1863 results about "Scanner" patented technology

The invention discloses a point cloud differential defect detection system and detection method based on multi-feature fusion, which are mainly used for high-precision detection of surface defects of a side wallboard of a railway passenger car, and the method comprises the following steps: obtaining datum point cloud data through a designed standard side wallboard model of the railway passenger car, and collecting real-time point cloud data through a laser scanner; preprocessing the obtained point cloud data; calculating the difference between the real-time point cloud and the reference point cloud by adopting a difference method for fusing geometric features such as Euclidean distance, curvature and normal vector, namely calculating the Euclidean distance difference, curvature difference and normal vector difference between the reference point cloud and the real-time point cloud; and a comprehensive abnormal score is generated by further combining a dynamic weight fusion mechanism, and different region characteristics (such as a plane, a curved surface and an edge region) are adapted through dynamic threshold adjustment. According to the method, the defect region is segmented through the clustering algorithm, and the defect area and depth are quantified. The method has the advantages of high detection precision, strong adaptability and good real-time performance, and is suitable for complex surface defect detection in industrial production.

XCB poly-radio devices as finders, locators, scanners, sensors, and Bluetooth (BT) radio topology reporters as part of a global lost-and-found services system. XCB devices function as “smart objects” and combine dual transceivers operating in the telecommunications and the low power ISM radio spectra, with default power management overrides under local control of the BT modem. “Familiar zones” are defined, and a “familiarity index” versus a “strangeness index” based on meta-analysis of BT radio contact logs are used to assign location. Location, in concert with other sensor data, is coupled to conditional logic rules programmable by the user or the system administrator. Locations, determined by monitoring familiar and unfamiliar BT radio topology, trigger executable commands to smartphones, to smart devices generally, and to remote machines, and can for example, generate alerts to a user if radiotagged assets, children or pets have strayed, are lost, or are left behind. When tied to cloud predictive services or increased edge computing capacity, incipient loss of radiotag objects can be detected before an owner knows the smart object is lost. In another embodiment, XCB devices having a novel chip architecture for improved power management of cellular and MCU circuits mediated by BT radio modem that achieves “situational awareness” by monitoring the BT signal environment around the device.

The invention belongs to the technical field of road deformation monitoring, and discloses a road slope deformation monitoring system and method, and the system comprises a fixed point monitoring mechanism which monitors the displacement, strain, underground water level and inclination parameters of a slope in real time at key points and key positions of the road slope; the route planning module plans the flight route of the unmanned aerial vehicle; the cruise monitoring mechanism is used for monitoring the side slope in all directions; the weather data acquisition module is used for acquiring local weather data; the three-dimensional laser scanner data analysis module is used for identifying abnormal conditions on the side slope; the image analysis module is used for identifying abnormal conditions on the slope; the comprehensive evaluation module is used for comprehensively evaluating the stability of the slope by utilizing a comprehensive evaluation model; and the alarm module comprises an alarm. According to the invention, the fixed-point monitoring mechanism and the cruise monitoring mechanism are combined to monitor the slope in all directions, the comprehensive evaluation module fuses data of various monitoring means, and the comprehensive evaluation model is utilized to comprehensively evaluate the slope stability.

The invention discloses a tunnel deep-buried drainage ditch rapid blasting excavation method based on vertical drilling, which comprises the following steps: step 1, detecting the geology in front of a tunnel by using vertical drilling coring, geological radar and TSP seismic wave technology, and constructing a three-dimensional model; 2, generating an asymmetric hole net layout based on a geological model and AI, and setting a drilling-free vibration isolation belt; the design of dense inside and sparse outside is adopted, and vibration propagation is blocked; thirdly, a three-stage air spacer is arranged at the bottom of the blast hole, segmented charging is implemented, the explosive energy release time is prolonged, and the single-segment explosive quantity peak value is reduced; fourthly, an electronic detonator is adopted for millisecond detonation, and peak vibration is weakened through the waveform superposition offset effect; 5, arranging fiber grating sensors in the tunnel, collecting data in real time and transmitting the data to the cloud AI platform; dynamically adjusting parameters based on the monitoring data; and 6, evaluating a blasting effect through a three-dimensional laser scanner, generating an evaluation report in combination with data, updating a BIM model database, and continuously optimizing an AI algorithm.

The present invention relates to the field of dam area deformation early warning technology, and proposes a dam area deformation early warning method and system based on a laser scanner, which includes the following steps: selecting a drone, equipping the drone with a laser scanner and a Beidou positioning system; planning the monitoring flight path of the drone, continuously emitting lasers and receiving reflected signals through the laser scanner, and using the Beidou positioning system to record the scanning position information of the laser scanner in real time to obtain original three-dimensional point cloud data; integrating the three-dimensional point cloud data obtained by multiple scans of the laser scanner into a unified coordinate system through a registration algorithm to obtain a three-dimensional model of the dam area; using a statistical method and a preset threshold to perform a data consistency check on the original deformation data set, screening out abnormal values ​​in the original deformation data set, and obtaining a deformation data set; identifying the deformation data set through a dam area deformation risk assessment model, obtaining a dam area deformation risk level, and taking corresponding early warning measures based on different dam area deformation risk levels. The present invention improves the accuracy of deformation data, realizes accurate judgment of deformation risk levels, and takes corresponding early warning measures according to different risk levels, thereby enhancing the safety of the dam area.

The invention relates to the technical field of stone structure ultrasonic detection, in particular to a stone structure building detection method based on a concrete ultrasonic fault detection scanner, and the method comprises the steps: obtaining the initial signal intensity when an ultrasonic signal is transmitted by using the ultrasonic fault detection scanner; obtaining an ultrasonic reflection signal after the ultrasonic signal is reflected at each reflection point under each scanning layer, the intensity of the reflection signal after reflection, and the signal propagation duration; the method comprises the following steps of: obtaining a signal propagation time difference, a signal intensity difference, a signal difference index, a signal disorder degree, a defect evaluation coefficient, a seam recognition degree and a seam correction coefficient of each reflection point under each scanning layer, correcting the intensity of a reflection signal, performing three-dimensional reconstruction on a constructed tomography graph, and detecting internal defects of a stone structure building. According to the method, the interference of the reflection points on the splicing seams during stone splicing is reduced, the accuracy of detecting the internal defects of the stone structure building is improved, and the stability detection of the stone structure building is improved.

The invention relates to the technical field of fan blade detection, and provides a wind power plant fan blade detection method and system based on three-dimensional point clouds, and the method comprises the following steps: carrying out the multi-angle scanning of a fan blade through a laser scanner, and obtaining the three-dimensional point cloud data of the fan blade; performing registration processing on the three-dimensional point cloud data, and unifying the three-dimensional point cloud data into the same coordinate system to obtain registered point cloud data; performing block acceleration processing on the registered point cloud data by adopting an octree partitioning algorithm to obtain block acceleration point cloud data; performing feature extraction and feature segmentation on the block acceleration point cloud data to obtain a key feature region of the fan blade; performing defect identification analysis on the key feature region based on a point cloud network enhancement model to obtain a defect detection result, the defect detection result comprising a defect position and a defect type; and generating a detection report containing the defect position and the defect type, and visually displaying the detection report. According to the invention, the integrity of data acquisition and the precision of defect identification are improved, and the efficiency of fan blade detection is improved.

A control mechanism for self-cleaning filtration systems. One embodiment is a controller for a filtration system that comprises a suction scanner and a screening element having modifiable respective locations therebetween. The controller comprises an input terminal for receiving a relative location signal and additional a differential pressure input terminal. The controller monitors differential pressure and outputs an activation signal after the differential pressure has exceeded a threshold value. The controller outputs a termination signal based on the relative location signal. Another embodiment is a filtration system that comprises: a screening element located within a filtration chamber, and a suction scanner for self-cleaning thereof. A location tracker communicates to a switching mechanism during self-cleaning sessions a signal indicative of a location of the suction scanner with respect to the screening element. The switching mechanism automatically terminates self-cleaning sessions based on the signal.

A two-part RFID antenna, metallic packaging containing the same as part of an integrated RFID inlay, and methods of making and using thereof are described herein. In some embodiments, the two-part antenna contains a feed element and a radiative element. In some embodiments, the feed element is an antenna which sends and / or receives radio signals from an RFID reader / scanner. In some embodiments, the second element is a radiative element which radiates the radio signals received by or sent from the antenna. In some embodiments, the radiative element is a metallic packaging. The prototypes described herein exhibited good sensitivity and operating rang

The invention discloses a gear three-dimensional structure construction method, system and device and a medium, and the method comprises the steps: obtaining at least two groups of regional point cloud data of a to-be-detected gear and gear rotation angles corresponding to the regional point cloud data; the regional point cloud data is obtained by scanning through a laser scanner based on a multi-axis rotary clamping mechanism adjusting gear rotation angles, and the gear rotation angles corresponding to any two groups of regional point cloud data are different; calculating a rotation center axis of the gear to be measured according to the point cloud data of all areas; registering every two adjacent groups of regional point cloud data based on the rotation center axis and the gear rotation angle corresponding to the regional point cloud data to obtain registered regional point cloud data; and constructing a pose map structure of the to-be-detected gear based on the registered regional point cloud data to obtain a three-dimensional structure of the to-be-detected gear, so that a helical tooth surface with a complex curved surface can be comprehensively scanned, and non-contact, efficient and high-precision detection of the gear is realized.

The invention provides a double-pulse high-frequency switching power supply control method and system for precise electroplating, and relates to the field of electroplating, and the method comprises the steps: collecting area surface data through a three-dimensional scanner, and obtaining a three-dimensional model; extracting a high-curvature area grid according to the three-dimensional model, and calculating to obtain a surface concave-convex degree index; performing current field simulation, and calculating current density vector distribution; when the deviation of the current density vector distribution exceeds a preset deviation threshold value, pulse parameters are optimized through a genetic algorithm; selecting a pulse parameter which is most matched with the surface concave-convex degree index, and carrying out iterative calculation to obtain updated current density vector distribution; based on the difference between the updated current density vector distribution and the initial distribution, predicting a coating thickness value, and determining a preliminary evaluation index; and optimizing pulse parameters to obtain a final control scheme of uniform current distribution. According to the method, pulse parameters can be dynamically optimized according to the geometrical shape of the workpiece, and uniform current distribution and stable plating quality are realized.

The invention provides an intelligent road crack detection method, and belongs to the technical field of electrical digital data processing.The intelligent road crack detection method comprises the steps that firstly, a line structured light scanner is adopted to obtain road surface point cloud data, and attitude compensation processing is conducted in combination with an inertial navigation system; then noise is eliminated through bidirectional moving average filtering, and the depth matrix is converted into an image and segmented; gaussian background modeling is used to screen abnormal points, a connected graph is constructed through a minimum spanning tree algorithm, and pruning is carried out to obtain a crack skeleton; using a feature enhancement function to optimize the crack saliency; and finally, inputting a pre-trained multi-scale pavement damage identification network, and outputting a crack identification result and classification. According to the method, three-dimensional point cloud data, geometric feature analysis and a deep learning technology are fused, the technical problem of poor adaptability of a complex pavement environment is solved, and accurate identification of various crack types is realized.

The invention relates to the technical field of automatic equipment control, in particular to an automatic equipment control system and method and a storage medium. The method comprises the following steps that a high-frequency laser scanner is used for scanning the surface of a target polishing part, B-spline surface fitting is carried out, and a surface fitting surface model is generated; controlling the polishing operation of the polishing industrial robot based on the surface fitting curved surface model, and performing polishing contact state detection to generate contact state point cloud data; based on the contact state point cloud data, grinding expected pose error analysis is carried out, reverse impedance error compensation is carried out, and a reverse impedance compensation amount is obtained; and the joint angle of the polishing industrial robot is corrected through the reverse impedance compensation amount, so that reverse impedance control over the automatic polishing equipment is achieved. By compensating the reverse impedance error of the automatic polishing equipment, accurate control over the automatic polishing process is achieved.

The invention provides an attack fault tree security risk assessment system based on deep reinforcement learning, and relates to the technical field of information security. The system specifically comprises a network asset data fingerprint scanner module, a deep reinforcement learning network model generation and training module and an automatic penetration test tool set module. The invention aims to determine the optimal attack path from the system attack graph by using deep reinforcement learning. By combining the screened attack paths with various resources and time costs encountered in the actual penetration test, the failure rates of various security risks in the attack fault tree, the success probabilities of various attacks and other indexes can be determined. And finally, establishing an attack fault tree of a power system scene in the embodiment, comparing the attack lethality and the detection capability level of each attack path in a game phase, and qualitatively and quantitatively analyzing the final security capability level of the target system and the damage degree caused by attacks.

The invention discloses a full-position welding penetration online detection method based on cooperation of an electric signal and a molten pool image. A pipeline is subjected to full-position welding under cooperation of double robots; preliminary segmentation is conducted on the basis of the welding position, segmentation is conducted again at the angle of 5-10 degrees, a laser scanner is adopted to scan a pipeline groove to obtain the groove size of each segment, and self-adaptive setting of welding process parameters is achieved on the basis of a process knowledge base and a welding parameter adjusting model; fusing the molten pool image and the electric signal time domain characteristic value, and performing discrimination through a neural network prediction model; and obtaining weld pool size characteristics based on the weld pool image, calculating a reference weld pool oscillation frequency based on a reference weld pool oscillation frequency model, performing spectral analysis on an upper envelope signal of the voltage signal, calculating an actual weld pool oscillation frequency, and comparing the actual weld pool oscillation frequency with the reference weld pool oscillation frequency to judge whether the weld is penetrated or not. According to the invention, all-position welding forming defect monitoring of the robot is realized.

The invention discloses a nondestructive testing method for a welding seam of a steel structure. The method comprises the steps that firstly, morphology data of the surface of a building steel structure are obtained through a high-precision laser scanner and an electromagnetic induction technology; coating thickness distribution and weld surface roughness are analyzed based on the morphology data, and a surface information matrix is constructed; then automatically adjusting ultrasonic wave beam parameters of the ultrasonic phased array by using the adaptive parameter regulation and control model and executing detection to obtain a preliminary ultrasonic echo signal; the time-frequency domain difference between the preliminary echo and the reference signal is calculated through an echo signal compensation model, and secondary compensation is completed to obtain an optimized ultrasonic echo signal; fusing the optimized echo signal, the morphology data and the surface information matrix to construct a detection data set, and adopting a pre-trained steel structure detection model to realize defect detection; and finally, evaluating the confidence of a detection result by adopting a three-dimensional confidence evaluation model, performing grading, and performing local re-detection and parameter adjustment on a low-confidence region to form closed-loop optimization. According to the method, the surface state of the steel structure can be adaptively matched, the accuracy of echo signals and the defect detection precision are improved, and the detection reliability is guaranteed through three-dimensional confidence evaluation.

The invention discloses a tunnel fire extinguishing robot emergency command system and a use method. The system comprises an inspection robot, a fire extinguishing robot, a visual command center, an industrial internet platform and corollary equipment. The inspection robot is in communication connection with the visual command center through the industrial internet platform; the visual command center is provided with a dispatching module for dispatching the fire extinguishing robot and a navigation module; and the fire extinguishing robot is in communication connection with the visual command center through the industrial internet platform. A high-definition infrared camera, multiple types of sensors and a laser scanner are carried, and conditions in a tunnel are monitored in real time; an automatic fire extinguishing device is carried, and the fire spraying angle can be adjusted through remote control for accurate fire extinguishing; by analyzing monitoring data and alarm information, the robot can be remotely commanded to perform emergency response; the system can upload monitoring data and transmit instructions of the command center to the fire extinguishing robot in real time.

The invention relates to the technical field of power transmission line monitoring, and provides a three-dimensional point cloud monitoring method and system for fracture and galloping of an overhead line of a power transmission line iron tower, and the method comprises the following steps: arranging a three-dimensional laser scanner along a power transmission line; acquiring original three-dimensional point cloud data of the power transmission line in real time; performing real-time noise reduction, filtering and compression on the original three-dimensional point cloud data to obtain three-dimensional point cloud data; based on the three-dimensional point cloud data, establishing a three-dimensional digital model of the power transmission line, extracting characteristic parameters of the three-dimensional digital model of the power transmission line, calculating a time sequence change rate of the characteristic parameters, and constructing a characteristic vector space; in the feature vector space, feature matching is carried out on the feature vectors, the operation state of the power transmission line is recognized in real time, and whether fracture galloping exists or not is judged; and generating a monitoring report according to the judgment result of the fracture galloping. According to the invention, the coverage range and acquisition precision of transmission line fracture galloping monitoring are improved.

The invention belongs to the technical field of atmospheric environment monitoring, and particularly relates to an unmanned aerial vehicle laser radar calibration quality control system and method, and the system comprises an unmanned aerial vehicle flight platform, a laser radar module, a navigation positioning module, a control communication module, a data processing module and a ground station. The unmanned aerial vehicle flying platform comprises a shockproof holder and a protective pod; the laser radar module comprises a laser radar, a scanner module and a photoelectric detector module. According to the invention, one unmanned aerial vehicle is adopted to carry various different types of laser radars, the extinction coefficient is measured by combining optical beam splitting, signal processing and algorithm inversion technologies, and atmospheric particulate classification is effectively monitored through cooperation of a high-precision optical system and an algorithm; the extinction coefficient and the depolarization ratio work cooperatively, high-precision quantitative analysis and classification of pollutants can be achieved, the combined measurement function of the extinction coefficient and the depolarization ratio is achieved, and high-resolution three-dimensional monitoring of atmospheric particulates is achieved through multi-parameter cooperative inversion of the laser radar.

A system for surface analysis of a cable layer. The system comprises an in-line surface scanner arrangement and a controller. The in-line surface scanner arrangement is for scanning a cable layer in or received from a cable manufacturing line, the scanner arrangement comprising one or more non-contact distance scanners arranged to measure distance to an outer surface of the received cable layer. The controller is arranged to receive scan data of the outer surface of the received cable layer based on signals received from the in-line surface scanner arrangement; extract surface texture data from the scan data; determine one or more properties of the surface of the cable layer based on the surface texture data; compare at least one determined property with one or more threshold criteria; and identify at least one of a surface feature of interest, a deviation, or a defect based on the comparison.

The invention discloses a deflection non-contact detection method applied to a grid structure circular steel pipe rod piece, and relates to the technical field of steel pipe rod frames. The method comprises the steps that grid structure point cloud data are acquired through a laser scanner, and high-density voxels are obtained through voxel division and density analysis screening; performing spherical fitting on the high-density voxels, and extracting spatial spherical anchor points according to a spherical fitting difference value; constructing a grid space candidate connection matrix based on the spatial spherical anchor points, screening to obtain a linear point cloud paragraph, and fitting the axis of the rod piece through a least square method based on an RANSAC (Random Sample Consensus) algorithm; a connecting line of the spatial spherical anchor points serves as a theoretical axis of the rod piece, and a deflection degree value and a deflection offset vector are calculated through offset analysis with the fitting axis; when the deflection degree value exceeds a preset threshold value, marking an abnormal rod piece, and constructing a net rack local sub-graph by taking the abnormal rod piece as a center; and calculating a deflection direction consistency index and a deflection degree consistency index in the subgraph, calculating a local risk comprehensive index by combining the two indexes, and dividing risk grades.

The invention provides a method for detecting the influence of temperature and mechanical deformation accumulation on the anti-short circuit performance of a converter transformer, belongs to the technical field of converter transformer anti-short circuit, and deeply studies the mechanical response characteristics of the converter transformer under different temperature and dynamic force load conditions through precise experiments and data analysis. Firstly, material characteristic parameters are obtained, temperature and mechanical load tests are carried out on a dynamic mechanical tension press, and temperature field distribution, mechanical response, residual deformation and insulation distance change of a converter transformer component are recorded in detail by using advanced equipment such as a three-dimensional laser scanner, a temperature sensor, a displacement sensor and a high-speed camera system. Through finite element analysis and data processing, a dynamic characteristic database under the accumulated action of temperature and mechanical deformation is established, and a correlation model is trained by applying a machine learning technology, so that the problem that a detection method capable of comprehensively evaluating temperature-mechanical deformation-electrical performance interaction is lacked in the prior art is solved.

The invention discloses a multi-element blasting effect evaluation method and system based on point cloud data, and relates to the field of blasting effect evaluation of a drilling and blasting method.The method comprises the steps that point cloud obtained after tunnel blasting is scanned through a three-dimensional laser scanner, and classification of muck pile point cloud, tunnel face point cloud and hole body point cloud is achieved through a Canupo algorithm; the muck pile point cloud, the tunnel face point cloud and the hole body point cloud are processed, and the boulder rate, the throwing distance, the excavation footage, the blast hole utilization rate, the tunnel half hole and the over-excavation and under-excavation quantity index parameters are obtained; and obtaining a blasting effect evaluation score through the combination weight and the score of each index parameter, and obtaining blasting effect evaluation. According to the method, multiple blasting effect evaluation indexes can be accurately obtained based on the point cloud data obtained through three-dimensional laser scanning, the blasting effect is quantitatively evaluated, a large amount of manpower is saved, the blasting effect evaluation efficiency and accuracy are improved, and reference is provided for improvement of subsequent blasting design.

The invention discloses a channel characteristic map determination method and device, relates to the field of communication, and can determine a high-precision channel characteristic map. In the method, a terminal device and / or an access network device senses an environment based on sensing devices such as a radar, an infrared sensor, a camera, a point cloud laser scanner and the like and a communication pilot signal to sense material information of a scatterer and relative position information of the scatterer and the terminal device and / or the access network device; and the information is sent to the channel feature map management device through a first message, and the channel feature map management device determines a channel feature map according to the first message, so that a high-precision channel feature map is obtained.

The invention discloses a tunnel point cloud high-precision splicing method based on rotation and translation constraint, and belongs to the technical field of engineering measurement and three-dimensional laser scanning. The method comprises the following steps: a data acquisition stage: acquiring absolute coordinates and relative point cloud data of each station through collaborative operation of a total station and a frame station scanner, and completing scanning of a target tunnel section; a point cloud data preliminary transformation stage: performing translation transformation on relative point cloud data of each station by using absolute coordinates of a rack station scanner, and preliminarily transforming the relative point cloud data into a global coordinate system; a two-stage registration stage based on rotation translation constraint: carrying out two-stage registration on the relative point cloud data of the adjacent sites after preliminary transformation; and a global point cloud model generation stage: unifying the relative point cloud data of all sites to a tunnel construction global coordinate system through two-stage registration, and generating a complete tunnel three-dimensional point cloud model. According to the invention, through rotation translation constraint and a two-stage registration strategy, the millimeter-level splicing precision is ensured, and the cost and the operation difficulty are reduced at the same time.

The invention discloses a shield tunnel segment behind-wall accurate detection and grouting trolley and a construction method thereof.The shield tunnel segment behind-wall accurate detection and grouting trolley comprises an electric car, a track is laid in a shield tunnel, the electric car walks on the track, an annular guide rail is installed at one end of the electric car, and the annular guide rail and a shield tunnel segment are coaxially arranged; the electric moving seat is arranged on the annular guide rail in a sliding manner; the geological radar detector is mounted on the electric moving seat in a position-adjustable manner; the laser scanner is mounted on the electric moving seat; the mechanical arm is installed at the other end of the electric car, a grouting pipe is installed on the mechanical arm, and the grouting pipe is connected with a grouting pump; and the controller is connected to the electric moving seat, the geological radar detector, the laser scanner, the mechanical arm and the grouting pump. According to the method, the problem that application limitation exists in an existing shield tunnel synchronous grouting quality evaluation means is solved.

The invention discloses a vein boundary extraction method, computer equipment and a storage medium, and relates to the technical field of data processing. The method comprises the following steps: acquiring point cloud data of a mine roadway through a three-dimensional laser scanner to obtain initial point cloud data; segmenting according to the initial point cloud data to obtain non-ground point cloud data; performing grid division on the non-ground point cloud data to obtain an initial point cloud grid map; extracting an elevation point cloud image and a reflection intensity point cloud image according to the initial point cloud grid map; based on the maximum entropy threshold, performing point cloud elimination on the initial point cloud grid map according to the elevation point cloud image and the reflection intensity point cloud image to obtain a target point cloud grid map; and based on an Otsu threshold method, performing threshold segmentation on the target point cloud grid map according to the reflection intensity point cloud image to obtain a target vein boundary. In this way, the boundary difference between objects can be identified in an auxiliary mode through the reflection intensity information, and the accuracy and stability of vein boundary extraction can be improved.

As an example, an asset receives a request from a scanner performing a reconnaissance of a network that includes the asset. The asset sends a response acknowledging receiving the request, indicating that the asset is alive. The asset receives port scan requests associated with ports of the asset. The asset creates fake fingerprints that include incorrect information about ports of the asset. The asset sends the fake fingerprints to the scanner in response to the port scan requests. The asset determines that a scan engine is requesting access to the asset via a particular port of the asset. The asset grants the scan engine access to the asset via the particular port to enable the scan engine to gather asset data associated with the asset for analysis.

An electromechanical Smart Lock is unlocked by the Smart Lock timely receiving a time sensitive access-code that solves a cryptographic hash algorithm (e.g., SHA-3 or the like) running on that Smart Lock. To enable this functionality, the Smart Lock knows at least three items of information: status of a countdown timer, its cryptographic hash algorithm, and its unique identifier. Further, the Smart Lock may have various elements for receiving the time sensitive access-code, such as, but not limited to, a QR code camera, a barcode scanner, a camera, a microphone, a keypad, and / or optionally, an antenna(s) / radio(s) for RFID / NFC inputs to the Smart Lock. Server(s) may also know the same three items of information for each given Smart Lock; and the Server(s) may provide time sensitive access-codes to (authorized) user(s) and / or to their devices. Users may request, receive, and / or send the time sensitive access-codes via text messaging (or other elements).

The invention discloses a multi-field joint detection method for force transfer path change of a deep flexural member, relates to the technical field, and aims to solve the problems that the local bearing capacity of a structure is reduced and the uncertainty of a force transfer path is increased. Collecting crack width and concrete peeling thickness and area, calculating a cross section loss coefficient, determining pressure rod bearing width by combining the crack width, analyzing a crack density index after screening a target position, and judging whether a path migration signal is generated or not. After a signal is generated, acquiring strain data by using a fiber grating sensor, analyzing the characteristics of a force transmission path, detecting vibration acceleration, fusing the strain data and the vibration acceleration to evaluate a path reconstruction index, and judging whether the force transmission path is changed or not. The method effectively improves the monitoring precision and response speed of the deep flexural member, avoids potential faults, and guarantees the structural safety.