method of assessing the quality of a manufactured component includes the steps of manufacturing a component and generating data at each of a plurality of locations through the component. The generated data is passed to a machine learning branch. The generated data is compared to training data at each of the plurality of locations and across a plurality of folds using K-fold validation to determine whether the component is of a functionally tolerant dimension at each of the plurality of locations. The training data at each of the plurality of folds at each of the plurality of locations is from a common part. A system is also disclosed.

The invention relates to the technical field of spring measurement, and discloses a spring fatigue life test system and a dynamic balance evaluation method, and the system comprises a reference length acquisition module, a dynamic balance state determination module, a working condition spectrum loading module, a stress-strain response data acquisition module, a damage feature extraction module and a life evaluation module. Acquiring a reference length in a free state; step increasing preload is applied, and when it is detected that the deformation rate of the to-be-detected spring is smaller than a set threshold value, it is judged that the to-be-detected spring reaches a dynamic balance state; in a dynamic balance state, loading the to-be-tested spring based on the variable amplitude load time sequence signal, and synchronously acquiring stress-strain response data; identifying the stress characteristics of the to-be-tested spring in the load period; generating a life evaluation report based on the stress characteristics; the accuracy of the fatigue life of the spring can be improved.

The invention discloses a bridge service state monitoring and early warning method based on machine vision, and the method comprises the steps: firstly building a bridge numerical model through numerical analysis software, and then arranging a sensor to recognize the information of passing vehicles; before monitoring is started, a standard vehicle is selected and passes through a bridge along the center line of each lane, and the influence surface of each feature point is established by recording the vertical displacement of the feature point in the vehicle driving process; according to the vertical displacement influence surface of each feature point of the bridge and the identified vehicle information, calculating the vertical displacement of each feature point by using a superposition method; and finally, calculating the correlation between the actual measurement response and the theoretical value, and when the correlation of more than three feature points is lower than 95%, triggering an alarm to remind passing vehicles. According to the method, piezoelectric sensing and machine vision technologies are fused, and accurate inversion of vehicle loads and real-time evaluation of bridge structure states are realized through axle coupling dynamic response analysis and a data dual criterion mechanism.