1881 results about "Operational safety" patented technology

The invention discloses an intelligent operation and maintenance method and system based on an MCP protocol, and belongs to the crossing field of artificial intelligence and operation and maintenance automation. The system comprises an AI Agent module, a central intelligent analysis engine module, a man-machine interaction module and a safety control module. The method comprises the following steps: collecting system operation data in real time through an AI Agent module, and packaging the system operation data into an MCP protocol format; the central intelligent analysis engine module predicts the load based on an LSTM model, and generates operation and maintenance decision suggestions in combination with log anomaly recognition and reinforcement learning; the man-machine interaction module realizes understanding of user input through a natural language large model, automatically converts the user input into an MCP instruction, and supports multiple rounds of interaction confirmation and instruction verification; the safety control module provides an MCP operation sandbox and semantic instruction verification, and the operation safety is guaranteed. The system can dynamically schedule resources and automatically dispose faults, realizes that non-technical personnel can execute complex operation and maintenance operations, and is suitable for application scenes with high reliability requirements, such as industrial data acquisition and chemical engineering.

The invention discloses a ship control auxiliary method based on machine learning, and relates to the technical field of ship intelligent control, and the method comprises the steps of ship data collection, fuel oil energy consumption prediction, dynamic navigational speed planning and energy-saving feedback control. According to the method, the fuel energy consumption is predicted by adopting a prediction method combining multi-mode and disturbance self-adaption, modeling multi-dimensional data is unified, perception of environmental disturbance is enhanced, accurate prediction of the fuel energy consumption under complex navigation conditions is realized, and the reliability of subsequent dynamic navigational speed planning is effectively improved; dynamic speed planning is carried out by adopting a speed planning method combining multiple targets and segmented constraints, three core factors of fuel energy consumption, navigation time and safety risks are comprehensively considered, a multi-target cost function is constructed, segmented constraints are introduced, the physical feasibility and risk control of speed adjustment are guaranteed, the speed is optimized through a reinforcement learning mechanism, and the speed planning efficiency is improved. Intelligent self-adaptive navigational speed adjustment is achieved, and the energy-saving capacity, the navigation efficiency and the operation safety of the ship under the complex navigation condition are improved.

The invention relates to the field of industrial production, and discloses a predictive maintenance system for an ultra-efficient explosion-proof motor based on digital twinning, which comprises the following steps: when key operation parameters of the motor deviate from a normal working condition interval, judging whether the key operation parameters reach a digital twinning model activation threshold value or not; based on historical operation data, sensor real-time data and environmental factors, a digital twin model is called to construct virtual mapping of motor operation, a current state evolution trajectory is generated, and whether the operation trend has a fault or not is predicted; the state track change mode is matched with a historical fault library, and whether a potential fault path exists or not is evaluated; according to the fault risk level and the predicted occurrence time, in combination with the current production plan and the equipment health tolerance, whether an advanced intervention measure needs to be taken is judged; and generating an intervention scheme according to state regulation and control parameters fed back by the digital twinning model in combination with specific working conditions. The method has the advantage that the operation safety and the maintenance efficiency are improved.

The invention relates to the technical field of metering pumps, in particular to an external meshing gear metering pump flow calculation method based on linear regression and curve fitting, which comprises the following steps: generating an integrated data set by monitoring the flow rate, pressure, temperature and viscosity in real time, setting flow rate, pressure and temperature thresholds based on the data set, judging the flow state and recording abnormity, and calculating the flow rate of the external meshing gear metering pump. Flow velocity and viscosity are selected for flow calculation, a corrected flow value is generated, whether flow is normal or not is analyzed and determined, a flow stability evaluation result is generated, and a visual interface is created to display parameters and a calculation result. According to the method, the multiple sensors are installed at the inlet and the outlet of the metering pump, the flow speed, the pressure, the temperature and the viscosity are monitored in real time, an integrated data set provides a precise basis for flow calculation, a threshold value is set, data are monitored, it is ensured that parameters exceeding the normal range can be recorded and analyzed in time, and the process improves the accuracy of flow calculation and improves the working efficiency. And flow evaluation is optimized, and the operation safety and efficiency are improved.

The invention relates to the technical field of aerocar mode switching, and discloses a distributed driving aerocar self-adaptive fault-tolerant control method for actuator multimode failure, which comprises the following steps: constructing a unified six-degree-of-freedom dual-mode state space model; residual signals are generated based on extended Kalman filtering and a sliding-mode observer, and fault types and positions are positioned in real time through a lightweight classifier; the method comprises the following steps: extracting residual time-frequency features, identifying hard faults by using a lightweight convolutional neural network, quantifying soft fault degrees through an incremental support vector machine, fusing multi-source information based on a Bayesian network to output fault types, levels and confidence coefficients, and introducing an incremental learning mechanism to realize self-evolution of a diagnosis model; a virtual control instruction is generated by adopting hierarchical sliding mode control, thrust and torque distribution of remaining actuators is optimized based on a dynamic quadratic programming algorithm, control parameters are adjusted online in combination with a Lyapunov adaptive law, aerodynamic interference and model uncertainty are inhibited, attitude stability and trajectory tracking in air-ground mode switching are guaranteed, and the method has the advantages of being high in reliability and high in reliability. And the fault-tolerant performance and the operation safety of the hovercar in the air-ground mode switching process are obviously enhanced.

The invention discloses an intelligent monitoring and adjusting method and system for a steel structure, and the method comprises the steps: deploying a plurality of types of sensors at key parts of the steel structure, continuously collecting various types of physical quantity data, recognizing potential abnormal events in real time through a dynamic threshold detection mechanism, and responding to the abnormality of a certain sensor. The system automatically associates and extracts the time sequence data of other sensors associated with the spatial position of the sensor before and after the exception to form a multi-dimensional and time-space coupled data slice, and then performs time-space feature extraction on the data to extract the mode representation of the complex exception state; and based on this, accurate matching and diagnosis of the causes of the abnormal events are realized. Through the mode, the intelligent sensing and analysis capability of the health state of the complex, multi-source and multi-dimensional steel structure is improved, solid data support and decision basis are provided for subsequent scientific adjustment measures, and the operation safety and management intelligence level of large-scale steel structure engineering are better guaranteed.

The present invention discloses a method, apparatus, medium, and device for sway control of an overhead crane, the method comprising: establishing a lifting strategy corresponding to the target lifting operation; obtaining training data of the target operator controlling the crane bridge and / or trolley to complete a simulated lifting operation according to the lifting strategy; analyzing the training data to generate the sway control method for each target motion state of the crane bridge and trolley; and adopting the corresponding sway control method during actual lifting based on the current travel state of the crane bridge and trolley. The present invention performs overall path planning and crane bridge and trolley motion state planning for the lifting operation to determine a lifting strategy consistent with the construction site environment.During the lifting process, electronic and manual sway damping are combined depending on the operator's operating habits and skills, which not only improves the lifting performance but also increases the operational safety of the bridge crane, so that the load only shakes slightly when the bridge crane starts, stops, accelerates or decelerates, which improves the safety of the lifting process.

The invention discloses a vehicle operation control system, method and equipment, a medium and a product. The system comprises an operation state determination subsystem used for determining predicted operation situation information associated with a vehicle; the operation constraint subsystem is used for determining vehicle operation constraint parameters based on the predicted operation situation information and determining a to-be-driven mode of the vehicle; the motion control subsystem is used for determining an actuator reference instruction based on the predicted operation situation information, the to-be-driven mode, the vehicle operation constraint parameters and the to-be-driven track; the control distribution subsystem is used for determining an actuator distribution instruction of a plurality of actuators in the vehicle based on the actuator reference instruction and the predicted operation situation information; and the coordination control subsystem is used for determining target actuator instructions of the plurality of actuators based on the to-be-driven mode and the actuator distribution instruction, and controlling the actuators to operate based on the target actuator instructions. The control consistency, the response real-time performance, the operation safety and the comfort of the whole vehicle in a complex dynamic scene are improved.

The invention relates to the technical field of mechanical arms, in particular to a man-machine interaction system of an intelligent mechanical arm with a body. The system decomposes a long time sequence task into sub-tasks through a large language model, and introduces a task acquisition module, a task queue management module, a task re-planning module and a control execution module, uses visual detection to identify gestures and environment events to trigger temporary tasks, and maintains interruptible marks and safety anchor points based on priorities and interruption risks. And during interruption, the mechanical arm with the timestamp and the environment state are collected, during recovery, the states are compared, local re-planning is carried out, transition sub-tasks are automatically generated for failure sub-tasks, and the mechanical arm is controlled to execute after constraint verification. According to the system, on the premise that the structure consistency, the space consistency and the time consistency are guaranteed, safe interruption and efficient recovery in a long-time-sequence task can be achieved, and the autonomy, the real-time performance and the operation safety of the mechanical arm in a man-machine cooperation scene are remarkably improved.

The invention belongs to the technical field of hydroelectric generating set monitoring, and relates to a water turbine bearing temperature and lubricating oil state monitoring and fault diagnosis method and system. According to the method, triple-redundancy temperature measurement values of a water turbine bearing are adopted, multiple parameters are fused, redundancy design is adopted, sensor failure diagnosis is executed, a temperature-vibration-oil pressure combined feature space is constructed according to the triple-redundancy temperature measurement values and online oil quality parameters, a fault propagation map is established, and the fault propagation map is analyzed. And finally, based on the multi-level diagnosis model and in combination with the fault propagation atlas, composite fault mode recognition is realized, a fault classification result is obtained, and the composite fault mode recognition is realized based on the multi-level diagnosis model, so that the problems of low reliability, single monitoring dimension and insufficient fault recognition capability of a sensor in the prior art are effectively solved. And the equipment reliability and the operation safety are obviously improved.

The invention discloses an elevator operation fault early warning method and system, relates to the technical field of intelligent elevator control, and aims to improve the operation safety and fault response capability of an elevator in a potential abnormal state. By constructing a load critical drift test working condition, a sudden non-vertical stress test working condition and a weak power supply fluctuation interference test working condition, abnormal behaviors which are difficult to appear but have potential safety hazards in the normal operation process of an elevator are induced; the method comprises the following steps: acquiring operation data under various working conditions, respectively calculating a drift overload response coefficient, a guide rail non-vertical interference coefficient and a power supply induced instability coefficient, respectively comparing the coefficients with preset thresholds, and judging whether operation faults such as brake response mismatching, asynchronous action of safety tongs and door lock control interference exist or not; and if the judgment result is abnormal, a targeted strategy is automatically generated and early warning is given out. According to the method, active recognition and classified response of elevator faults can be achieved, and the maintenance efficiency and the operation reliability are effectively improved.

The invention relates to the technical field of water conservancy projects, in particular to a construction scheduling method for collaborative linkage of cross-basin water conservancy projects, which comprises the following steps of: constructing a space-time water conservancy topological network to realize multi-source data fusion and spatial association and provide a basis for accurate scheduling; potential contradictions between construction and hydrological regulation and control are found in advance by recognizing conflict areas and performing quantitative analysis; a space-time safety window strategy set is formulated, the construction period is optimized in combination with risk prediction, and operation safety and efficiency are guaranteed; through task decomposition and collaborative factor allocation, an atomic operation unit and a dependency relationship are defined, and the cross-project linkage capability is improved; by generating a preliminary scheduling scheme, and through a resource-collaborative double-constraint graph and a genetic algorithm, efficient resource configuration and conflict minimization are realized; through dynamic risk monitoring and scheduling scheme reconstruction, hydrological abrupt change and construction deviation are quickly responded, cooperative factors are triggered for rebinding, and scheme adaptability and robustness are ensured.

The invention relates to the technical field of authority control, in particular to a Bluetooth-based operation and maintenance authority control system, which comprises a Bluetooth link identification module, a task risk assessment module, an authority adaptation decision module, a task path verification module and an execution consistency verification module. By acquiring the Bluetooth communication address and the channel number and combining the hopping frequency and the stability, the link security state identification is realized, the communication legality judgment precision is improved, the task risk is evaluated by introducing the equipment performance and the communication parameters, the bearing capacity judgment precision is improved, the permission level, the execution frequency and the historical success rate are combined, and the reliability of the system is improved. The permission matching state is dynamically verified, and the task success rate is optimized. Relay node addresses are compared with declaration path structure consistency, accurate and reliable paths are ensured, execution environments are verified according to device roles and instruction contents, instruction execution feasibility judgment is enhanced, all links are compared based on real-time data and structures, task whole-process closed-loop control is formed, and operation safety and decision accuracy are improved.

The invention relates to a self-adaptive control method for a rain and snow mode of rail transit, electronic equipment and a medium, and the method comprises the steps: comprehensively studying and judging a rain condition based on multi-sensor data and numerical weather forecast data, and calculating a weather grade in the rain and snow mode, the multi-sensor data including video detection data, laser radar data and rainfall data; whether a rain and snow mode is set or not is judged according to the weather level, if yes, the current track slip degree is evaluated according to the multi-sensor data, and the GEBR value is adaptively updated based on the slip degree; the CC calculates the running safety braking envelope of the train by using the updated GEBR value, and feeds back a slip detection result and a dynamic parameter adjustment result in real time; and the ATS dynamically adjusts the operation plan of the train according to the slip detection result reported by the CC, and optimizes the operation scheduling of the whole train. Compared with the prior art, the method has the advantages that self-adaptive management of the rain and snow mode is achieved based on the dynamically-adjusted GEBR, and the running safety and reliability of the train in the rain and snow weather are effectively improved.

The invention relates to the technical field of pole-mounted circuit breakers, in particular to a pole-mounted circuit breaker with a protective cover, which comprises a circuit breaker body, the circuit breaker body is detachably connected with the protective cover, the top of the protective cover is provided with a through hole for a cable to pass through, and two opposite side walls of the protective cover are provided with access holes in a penetrating manner. The protective cover is movably provided with a door curtain used for shielding the access hole, the door curtain and the protective cover are both provided with locking structures, and the locking structures are used for locking the door curtain on the protective cover. The circuit breaker body is protected through the protective cover, the operation safety is remarkably improved, the service life of equipment is remarkably prolonged, and the movable door curtain is arranged so that an operator can conveniently overhaul the circuit breaker body.

The invention relates to the technical field of low-altitude aircraft chip safety monitoring, and discloses a low-altitude aircraft chip safety monitoring system which comprises a state acquisition module, a risk assessment module, an anomaly detection module, a strategy generation module, an instruction execution module, an effect verification module, a threshold setting module, a data output module, a feedback optimization module and a system regulation module. The state acquisition module analyzes the operation parameters and the environment interference to obtain a state value; the risk assessment module extracts and screens abnormal protection feature combinations; the anomaly detection module combines a sample variation matching feature with an evaluation combination; the strategy generation module maps a feature strategy based on real-time data and sets a rule; the instruction execution module captures feature data and analyzes a trend; the effect verification module adjusts rules according to errors; the threshold setting module determines a monitoring threshold interval; the data output module generates standardized data; the system realizes comprehensive monitoring of the chip state through cooperation of multiple modules, and the operation safety and stability are improved.

The utility model belongs to the technical field of carbon molecular sieve production equipment, and discloses a flower mud material crushing conveyor line which comprises crushing equipment, a bottom belt conveyor, an inclined lifting belt conveyor and a vibrating screen, a sunken main pit is formed in the workshop ground of a flower mud crushing station, the crushing equipment is installed in the main pit, and the inclined lifting belt conveyor is installed in the main pit. A feeding hopper of the crushing equipment is removed towards the outer side wall, and the bottom of the feeding hopper is connected through a horizontal steel plate, extends and is connected to the workshop ground in a lap joint mode. The bottom belt conveyor is horizontally connected below a discharge port of the crushing equipment, the bottom end of the inclined lifting belt conveyor is connected at the discharge end of the bottom belt conveyor, and the high end of the inclined lifting belt conveyor inputs crushed flower mud materials to a feed port of the vibrating screen. According to the flower mud material crushing conveying line, crushing equipment is installed in a pit mode, the feeding difficulty is lowered, and the operation safety is improved.

The invention relates to the technical field of photovoltaic energy regulation and control, in particular to a photovoltaic energy supply method and system driven by load sensing of a bridge structure. The method comprises the following steps: acquiring load response data through sensors arranged at key parts of a bridge; carrying out load sensing feature extraction according to the load response data to obtain load sensing feature data; performing load energy regulation and control mapping on the load sensing characteristic data to obtain photovoltaic regulation and control data; acquiring historical traffic flow data, and performing digital twinborn body construction according to the historical traffic flow data and a preset bridge-vehicle coupling model to obtain bridge-vehicle twinborn body data; and performing energy regulation and control response according to the photovoltaic regulation and control data and the bridge vehicle twinborn body data to obtain photovoltaic regulation and control response data. According to the invention, response control is carried out by combining twinborn body data and photovoltaic regulation and control data, so that the timeliness and execution precision of energy allocation are effectively improved, and the operation safety of a bridge structure and the utilization efficiency of renewable energy sources are enhanced.

The invention discloses an electric vehicle multi-source fault diagnosis and early warning method based on a decision tree model, and belongs to the field of intelligent diagnosis and operation and maintenance of new energy vehicles. According to the method, various data sources generated in the running process of the electric vehicle are comprehensively utilized, and the data sources comprise battery management system (BMS) alarm data, running state label-free data and battery monomer cycle life data. Through feature engineering construction and mutual information analysis, feature variables strongly related to faults are extracted, an up-down sampling strategy is adopted to optimize data balance, and decision tree classification models are constructed for various typical faults respectively. After the model is trained, the model is deployed to a cloud platform, and online state monitoring, real-time fault early warning and alarm reason tracing are realized. The method has the advantages of being high in interpretability, high in diagnosis accuracy, convenient to deploy and the like, is suitable for an electric vehicle full-life-cycle health management system, and can remarkably improve operation safety and maintenance efficiency.

The invention relates to the technical field of battery management of hybrid power vehicles, in particular to a hybrid power semitrailer battery management system and a multi-mode balance control method, and the hybrid power semitrailer battery management system comprises a data acquisition module, a main control module, a balance execution module, a thermal management module, a communication interface module and a safety protection module. Accurate battery state estimation and dynamic parameter updating are realized through an advanced algorithm and a model, a decision basis is provided for equalization and thermal management, an active and passive hybrid architecture and an intelligent topology switching strategy are adopted, energy management between battery cells is efficiently realized, energy waste is avoided, wind speed and wind direction are dynamically regulated and controlled by applying reinforcement learning, and energy consumption is reduced. The temperature consistency of the battery cell is maintained with low energy consumption, the energy utilization efficiency, the state control precision and the operation safety of the battery management system are remarkably improved, the service life of the battery is effectively prolonged, and stable operation of the system is guaranteed.

The invention discloses a broken sample anti-adhesion and waste taking device and method under an automatic mode of a tensile testing machine, and relates to the technical field of tensile testing machines. The clamp comprises a clamp body, a horizontal pushing type driving mechanism, a clearance, a gas spring ejection mechanism, a manipulator and a control system. A gap (delta = 30mm) is reserved to form a manipulator operation window, so that the problem of failure in grabbing of the fractured sample is solved; the gas spring ejection mechanism pushes the ejection head to extend out by 3mm with the thrust of 20N, and the adhered sample is forcibly separated; the clamping force of the horizontal pushing type driving mechanism reaches 30 MPa, and the maximum opening stroke exceeds 100 mm. All the components are coordinated through a PLC, the processes of sample feeding, tensile sample breaking treatment and separation and recovery are completed, the clamping face state is detected in real time through a laser obstacle avoidance sensor, and operation safety is guaranteed. Manual intervention is eliminated, the automatic compatible defect is overcome, and the automatic testing efficiency of the tensile testing machine is improved.

The embodiment of the invention provides a molten iron blending control system and method after blast furnace reblowing. The system comprises a molten iron monitoring subsystem, an iron blending control subsystem, an intelligent scheduling subsystem and a central processing unit. The central processing unit receives slag content associated data detected by the molten iron monitoring subsystem, monitoring parameters collected by the iron blending control subsystem and production associated information collected by the intelligent scheduling subsystem and inputs the slag content associated data into a slag content monitoring model so as to obtain slag content information through a machine learning algorithm. And first early warning information is generated according to the slag content information and the control reference data. And the iron blending speed and the iron blending angle in the iron blending process parameters can be calculated according to the monitoring parameters, the slag content information and the control reference data. And according to the production associated information and the iron exchange process parameters, an optimal iron exchange plan is generated by using an operational research algorithm. According to the system, the operation safety and the production efficiency can be improved through cooperation of a plurality of subsystems.

The invention relates to the technical field of engineering machinery, and discloses an engineering machinery active safety control method and device based on multi-parameter analysis, and the method comprises the steps: collecting the multi-modal data of an environment where the engineering machinery is located based on a multi-modal data collection device, and constructing a dynamic model of the engineering machinery and the environment according to the multi-modal data, analyzing the multi-modal data through a dynamic model to obtain an environment data analysis result and an equipment data analysis result, determining an operation risk level of the engineering machinery according to the environment data analysis result and the equipment data analysis result, and determining an optimal working path of the engineering machinery according to the multi-modal data. And generating a safety control strategy according to the operation risk level and the optimal working path. Therefore, by implementing the method, the evaluation accuracy of the operation risk can be improved, the probability of misoperation of operators is reduced, the operation accuracy and reliability of the engineering machinery are enhanced, and the operation efficiency, the operation stability and the operation safety of the engineering machinery are further improved.

The invention provides a method for systematically monitoring aircraft pilot and air traffic control (ATC) radio communications to detect predefined aviation-specific keywords indicative of operational conditions affecting flight safety or efficiency, such as turbulence, icing, or visibility constraints. Detected keywords and semantic equivalents from voice transmissions are transformed into structured data formats. These structured data are correlated with Automatic Dependent Surveillance-Broadcast (ADS-B) data, including precise aircraft position, altitude, heading, and speed. Leveraging this integrated data, the system generates automated, quantitative visualizations, such as condition-specific heatmaps or other graphical representations, illustrating spatial distributions of reported in-flight phenomena like turbulence, icing, or hazardous conditions. These visualizations enable air traffic controllers, pilots, and aviation stakeholders to rapidly assess and disseminate real-time observations and historical patterns of flight hazards, thereby significantly enhancing situational awareness, operational safety, and decision-making effectiveness without manual input or subjective interpretation, improving overall aviation operational efficiency and safety.

The invention discloses a plateau high-risk operation safety monitoring and early warning system and method based on multi-source perception, and the system comprises six units: an environment parameter multi-dimensional collection and integration unit and an operation equipment state full-dimensional monitoring unit, and can collect multi-source heterogeneous data, such as plateau operation environment parameters, equipment operation states and personnel signs, in real time. After integration of the multi-source data heterogeneous fusion processing unit, the danger situation analysis unit mines potential correlation of the data, and then accurate early warning is achieved through the high-risk operation multi-source danger perception early warning unit in combination with a dynamic threshold value. The method comprises the steps of data acquisition, format conversion and fusion, deep analysis, danger judgment, early warning release and the like. According to the invention, through a multi-source data integration and optimization algorithm, the limitation of single data acquisition and insufficient analysis capability of a traditional monitoring and early warning technology is broken through, the plateau high-risk operation danger can be monitored comprehensively and dynamically, and the operation safety guarantee level is effectively improved.

The invention discloses a scene-oriented rail transit operation business process standardization design method, and relates to the technical field of urban rail transit standard digital transformation, and the method comprises the steps: carrying out the classification and grading processing of an urban rail transit standard file and an urban rail transit operation standard, and obtaining machine readable standard data; based on the service architecture, performing service splitting processing on the machine readable standard data to obtain professional data containing a multi-level interface; according to the professional data, constructing a scene-based operation knowledge graph; carrying out secondary disassembly and recombination processing on the scene-based operation knowledge graph to obtain minimum scene unit data; and performing systematization processing on the minimum scene unit data to obtain a standardized operation business process. According to the invention, the operation management business process is standardized, so that the operation efficiency and the operation safety are improved.

The invention discloses a ceiling lamp mounting robot which comprises a vehicle body, a mechanical arm, a lamp lifting platform, a lampshade mounting device, a punching and screw tightening device, a wiring device and a particle mounting device. The mechanical arm is arranged on the vehicle body; the lamp lifting platform comprises a lamp mounting platform base, and the lamp mounting platform base is arranged on the vehicle body in a lifting manner; the punching and screw tightening device is used for punching a mounting hole and screwing in a screw, the wiring device is used for wiring the ceiling lamp, the particle mounting device is used for mounting expansion particles in the mounting hole, and when the lamp body is mounted, the mounting hole is punched in the ceiling lamp mounting position through the punching and screw tightening device; then, expansion particles are installed in the installation holes through a particle installation device, and then screws are screwed into the expansion particles through a punching and screw tightening device; and the lampshade mounting device is arranged on the lamp mounting platform base and is used for mounting the lampshade on the lamp main body. Manual operation can be reduced, the operation safety risk is reduced, and the installation precision is improved.

The invention discloses a safety performance analysis method for a large-section high-abrupt-slope inclined shaft full-process integrated construction intelligent trolley. The method comprises the steps that 1, the load of the trolley is calculated; step 2, carrying out finite element analysis on the trolley; step 3, calculating and rechecking the safety of the trolley; the trolley is divided into six parts including a needle beam module, an inner frame module, a template module, an inclined strut module, a stabilizer bar component and a pin shaft component, and stress nephogram representation and safety calculation are carried out respectively; step 4, calculating and re-checking the safety of the track; and 5, calculating and rechecking the safety of the bent section structure. According to the method, the bearing capacity of the trolley in the working process of the Lauba hydropower station can be accurately calculated, so that the working reliability of the trolley is evaluated, and the working safety is guaranteed.

The invention relates to the technical field of beacon lights, in particular to a beacon light capable of being installed through an unmanned aerial vehicle and the unmanned aerial vehicle. The beacon light comprises a beacon light body, a power module is fixed in the beacon light body, and a mounting groove is formed in the lower end of the beacon light body; a mounting groove is formed in the lower end of the beacon light body, a plurality of electromagnetic bolts which are distributed along the mounting groove in an annular array mode are arranged in the lower end of the beacon light body, a conical top base is fixed to the upper end of the beacon light body, and a magnetic switch is fixed in the conical top base and connected to a circuit between the power module and the electromagnetic bolts in series. The beneficial effects are that the unmanned aerial vehicle is utilized to realize automatic replacement of the beacon light device, an operator can perform remote operation without arriving at a site, the efficiency is high, manpower and material resources are saved, the operation safety is high, and the unmanned aerial vehicle has very high use value and popularization significance.

The invention relates to the technical field of voice broadcasting, in particular to a voice broadcasting system for an oxygen source compressor, and adopts the technical scheme that the reliability and the control precision of signal acquisition are remarkably improved through intelligent signal recognition, a composite filtering algorithm and a fault-tolerant control mechanism; the control reliability and the voice broadcast accuracy are ensured through triple guarantee of time sequence closed-loop control, a double-relay interlocking mechanism and voice feedback verification, the reliability of the voice broadcast system is improved through digital coding triggering, environment self-adaptive output and multiple safety protection design, and the voice broadcast system is more reliable through intelligent medium recognition, dynamic loading optimization and multiple safety mechanisms. The plug-and-play and reliable operation of the multi-language system is realized, and the mechanical signal of the oxygen source compressor is directly converted into the control signal of voice broadcast through the switching characteristic of the electromagnetic relay, so that the real-time voice prompt of the operation state of the equipment is realized, the operation safety is improved, the complexity and cost of the system are reduced, and the system can be conveniently integrated into the existing equipment.