69results about How to "Improve reaction speed" patented technology

The invention relates to the technical field of force feedback handles, in particular to a remote surgical robot control system based on a force feedback handle and a control method thereof. The method comprises the following steps: carrying out multi-dimensional force data acquisition on an end effector of the surgical robot, and carrying out contact force size, direction and time sequence feature extraction to obtain multi-dimensional force feature data; performing surgical operation safety baseline analysis according to the multi-dimensional force feature data to generate surgical operation safety baseline data; performing dynamic force feedback threshold calculation according to the surgical safety operation baseline data to obtain force feedback threshold range data; and performing adaptive compression processing on different force feedback signals according to the force feedback threshold range data to obtain dynamic force feedback control parameters. Through real-time control instruction optimization and a closed-loop feedback strategy, the system can quickly respond to an operation intention, early warning is carried out on potential risks, and it is ensured that the operation process is safer and more reliable.

The invention relates to the technical field of obstacle avoidance early warning, in particular to an obstacle avoidance early warning method and system for a robot. The method comprises the following steps: acquiring motion data and moving target point data of a robot; robot motion mode classification is conducted on the robot motion data, and a robot motion mode and a robot static mode are generated; performing environment detection on the moving target point data by using a built-in laser radar of the robot according to the static mode to obtain standard static environment detection data; and planning the path according to the standard static environment detection data, and generating initial running path planning data of the robot. According to the invention, the obstacle avoidance early warning precision and real-time performance of the robot in a complex environment are improved by accurately distinguishing static and dynamic objects, reconstructing the motion trail and planning and adjusting the path.

The invention relates to the technical field of wastewater treatment, in particular to a generation method for a chemical production wastewater treatment system control model. The method comprises the following steps: collecting chemical wastewater data by using an online monitoring instrument, wherein the chemical wastewater data comprises tin-containing wastewater data and etching liquid waste liquid data; determining a wastewater recovery control stage according to the chemical wastewater data; constructing a wastewater control model by utilizing chemical engineering simulation software based on the wastewater recovery control stage; inputting the chemical wastewater data into a wastewater control model, simulating a wastewater recovery control process by using simulation software to obtain wastewater recovery control data, and performing control abnormality judgment on the wastewater recovery control data to obtain abnormal wastewater data; the high-definition industrial camera is used for collecting images of the waste water sedimentation tank, and a centrifugal pump image is recognized and obtained from the images of the waste water sedimentation tank. According to the method, wastewater recovery control is optimized based on a wastewater treatment technology, and the wastewater recovery efficiency and the anomaly detection rate are remarkably improved.

The invention discloses a dynamic deviation rectifying method and system for sliding and lifting of a concrete sliding formwork of an ultra-large special-shaped vertical shaft. The method comprises the following steps that an ultra-large special-shaped vertical shaft model is established; configuring a deflection monitoring instrument; measuring the deflection amount of the sliding mode and generating measurement data; analyzing and processing the measurement data and generating a deviation correction control signal; deviation rectifying equipment performs slip form deviation rectifying; verifying a deviation correction result; and performing real-time dynamic analysis on the measured slip form deflection data, and generating a real-time dynamic deviation correction control signal to control deviation correction equipment to complete dynamic deviation correction of the slip form. The position, the posture and the motion state of the sliding mode can be monitored in real time, then measurement data are processed, and finally a deviation rectification control signal is generated to control deviation rectification equipment, so that the dynamic real-time deviation rectification work of the deflection of the sliding mode is realized. Therefore, high-precision, high-efficiency and high-adaptability dynamic deviation correction is realized, dependence on manual operation is reduced, high construction cost is reduced, adaptability and flexibility are enhanced, and safety and reliability of construction are improved at the same time.

The invention relates to the technical field of temperature control, in particular to a traditional Chinese medicine raw material extraction process temperature control system and method.The system comprises a real-time environment monitoring module, a temperature prediction adjusting module, an abnormal temperature analysis module and a temperature control optimization response module; collecting a temperature signal of the traditional Chinese medicine raw material extraction equipment, and recording the humidity change of the extraction environment. According to the invention, through real-time acquisition and analysis of temperature and humidity data, the precision and the reaction speed of temperature regulation are further improved, so that even tiny temperature fluctuation can be detected and brought into regulation, through temperature prediction, the system can effectively predict the future temperature change trend, and through the combination of the prediction capability and the instant reaction, the real-time performance of the system is improved. The temperature in the extraction process is maintained in the optimal state, the extraction rate and quality of effective components are greatly optimized, and due to timely recognition and regulation of abnormal temperature points, potential quality problems are prevented, and energy consumption is reduced.

The invention relates to the technical field of network advertisements, in particular to an advertisement data management system based on market trend analysis, which comprises a data acquisition module, an analysis module, a prediction module, a conversion rate calculation module and an adjustment module. The advertisement effect is reflected by acquiring click and purchase data after advertisement putting, the change trend of user behaviors is accurately recognized through the analysis module, and the user change rate is calculated, so that data support is provided for an advertisement putting strategy, and the advertisement putting strategy is more accurate by analyzing historical data, predicting the future purchase trend and comparing with predicted data in real time. The conversion rate change of the advertisement is accurately evaluated, a basis is provided for optimizing the advertisement effect, whether the advertisement putting duration needs to be adjusted or not is judged according to the comprehensive analysis of the user change rate and the conversion rate change rate, efficient utilization of advertisement resources is ensured, the accuracy and flexibility of advertisement putting are remarkably improved, the conversion rate and the return on investment of the advertisement are facilitated, and the user experience is improved. And continuous optimization and improvement of the advertisement effect are realized.

The invention discloses a time series data anomaly detection model construction method and an anomaly detection method and system, and the method comprises the steps: reconstructing time series data through employing a model constructed based on a TCN-LSTM-CMA auto-encoder, and generating reconstructed data; calculating a reconstruction error by comparing the time sequence data and the reconstruction data before and after reconstruction; and according to the calculated reconstruction error, carrying out anomaly detection by adopting an isolated forest algorithm, and identifying abnormal data in the time series data. The invention provides a brand-new TCN-LSTM-CMA auto-encoder model construction method, and the method is combined with an isolated forest method to carry out time series data anomaly detection. According to the method, the defects of an existing anomaly detection method in the aspects of precision, adaptability and robustness are overcome. The method has a wide application prospect in the aspect of time series data anomaly detection in the fields of industrial monitoring, network security and the like.

The invention relates to a TPA-LSTM-based shunting area wet and slippery road surface vehicle type-based dynamic early warning and speed guiding method. The method comprises the following steps: S1, collecting traffic flow operation time sequence data in a highway shunting area wet and slippery road surface scene; s2, predicting speed limit values of different vehicle types for safe passing on the wet and slippery road surface in the shunting area; s3, formulating early warning information release content; s4, determining an early warning information issuing mode; s5, determining an information issuing position of the highway shunting area, wherein the information issuing position is comprehensively determined according to an existing shunting area ETC portal layout principle in combination with a warning information issuing standard; and S6, early warning information is pushed to the vehicle end, and the ETC door frame receives the optimal passing speed information of the wet and slippery road surface pushed by the traffic management background and issues the information to vehicle-mounted OBU equipment with a voice broadcast function of the vehicle. According to the method, the real-time performance, the dynamic adaptability, the personalized early warning and the driver response effect are remarkably improved, so that the occurrence rate of accidents in the diversion area in a wet and slippery road scene in rainy days is greatly reduced.

The invention discloses a dance formation self-organization control method based on a robot group. The method comprises the following steps: S1, obtaining dynamic changes of light frequency, color and intensity through a spectrum camera; s2, judging an effective light source and an invalid light source, and removing the invalid light source to form a target light signal; s3, converting the optical signal into a digital signal through a photoelectric converter and a digital signal processor, and extracting the characteristics of the digital signal to form a characteristic instruction; s4, comparing the feature instruction with a predefined action matching database in real time, and outputting a robot action instruction; s5, analyzing the characteristics of the received digital signal, predicting an action instruction at the next moment, and generating the next action instruction in advance; s6, generating a robot action track by using a path planning algorithm; and S7, adopting a distributed control strategy, dynamically adjusting the motion track, and completing dance arrangement. According to the invention, dance arrangement of the robot group is controlled through light, and diversity of dance of the robot group is realized.

The invention provides an unmanned aerial vehicle intelligent adaptive scheduling method and system based on a large model, and the method comprises the steps: carrying out the type selection of a large model according to the specific task demands and computing resources of an unmanned aerial vehicle system, and carrying out the fine adjustment of a specific task field of the selected large model; integrating a plurality of professional models for executing different task requirements in the unmanned aerial vehicle system; for different task scenes, large model analysis judges whether a specific professional model needs to be activated or not, and the professional model is selected for task processing when needed; the large model confirms a professional model needing to be called, and automatically extracts and transmits required parameters to the professional model based on the collected environment information and task instructions; and the professional model receives the parameter information transmitted by the large model, executes the corresponding subtask, and feeds back an execution result to the large model, so that the large model performs continuous learning optimization. According to the invention, the unmanned aerial vehicle can complete the task more quickly, and the accuracy and reliability of task completion are improved.

The invention relates to a braking control method based on the comfort of an automatic driving vehicle, which comprises the following steps of: 1, collecting the speed and distance information of a front obstacle, and analyzing the collected road information and vehicle information; comprehensively judging whether the condition is an emergency condition or not by combining the current speed of the vehicle, the speed of the front vehicle, the distance information with the obstacle and the like; 2, learning a Q matrix in model prediction control through a TD3 deep reinforcement learning algorithm; 3, the model prediction control model estimates the current braking stage according to the information input data, and calls a Q matrix which is suitable for the current stage and has the best comfort from a strategy library to carry out optimization solution; 4, calling the trained Q matrix to carry out optimization solution so as to generate a most comfortable control sequence; and 5, the control sequence is transmitted to a vehicle control module for signal conversion, braking torque is generated, and the pitch angle of the whole vehicle is made to be within a comfortable range.

The utility model relates to the field of polyurethane spraying devices, in particular to a polyurethane spraying device for cold storage construction, and aims to solve the technical problems that an existing polyurethane spraying device for cold storage construction is low in automation degree, and a worker needs to hold a spray head by hand for operation. According to the technical scheme, the polyurethane spraying device for refrigeration house construction comprises a platform car, a spray head, a heating assembly, a stirring assembly and a lifting assembly; a nozzle is arranged on the platform car, a heating assembly is mounted on the platform car, a stirring assembly is mounted on the platform car, and a lifting assembly for adjusting the height of the nozzle is mounted on the platform car; the lifting assembly capable of adjusting the height of the spray head is additionally arranged on the polyurethane spraying device, the spray head can be driven by electric energy to ascend and descend automatically, the height of the spray head does not need to be changed through handheld operation of a worker to spray the wall face of the refrigeration house, and the problems that an existing polyurethane spraying device for refrigeration house construction is low in automation degree and high in spraying efficiency are solved. And a worker needs to hold the nozzle by hand for operation.

The invention relates to the technical field of supply chain analysis, in particular to a supply chain cooperative processing method based on digital service, which comprises the following steps: a central processing unit analyzes demand fluctuation through a trend analysis algorithm to generate a demand fluctuation characteristic model; based on the demand fluctuation characteristic model, a fault-tolerant threshold value of each node is set, and the fault-tolerant threshold value comprises a resource redundancy range, logistics delay tolerance and inventory buffer capacity; on the basis of the demand fluctuation characteristic model and the fault-tolerant threshold value, predicting a future demand peak value and a future demand valley value of the supply chain in real time by using an AI algorithm, and dynamically adjusting resource configuration of each node through resource allocation; and an inter-node cooperative fault-tolerant mechanism is established, so that when a certain node exceeds a fault-tolerant threshold value, the demand pressure is relieved by allocating resources of other nodes. According to the invention, under the condition that the demand fluctuation is relatively large, the system can flexibly respond and rapidly adjust, so that the adaptability and the reaction speed of the supply chain are improved.

The invention relates to the technical field of underwater robot formation, in particular to an underwater unmanned underwater vehicle cluster defense confrontation method, which utilizes an underwater unmanned cluster to make up the defect of insufficient functions of a single platform by means of the number advantage, and aggregates various underwater platforms with different functions to form a common body capable of completing a given task together; a traditional expensive large manned platform is replaced by a large number of small-size low-cost distributed unmanned platforms, and the distributed unmanned platform has the advantages of being high in efficiency, low in cost, reconfigurable and capable of executing multiple tasks, is used for underwater defense and resistance, and can greatly increase the underwater reconnaissance search range and improve the response speed and the confrontation effect.

The invention relates to the technical field of financial science and technology, in particular to a transaction sharing method based on a delivery service platform. According to the invention, through transaction behavior data analysis and evaluation, the accuracy, timeliness and cost effectiveness of each trader are analyzed in combination with historical transaction data, and the platform can effectively identify traders with good performance and potential risk traders; through intelligent recommendation and strategy optimization, the platform can continuously improve a transaction sharing strategy, ensures that a decision more meets market requirements, and improves a transaction effect. By adopting an encryption algorithm and an asymmetric encryption means, effective privacy protection can be achieved on sensitive information in transaction data; by means of time sequence analysis based on the ARIMA model, the platform can predict market changes in real time, take corresponding actions according to different risk levels, send early warning information in time and help traders to make responses quickly.

The utility model discloses a photovoltaic panel fault intelligent detection circuit and instrument, comprising a photovoltaic cell string current detection circuit, a voltage detection circuit, a temperature monitoring circuit, an insulation resistance detection circuit, a data acquisition and processing unit and a power supply management circuit which are connected with each other. The photovoltaic cell string current detection circuit is used for monitoring current of each string of photovoltaic cells, each string of photovoltaic cells is correspondingly provided with a Hall effect sensor, a shunt resistor and an amplifier, and the voltage detection circuit is used for monitoring open-circuit voltage and working voltage of a photovoltaic panel and comprises a high-impedance voltage follower and a differential amplifier. The temperature monitoring circuit is used for monitoring the surface temperature and the environment temperature of the photovoltaic panel in real time and comprises a thermocouple and a signal conditioning circuit, and the insulation resistance detection circuit is used for detecting the insulation performance of the photovoltaic panel and a connecting line of the photovoltaic panel, measuring the leakage current or impedance change of the photovoltaic panel and judging the insulation condition by applying high-voltage pulse or alternating-current voltage to a photovoltaic array.

The invention belongs to the technical field of anhydrous hydrogen fluoride production, and particularly relates to a feeding and conveying device for anhydrous hydrogen fluoride production. A discharging pipe is arranged at the bottom of the raw material box; the bottom of the raw material box is fixedly connected with a fixing frame; the end part of the discharging pipe is fixedly connected with a material conveying pipe; the end part of the material conveying pipe is fixedly connected with a motor; the output end of the motor penetrates through the end part of the conveying pipe; the output end of the motor is fixedly connected with a spiral blade; the spiral blade is mounted in the middle of the conveying pipe; a drying assembly, a screening assembly and an anti-blocking assembly are arranged in the middle of the raw material box; a cleaning assembly is mounted in the middle of the conveying pipe; a sealing assembly is mounted in the middle of the raw material box; by means of the structure, extra drying and screening treatment in the anhydrous hydrogen fluoride production raw material feeding and conveying process can be reduced, a large amount of energy consumption and time are effectively reduced, and therefore the problem that the production efficiency of anhydrous hydrogen fluoride is reduced in the whole production period is solved.

Provided is a method for preparing a recycled ABS resin including: preparing an extrusion feed including an acrylonitrile butadiene styrene (ABS) base resin including polyurethane and a metal carboxylic acid salt or a hydrate of the metal carboxylic acid salt, and supplying the extrusion feed to an extruder to perform a depolymerization reaction of the polyurethane and extrude the extrusion feed, wherein a master index (M) value satisfies 0.2≤M≤0.6.

The invention relates to the technical field of lithium battery thermal runaway suppression, and discloses a simulation system for lithium battery thermal runaway suppression by multi-particle-size water mist, which comprises a data acquisition module for lithium battery temperature acquisition, the temperature monitoring module is used for monitoring and predicting the temperature of the lithium battery and correcting the output of the temperature monitoring unit to monitor and predict the temperature of the lithium battery; the water mist control module is used for controlling the spraying type of particle size water mist and controlling the spraying momentum of fog drops; the suppression analysis module is used for performing suppression result analysis on the thermal runaway of the lithium battery; the feedback module is used for feeding back battery thermal runaway temperature response data and a particle size water mist cooling effect; according to the invention, higher monitoring precision can be ensured, the diameter of water mist and the momentum of fog drops are allowed to be adjusted according to different conditions, and a targeted inhibition effect is realized.

The invention relates to the technical field of energy storage power supply management, in particular to a control method, system and device for an energy storage power supply battery pack and a medium, and the control method for the energy storage power supply battery pack comprises the steps: obtaining a plurality of interrupt signals generated by insertion of each battery module in real time, and sorting the interrupt signals to obtain an interrupt signal sequence; closing a corresponding interrupt pin based on a signal sequence in the interrupt signal sequence, and reading a default ID of each battery module connected to the host; generating corresponding battery numbers according to the default IDs of the battery modules, integrating the battery numbers to form a battery number list, and storing the battery number list in a host; and obtaining each battery state based on the battery number, obtaining battery current data according to each battery state, and performing energy equalization processing on each battery pack based on the battery current data. The method has the effects of automatically identifying the battery packs and realizing energy balance among the battery packs.

The utility model relates to the technical field of copper smelting, and discloses a copper smelting fire extinguishing device which comprises a sand storage box, a limiting ring is arranged at the top of the sand storage box, a sealing cover plate is fixedly installed at the top of the limiting ring through bolts and nuts, a first sealing ring is arranged between the limiting ring and the sealing cover plate, and a second sealing ring is arranged between the limiting ring and the sealing cover plate. And a plurality of groups of through holes are formed in the outer surface of the sand storage box. According to the fire extinguishing device for copper smelting, through the sand discharging valve, a worker drives the output end of the sand discharging hose to move to the position above a fire ignition point, and after the sand discharging hose moves to the position above the ignition point, the sand discharging hose controls the output end of the sand storage box to communicate with the sand storage box through the sand discharging valve; sandy soil in the sand storage box enters the sand discharging hose through the sand discharging valve under the action of the conical appearance of the sand storage box and gravity, the sand soil in the sand discharging hose covers the surface of a fire ignition point from the output end of the sand discharging hose, the extinguishing speed and the reaction speed of the device are increased, the fire extinguishing effect of the device is improved, and therefore the practicability of the device is enhanced.

The utility model relates to a quantitative feeding reaction kettle for production, which belongs to the field of reaction kettles and comprises a reaction kettle body, support rods fixedly connected to four corners of the bottom of the reaction kettle body respectively and a bottom plate fixedly connected among the bottom ends of the four support rods, and a feeding structure for quantitative feeding is arranged at the top of the reaction kettle body. The feeding structure comprises a proportional valve fixedly connected to the top of the reaction kettle body, a stock bin fixedly connected to the top end of the proportional valve and two feeding pipes fixedly connected to the top of the stock bin, and the top of the stock bin is provided with a stirring assembly used for improving the fluidity of materials; the left side and the right side of the stock bin are each provided with a heating assembly used for preheating materials. According to the production reaction kettle with the quantitative feeding function, the fluidity of materials is improved through the stirring assembly, it is ensured that the materials are evenly distributed when entering the reaction kettle, meanwhile, the stirring device is combined with the preheating assembly, preheating treatment on the materials is achieved, and the reaction speed and efficiency are improved.

The utility model relates to the technical field of experimental equipment, in particular to a boron trifluoride gas experimental device which comprises a reaction kettle, a condenser, a first purification tower, a second purification tower, a third purification tower and a gas buffer tank which are sequentially connected through gas pipelines. The reaction kettle is composed of a speed reducer, a stirring paddle, a kettle cover and a kettle body, a cavity is formed in the kettle body, a jacket is arranged outside the cavity, a heat preservation layer is arranged on the outer wall of the jacket, and a gas inlet and outlet is formed in the tail end of a gas pipeline on one side of the top of the gas buffer tank. According to the boron trifluoride gas experimental device, the temperature control in the reaction process is more accurate and stable due to the design of the jacket and the thermal insulation layer of the reaction kettle, so that the reaction efficiency is improved, the reaction speed and efficiency are further improved, impurities and particulate matters in boron trifluoride gas are effectively removed, and the purity of the gas is remarkably improved.

The utility model discloses a kind of mixed reaction devices for aminosulfonic acid production belong to aminosulfonic acid technical field, including fixed plate, the top of the fixed plate is equipped with cylinder, the bottom surface of the cylinder is inlaid with mixing mechanism, the outer surface of the cylinder is connected with a group of support rods, the bottom surface of each support rod is connected with the upper surface of fixed plate. Through the design of motor and connecting rod, it is convenient for connecting rod to rotate, while driving the rotation of mixing plate, while mixing and stirring the raw materials inside the cylinder using the mixing plate, at this time, through the cooperation of dispersion plate and mixing plate, it is convenient for raw material mixing and dispersion, while being beneficial to uniform mixing of raw materials, and then it is convenient to speed up its mixing and reaction speed, using the design of fan, control valve and straw, it is convenient to suck the gas inside the cylinder, and it is convenient for gas discharge to the inside of box, while being beneficial to the treatment and discharge of gas by multiple filter elements, thereby reducing the influence of gas on surrounding environment.

The invention relates to the technical field of air pressure sensing detection, in particular to an air pressure feedback method and equipment based on high-precision pressure sensing. The method comprises the following steps: carrying out pressure sensing element space positioning calculation on air pressure feedback equipment, carrying out topological distribution fitting, and constructing an element topological distribution diagram; acquiring a historical pressure sensing sample of the high-precision pressure sensing element; performing dynamic pressure deformation rendering on the element topology distribution map based on a historical pressure sensing sample, thereby constructing a dynamic pressure deformation visual network; performing environment barometric disturbance mapping on the dynamic pressure deformation visual network according to the barometric feedback equipment to obtain a barometric disturbance visual network; and carrying out real-time operation monitoring based on the barometric disturbance visual network, and carrying out pressure visual mapping to obtain a real-time pressure deformation visual network. According to the invention, efficient and accurate element air pressure feedback is realized.

The present invention relates to the technical field of electric variable monitoring and analysis, and in particular to a method and system for monitoring electric variables in a wide temperature range. The method comprises the following steps: obtaining thick film integrated circuit design data; performing circuit distribution functional characteristic analysis based on the thick film integrated circuit design data to generate circuit distribution functional characteristic data; collecting temperature partition electric variable distribution signals; performing potential representation quantitative data analysis of abnormal multi-temperature zone electric variable distribution based on the temperature partition electric variable distribution signals to generate abnormal multi-temperature zone electric variable distribution potential quantitative data; analyzing circuit distribution passive chip signal compensation mapping data based on abnormal multi-temperature zone electric variable distribution potential quantitative data; performing iterative closed-loop monitoring of temperature partition electric variable distribution signals based on circuit distribution passive chip signal compensation mapping data to generate iterative temperature partition electric variable distribution signals. The present invention realizes precise monitoring of electric variable parameters with temperature changes in complex circuit systems.

This invention discloses a method for intelligent verification and early warning of feeder protection settings across the entire distribution network, belonging to the field of power system relay protection technology. The method includes collecting relevant distribution network data and calculating positive-sequence components, establishing a Thevenin equivalent circuit model and iteratively optimizing parameters, calculating the operating current based on Thevenin parameters, verifying the level difference of adjacent feeder settings in real time, generating a list of compliant settings and distributing it to the protection device. The relevant distribution network data includes current and voltage. The method calculates the instantaneous current increment and performs a three-level decomposition using Daubechies 4 wavelets, extracting high-frequency detail coefficients d1-d3 for fault prediction, and performing Stockwell and Hilbert transform analysis on the current data based on the fault prediction results. This invention can significantly improve the response speed and processing capability of the power grid under sudden events, ensuring the safety and stability of power grid operation.

The present invention relates to a method for monitoring the height-climbing safety of transformer substation workers, and belongs to the field of target detection technology. The method comprises the following steps: extracting human body joint points from a video screen, and then connecting each pair of associated body parts through a posture line, and the posture line will be combined into the whole-body posture of the human body detected in the image; detecting and judging the climbing action of the worker; if it is detected that the worker has the climbing behavior, the protective measures for the climbing worker shall be identified: judging whether the safety belt and safety helmet are correctly worn according to the requirements, and specifically, using the YOLO algorithm to detect whether there is a corresponding object in the human body image area. When the present invention monitors the on-site video, the response time to the safety protection problem of personnel during the climbing period is about 3.4 seconds. The behavior of inadequate protection in climbing work can be alarmed in a very short time, which improves the detection accuracy and reaction speed, thereby greatly improving the safety problem in the climbing work of the transformer substation.

The utility model discloses an intelligent control box of automobile emergency starting, including central processing unit, LDO voltage stabilizing module, high -power relay device, reverse connection detection module, wire clamp inspection module, pilot lamp control module, button detection module and alarm prompt sounding device, wherein central processing unit is connected with battery power supply through LDO voltage stabilizing module, and is connected with relay, reverse connection detection module, wire clamp inspection module, pilot lamp control module, button detection module and alarm prompt sounding device respectively to realize unified control, battery power supply connects LDO voltage stabilizing module, and provides stabilized power supply to central processing unit through this voltage stabilizing module. Realized 12V and 24V battery's automatic identification, promoted the general property of intelligent control box of automobile emergency starting, integrated reverse connection protection, short circuit protection, undervoltage protection, alarm prompt and the like function, promoted the use safety of intelligent control box of automobile emergency starting.

The invention discloses an electromagnetic signal monitoring method and device based on deep learning in the technical field of electromagnetic signal monitoring. The electromagnetic signal monitoring method comprises the following steps: an electromagnetic signal monitoring process; carrying out deep learning on the electromagnetic signals; and the electromagnetic signal is subjected to an anti-electromagnetic interference process. According to the electromagnetic signal monitoring method and device based on deep learning, a proper high-performance device, a shielding scheme, an integrated design method and a deep learning model algorithm are adopted, monitoring and shielding strategies can be automatically adjusted according to real-time data through a deep learning model, manual intervention is reduced, the response speed and the processing efficiency are improved, and the electromagnetic signal monitoring method and device based on deep learning are suitable for popularization and application. Real-time data processing can be realized, a monitoring result can be quickly fed back, and potential interference can be timely dealt with.