9results about How to "Improve safety management efficiency" patented technology

The wireless blasting vibration meter comprises a shell, the shell comprises a bottom plate and an outer shell, and the bottom plate and the outer shell are fixed together in a sealed mode; a fixing frame is arranged in the bottom plate, and three accommodating cavities for accommodating detectors in the X direction, the Y direction and the Z direction are arranged in the fixing frame; a circuit board is further fixed on the inner side of the shell, and the detector is electrically connected with the circuit board; a 4G antenna, an external SIM card terminal and an on-off key are arranged on the side face of the shell and all electrically connected with the circuit board. According to the utility model, the X-axis detector, the Y-axis detector, the Z-axis detector and the data acquisition part are integrated in the same sealed housing, so that compared with a traditional split structure, installation steps can be simplified; and meanwhile, the shell adopts a closed design that the positioning raised lines are matched with the sealing rings, so that the waterproof, moistureproof and anti-interference capabilities of the equipment in a severe environment can be remarkably enhanced, and the stability and continuity of monitoring operation are ensured.

The application provides a kind of intelligent construction site safety monitoring and abnormal behavior detection method, it is related to behavior identification technical field, including: based on video frame data, through target detection algorithm, personnel and cigarette in the construction site multi-modal data are positioned, to output first detection result;Based on the first detection result, video frame data and construction site multi-modal data in the preset time period, utilize 3D CNN to combine attention mechanism, to output second detection result;Based on the second detection result and construction area security level information, by isolated forest and self-encoder algorithm, get comprehensive abnormal score.

The invention relates to the field of airport road foreign matter detection, and provides a machine learning-based FOD detection algorithm, which comprises an input module used for receiving basic image data of an airport runway; the processing module is used for carrying out preprocessing and feature extraction on the input data; the storage module is used for storing the original image data and the detection result; the acquisition module is used for acquiring image and sound data of an airport runway in real time; and the recognition module is used for recognizing moving objects and static objects in the collected data based on a machine learning model. And high-precision real-time detection is realized through cooperation of multiple modules. The acquisition module adopts a high-definition camera to ensure that image data is clear; the processing module utilizes a convolutional neural network (CNN) to extract features, and can accurately recognize moving and static objects in combination with a YOLOv5 algorithm of the recognition module. The comparison module compares the real-time image with the original image, abnormity is judged if the real-time image is lower than the threshold value, the runway foreign matter can be found in time, and the system can rapidly position the FOD in the complex environment.

The invention relates to a cross-network access control strategy dynamic arrangement method based on intention driving, and belongs to the field of network security. Through a BERT-based field adaptive intention analysis engine, a rule reasoning and machine learning fused strategy generation algorithm, a graph theory-based multi-dimensional strategy conflict detection and resolution mechanism, a multi-network domain-oriented multi-target optimization strategy arrangement framework and an eBPF-based high-performance strategy execution engine, a multi-network domain-oriented multi-target optimization strategy arrangement framework is optimized, and a multi-network domain-oriented multi-target optimization strategy is optimized. And intention-strategy-state closed-loop control is realized through a four-layer collaborative architecture. The method has the closed-loop control capability, can respond to network changes in real time, and remarkably reduces the operation and maintenance complexity while improving the safety management efficiency.

The application relates to a bolt, which comprises a head and a screw rod and further comprises: a blind hole, the inner end of the blind hole being arranged in the screw rod, and the outer end of the blind hole penetrating through the head; a jack rod, which is arranged in the blind hole and is fixedly connected with the blind end of the blind hole at the lower end; and a sensing device, which is arranged on the head and is used for converting the axial displacement of the upper end of the jack rod into an electric signal. The intelligent bolt of the application can realize instant feedback of the loosening state of the bolt by real-time detection of the axial displacement of the jack rod representing the deformation of the bolt, conversion of the mechanical displacement into the electric signal, compact structure, seamless integration of the sensing device and the bolt body through the embedded design of the blind hole and the jack rod, reservation of the traditional bolt appearance, no need to greatly change the traditional bolt structure, easy installation, real-time monitoring of the bolt state, reduction of the artificial inspection frequency, reduction of the maintenance cost, remote monitoring through wireless signals, and improvement of the safety management efficiency.

The invention relates to the technical field of computers, in particular to an identity recognition method and device, electronic equipment and a storage medium, and is used for quickly confirming the identity of an object in a medium replacement scene. The method comprises the steps that a verification instruction sent by a first object terminal is received, the verification instruction comprises a place identifier of a target place and target biological information, and the target biological information is a verification operation triggered by the first object terminal in response to a first object and biological information of a second object, the first object is an object with business management authority in the target place; determining a candidate biological information set according to the place identifier; the candidate biological information set comprises candidate biological information of at least one candidate object, and each candidate object is an object executing the target business through biological recognition verification in the target place; and when the target biological information hits the candidate biological information set, determining identity information of the second object based on the hit candidate biological information, and returning the identity information to the first object terminal.

The invention discloses a new energy automobile battery multi-parameter real-time monitoring and thermal runaway early warning system, which comprises a vehicle-mounted data acquisition module, a cloud data analysis module and a remote early warning module, and is characterized in that the vehicle-mounted data acquisition module is used for acquiring original data of a new energy automobile battery in real time; the cloud data analysis module constructs a multi-parameter fused thermal runaway risk index calculation model based on the original data of the new energy automobile battery, and obtains a thermal runaway risk index by using the thermal runaway risk index calculation model, and the remote early warning module is used for performing graded early warning according to the thermal runaway risk index and sending early warning information. According to the system, the thermal runaway risk index is calculated through the thermal runaway risk index calculation model, graded early warning is carried out according to the thermal runaway risk index, information is pushed to the user, the problem of early warning lag of a traditional BMS is effectively solved, and the safety and reliability of the new energy automobile are improved.

The application relates to the technical field of file storage, and discloses an administrative file tamper-proof storage method and system. The method comprises the following steps: associating and coupling content features and structure description information to obtain a digital fingerprint; binding a unique identifier to the digital fingerprint to obtain a feature binding record; block-encoding metadata and the feature binding record to obtain a data block, and storing the data block in a chain based on a blockchain consensus mechanism to obtain a storage chain record; when a target file is accessed, performing multilevel verification on an instant feature digest and the storage chain record to obtain a state verification result; when the state verification result is passed, archiving an access log in the storage chain record; when the state verification result is not passed, locking an access right to obtain a right locking record, and auditing and tracking the right locking record to generate an audit report of the target file; and the application can improve the security of administrative file storage.

This application provides a railway safety management system and method based on BeiDou positioning, relating to the field of safety monitoring technology. It solves the technical problem that existing railway safety management systems, due to the comprehensive data analysis, waste a large amount of computing power, thus reducing the efficiency of railway safety management. The method includes: acquiring first positioning information of each carriage of a train; the first positioning information is the carriage positioning; dividing the area in front of the train into several warning zones based on the first positioning information; acquiring several second positioning information of the track in each warning zone; the second positioning information is the positioning of a positioning point on the track; generating a regional anomaly score for each warning zone based on the second positioning information; and generating a warning signal based on the regional anomaly score. This application is used for safety monitoring and early warning during train operation; it significantly reduces the waste of computing power, thereby improving the efficiency of railway safety management.