1375results about How to "Reduce accidents" patented technology

The invention discloses a coal mine heat energy monitoring and cooling regulation and control method based on the Internet of Things, and relates to the technical field of coal mine heat energy monitoring and cooling regulation and control. The collected temperature data are transmitted to a central monitoring system in real time through an Internet of Things gateway; redundant temperature sensors are arranged at key positions, and data of the temperature sensors in the same area are regularly compared and verified. According to the invention, the monitoring robustness is improved through a redundant temperature sensor and a data fusion algorithm, a monitoring blind area caused by a single-point fault is avoided, and the accident risk is reduced; a self-adaptive learning algorithm is adopted to dynamically optimize a detection threshold value and a compensation strategy, so that the anomaly detection accuracy is improved, and false alarms and missing alarms are reduced; the temperature trend is pre-judged through a predictive control algorithm, cooling is conducted in advance, balance between safety and energy efficiency is achieved, overheating accidents are prevented, and energy consumption is reduced.

The invention relates to a coal mine potential safety hazard characterization method and system based on a knowledge graph, and belongs to the technical field of coal mine safety. The method comprises the following steps: data collection: collecting coal mine daily safety inspection records including hidden danger types, occurrence places, time and related descriptions; data preprocessing: cleaning, classifying and standardizing the collected data so as to facilitate subsequent knowledge extraction and graph construction; and knowledge graph construction: based on the preprocessed data, identifying key entities, extracting relationships among the entities, and constructing a coal mine potential safety hazard knowledge graph. Through the hidden danger correlation analysis and risk assessment module in the knowledge graph, the system can assess the risk degrees of different hidden dangers in real time and generate corresponding early warning information according to the assessment result, and the dynamic early warning mechanism enables managers to master the safety condition of a coal mine in time and quickly respond to potential safety threats.

The invention discloses an intelligent construction site construction safety supervision method and system based on artificial intelligence, and the method comprises the steps: obtaining an unmanned aerial vehicle aerial image and point cloud data every preset time period; generating a digital elevation model according to the point cloud data; elevation data are extracted from the digital elevation model; extracting ground feature features and edge features in the aerial image of the unmanned aerial vehicle; integrating the digital orthoimage, the ground feature features and the digital elevation model to obtain a vector diagram; matching edge features in an overlapped image in the aerial image of the unmanned aerial vehicle, and inputting the edge features into the machine learning model to generate an aerial triangulation model; creating a stereo image pair according to the aerial triangulation model, and generating a live-action three-dimensional model; integrating the live-action three-dimensional model and the vector diagram to obtain a construction site digital map; acquiring personnel position data; dangerous factors are determined, a potential safety hazard analysis warning area of the construction site is obtained through analysis, and the safety construction distance and the construction safety risk coefficient of the construction area are determined and displayed.

The invention discloses a safe airtight cold-resistant low-smoke flame-retardant control cable used in an explosion environment, and relates to the technical field of cables, a first hot melting pipe is filled with expanded graphite, the outer side of a wrapping tape is uniformly sleeved with protective iron rings at intervals, the outer sides of the protective iron rings are uniformly provided with fixing holes at intervals, and a communication port is formed between every two adjacent fixing holes; according to the invention, the heat insulation cotton, the compression-resistant rib, the protection iron ring, the arc-shaped elastic sheet, the arc-shaped frame and the elastic roll absorb and buffer external force, so that the compression resistance and impact resistance of the cable are enhanced; the aluminum hydroxide powder absorbs a large amount of heat and delays combustion, the expanded graphite in the first hot melting pipe is heated to expand, the expanded graphite is diffused to a gap between the shielding layer and the wrapping layer, flame is prevented from combusting to the interior of the cable, the working time is prolonged, and the economic loss is reduced.

The invention discloses an in-tunnel construction vehicle meeting scheduling system based on positioning equipment. The system comprises a basic service module which is used for storing basic data for business service analysis in an acquisition and collection mode; the business service module is used for carrying out detailed analysis of the corresponding service through the data acquired by the basic service, and providing an analysis result to the display end for display; and the display end module is used for displaying the analysis result of the business service module, wherein the display modes comprise a mobile phone APP, a webpage large screen, an LED panel, a tunnel loudspeaker and a tunnel traffic light. The system carries out weight grading on vehicle and personnel positioning labels by standardizing a tunnel construction process, and integrates data of avoidance points of a transverse tunnel. And in combination with an intelligent technology, efficient vehicle meeting scheduling, intelligent construction path planning and avoidance point path planning of the construction area are realized.

The invention relates to the related field of photovoltaic construction, in particular to a photovoltaic construction management system, which comprehensively analyzes video data and environmental sensor data, improves the accuracy and reliability of the monitoring effect, and can effectively reduce the blind area and false alarm rate of a single data source through the fusion of multi-modal data. According to the invention, a genetic algorithm and a decision tree algorithm are integrated, so that the system has strong learning ability, and the system can be continuously self-optimized according to historical data and operation logic to gradually adapt to different construction environments and working conditions; through regular updating and model training, the system can continuously improve the monitoring precision and the safety management level, and it is ensured that an efficient and stable operation state is always kept in long-term use; an analysis result is displayed through a visual platform, accurate defect positions and severity degree marks are provided, a detailed detection report can be automatically generated, long-term monitoring and data comparison are supported, and powerful technical support is provided for construction quality guarantee.

The invention discloses an intelligent vehicle-mounted application adjusting method and system based on a driving scene, and relates to the field of vehicle-mounted application, and the method comprises the steps: obtaining current real-time driving data, current external environment information and current position information, and matching a user behavior mode of a current vehicle in a preset behavior mode database according to the current real-time driving data, identifying a driving scene of a current vehicle according to the current external environment information and the current position information, and predicting an information type and a presentation mode required by a current driver according to the user behavior mode and the driving scene, and determining an information presentation mode and information presentation time in a preset application database according to the information type and the presentation mode, and presenting all the vehicle-mounted applications according to the information presentation mode and the information presentation time, and by implementing the method, the driving experience of a driver can be improved in a complex driving scene.

The invention relates to the technical field of coal mine safety supervision, and provides a coal mine safety supervision method, which comprises the following steps of data acquisition, data transmission, data analysis, artificial intelligence judgment, risk early warning, safety decision and event recording. According to the comprehensive coal mine safety supervision method and system, the safety management level of a coal mine is greatly improved, the occurrence probability of accidents is reduced, and the sense of safety and the working efficiency of miners are improved. In addition, through continuous data collection and analysis, the system can be continuously self-optimized to adapt to the change of a coal mine environment, and long-term safety production is realized. The popularization and application of the system undoubtedly bring revolutionary improvement to the safety management of the whole coal mine industry.

The invention discloses a soft foundation treatment method under the condition of reinforced flow-state muddy soft soil. According to the intelligent soft foundation treatment method, an intelligent monitoring and control system is introduced, the whole soft foundation treatment method achieves accurate monitoring and automatic adjustment of the construction process, and remarkable beneficial effects are achieved. Firstly, key parameters such as pore water pressure, soil deformation and underground water level are monitored in real time, so that engineers can quickly respond to changes of soil properties and timely adjust preloading load and vacuum degree, construction efficiency is optimized, and unnecessary construction period delay is reduced. And secondly, due to automatic data acquisition and processing, the accuracy and speed of data processing are greatly improved, personal errors are reduced, and the construction quality is ensured. In addition, the intelligent system can give out early warning in time when potential risks are found, construction safety is guaranteed, and the possibility of accidents is reduced.

The invention relates to the technical field of dangerous goods storage, and discloses a data twinborn early warning system and method for a dangerous goods storage area. The model establishing module is configured to establish a data twinborn model of the storage area according to the image information; the acquisition module is configured to acquire the environment information and the dangerous goods information of the storage area and display the information on the data twinborn model; the environment evaluation module is configured to obtain an environment evaluation value according to the temperature information and the humidity information and adjust the environment evaluation value according to the change value amplitude; the dangerous goods evaluation module is configured to obtain a dangerous goods evaluation value according to the complete state of the dangerous goods and adjust the dangerous goods evaluation value according to the gas leakage information; and the early warning module is configured to judge the early warning level of the storage area according to the comprehensive evaluation value and perform early warning. Storage of dangerous goods is monitored in multiple aspects, and the safety of storage materials is effectively evaluated.

The invention relates to the technical field of data processing, in particular to a hoisting state intelligent sensing and early warning system, method and equipment, and the system comprises an environment interference early warning module, a hoisting equipment abnormity early warning module, a hoisting operation abnormity early warning module and a hoisting system database, according to the intelligent sensing and early warning system, method and equipment for the hoisting state, the influence of environment interference, hoisting equipment abnormity and hoisting state abnormity on hoisting operation is comprehensively analyzed, and a comprehensive hoisting operation abnormity evaluation system is formed; the evaluation system not only can monitor the environmental interference degree of a hoisting operation site in real time, but also can perform analysis and early warning on hoisting equipment abnormity and hoisting state abnormity, and through comprehensive evaluation and early warning on hoisting operation, the emergency response capability of hoisting operation can be improved, and the safety of hoisting operation is improved. And therefore, the hoisting operation can still be kept stable and safe under the emergency condition.

The invention provides a model-based battery thermal runaway early warning system and method, and the method comprises the following steps: S1, building an electrochemical-thermal and electrochemical-expansive force coupling model, and obtaining a temperature change curve, a temperature rise rate curve, a voltage curve and an expansive force curve of a battery under different working conditions; s2, establishing a thermal runaway-expansive force coupling model, and obtaining a time-temperature curve, a time-temperature rise rate curve, a time-expansive force curve and a time-expansive force change rate curve of the battery in a thermal runaway stage; s3, determining a multistage safety threshold Xt of the battery according to the curves obtained in the step S1 and the step S2; and S4, carrying out battery thermal runaway early warning according to the battery working safety threshold Xt in the step S3. According to the invention, the accuracy and timeliness of lithium ion battery thermal runaway early warning can be improved.

The invention belongs to the technical field of aging state evaluation, and discloses a high-voltage dry-type bushing insulation aging state evaluation method based on frequency domain characteristics. According to the method, the FDS is adopted, and the aging state of the insulating material is evaluated according to the change of the complex capacitance, the complex dielectric constant, the dielectric loss factor and the like of a medium along with the frequency under a low-voltage sine alternating electric field. The FDS shows remarkable superiority in a plurality of aspects. The method comprises the following steps: firstly, measuring a dielectric constant and dielectric loss of an insulating medium in a wide frequency range by an FDS method so as to obtain response characteristics of the insulating material under different frequencies; according to the method, the frequency domain dielectric spectroscopy FDS is combined with the advantages of wide frequency range measurement, frequency domain feature recognition, comprehensive reflection of electrical characteristics and the like, so that accurate evaluation of the insulation aging state of the high-voltage dry-type bushing is realized. The safety and the stability of a power system can be improved, and faults and accidents caused by insulation aging can be reduced.

The invention provides a substation environment monitoring inspection control system and method, and relates to the technical field of power system monitoring. Comprising a holographic sensing subsystem and a data fusion control subsystem. The holographic sensing subsystem collects substation environment and equipment state data in real time and comprises a non-contact optical fiber sensor, a temperature and humidity sensor, a gas concentration sensor, an infrared camera, an ultraviolet camera, a visible light camera and a millimeter wave radar. The data fusion control subsystem carries out redundancy elimination, complementation and standardization processing on collected data, the intelligent analysis module carries out state analysis and fault prediction based on fused data, and the control instruction generation module generates an emergency control instruction according to an analysis result to realize closed-loop feedback control; the system improves the monitoring accuracy and response speed of the transformer substation through multi-sensor data fusion and intelligent analysis.

The invention relates to the technical field of storage tank safety monitoring, in particular to a visual real-time monitoring method and system for a digital floating disc of a storage tank. The method comprises the following steps: carrying out real-time floating disc signal acquisition on a full liquid receiving floating disc to obtain real-time floating disc sensing signal data, and carrying out data filtering preprocessing on the real-time floating disc sensing signal data to obtain floating disc sensing signal data; performing Kalman filtering data fusion on the floating disc sensing signal data to obtain real-time floating disc sensing fusion data; performing floating disc abnormal state detection on the real-time floating disc sensing fusion data to obtain floating disc abnormal detection data; floating disc early warning information integration is carried out according to the floating disc anomaly detection data, so that an abnormal floating disc alarm strategy is obtained; data of the full-liquid-receiving floating disc auxiliary mechanism is obtained, prevention and control strategy analysis is carried out, an abnormal floating disc prevention and control strategy is obtained, and the abnormal floating disc prevention and control strategy is uploaded to a controller to execute a floating disc prevention and control task. The safety of the storage tank can be improved.

The invention discloses an unmanned aerial vehicle safety scheduling optimization algorithm, and relates to the technical field of storage scheduling, and the algorithm comprises the steps: carrying out the modeling of a storage environment based on the position, shape and size information of goods shelves and mechanical equipment in a warehouse, and building a preliminary environment model; and scanning the environment by using a laser radar carried by the unmanned aerial vehicle to obtain environment data in the warehouse, and updating the environment model in real time in combination with the preliminary environment model. According to the unmanned aerial vehicle safety scheduling optimization algorithm, the accuracy and efficiency of a flight path are remarkably improved through an integrated path planning technology, the optimal flight path is customized for the unmanned aerial vehicle in combination with actual conditions of topography and landform of a storage area and obstacle distribution, redundancy and waste in the flight process are reduced, and meanwhile, the unmanned aerial vehicle safety scheduling optimization algorithm has good application prospects. And the path can be dynamically adjusted according to the real-time environment change to effectively deal with emergencies, so that the flight efficiency and safety are further improved.

The invention relates to an engine fault detection method based on multiple sensors and spectral data fusion, and the method comprises the steps: collecting the first spectral data, reference temperature and reference pressure of the tail flame of a normal engine, and extracting the ideal spectral characteristics of a target substance based on the first spectral data; acquiring second spectral data of engine tail flame of the to-be-detected engine, and acquiring actual spectral characteristics of the target substance based on the second spectral data; the actual tail flame temperature and the actual tail flame pressure of the engine tail flame of the engine to be detected are collected, and the actual spectrum characteristics are corrected to obtain actual spectrum correction characteristics; based on the ideal spectral feature and the actual spectral correction feature, obtaining a dynamic feature for judging whether the to-be-detected engine has a fault; constructing a dynamic threshold range; and judging whether the dynamic characteristics are abnormal based on the dynamic threshold range. The method can be flexibly and accurately used for engine fault prediction and timely alarm, and accidents can be fully reduced.

The invention discloses a power distribution network fault early warning method, system and device and a storage medium, and the method comprises the steps: carrying out the processing of the operation state data of a power distribution network according to a minimum redundancy and maximum correlation algorithm, and obtaining a corresponding dimension feature tag; performing classification processing on the data according to the dimension feature tags to obtain a balanced data set; constructing a target data model based on a weak classifier through a multi-dimensional integration strategy; and optimizing and integrating the target data model based on a gradient lifting decision tree algorithm to obtain a fault prediction model for fault prediction. According to the method, the integrated prediction model is constructed by using the multi-dimensional weak classifier, so that the state in the operation process of the power distribution network can be accurately predicted, the fault risk of the power distribution network can be early warned in advance, and a more effective fault maintenance strategy can be formulated, thereby reducing the occurrence of power distribution network accidents and improving the economy and safety of the power distribution network.

The invention relates to the technical field of intelligent chemical engineering, and discloses an intelligent chemical engineering construction safety and quality detection method based on big data, and the method comprises the following steps: 1, installing a monitor and a sensor; step 2, intelligent analysis; step 3, predictive maintenance; step 4, risk assessment; step 5, quality control; step 6, safety management; 7, accident prevention; 8, remote real-time management is carried out; step 9, decision support; step 10, intelligent reporting; and step 11, displaying an interface. According to the intelligent chemical engineering site construction safety and quality detection method and system based on big data, through real-time monitoring and risk assessment, the intelligent chemical engineering site system can improve the safety management level of a construction site and reduce accidents, and the system can predict potential safety risks and take measures to avoid the potential safety risks by utilizing predictive maintenance and accident prevention technologies; and by using big data and an intelligent optimization algorithm, the resource allocation and the construction process are optimized, and the construction efficiency is improved.

The invention provides an intelligent fully-mechanized coal mining electromechanical equipment cooperative control system, and relates to the field of coal mining. The intelligent fully-mechanized coal mine electromechanical equipment cooperative control system comprises a data acquisition module which is used for acquiring operation state data of all electromechanical equipment in a fully-mechanized coal mine in real time; the data processing and analyzing module is used for processing and analyzing the collected data in real time and identifying the running state and potential problems of the equipment; the cooperative control module is used for intelligently adjusting operation parameters of the electromechanical equipment according to an output result of the data processing and analyzing module, so that cooperative work among the equipment is realized; and the safety monitoring module monitors the running state of the equipment in real time, and immediately starts safety protection measures once an abnormal condition is found. The system can detect abnormal conditions in operation of the equipment in real time and give an alarm in time, so that the possibility of accidents is reduced, and when security threats are detected, the system can automatically execute preset emergency response measures.

The invention relates to the technical field of power industrial control network asset management, in particular to a power industrial control network security-oriented asset dynamic digital fingerprint construction system, which comprises a data acquisition module, a first determination module, a second determination module, an identification module, an adjustment module and a construction module. Through accurate multi-level data acquisition, behavior analysis and threshold adjustment, the security of an electric power industrial control network is remarkably improved, the system can acquire key behavior data of equipment in real time, such as the number of bytes of a data packet, the memory utilization rate and the number of login failures, and normal equipment and abnormal equipment are accurately identified through multi-stage screening, so that the security of the electric power industrial control network is improved. The system flexibly deals with the dynamic change of the equipment behavior by adjusting the byte number fluctuation threshold value, ensures the high efficiency and accuracy of the safety detection, and effectively solves the problems that the system cannot adapt to the network asset change and cannot identify the abnormal equipment in real time due to the dependence on a static fingerprint database and a fixed similarity threshold value.

The invention discloses a stage equipment comprehensive management method and system based on a digital twinning technology, and aims to carry out all-around real-time monitoring and intelligent management on all system modules of stage equipment, including light, sound equipment, an LED module and stage machinery, through integration of BIM, an Internet of Things technology and a high-precision 3D modeling technology. The system can accurately monitor the voltage, current, temperature and electric leakage conditions, and carries out automatic alarm and opening control based on a preset threshold value, thereby guaranteeing the safe operation of equipment. The system supports a full 3D scene interaction mode, a user can control the operation of equipment through one-key operation in an immersive environment, and all modules are comprehensively managed and monitored.

The invention discloses a vehicle cloud collaborative data acquisition method based on a central gateway, and relates to the technical field of information processing. The method comprises the following steps: periodically acquiring CAN / LIN data through central gateway equipment, and filtering, classifying, compressing and storing the CAN / LIN data; the ECU with the fault actively uploads fault information to the central gateway equipment; and the central gateway equipment packages and uploads the collected data and the received fault information to a cloud end in an MQTT transmission mode to carry out real-time monitoring and predict the running state of the vehicle. Through real-time monitoring and analysis of vehicle data, the state of the vehicle is comprehensively mastered, potential problems are found and solved in time, accidents are reduced, and the safety of the vehicle is improved; the data acquisition efficiency and utilization efficiency of the vehicle are improved; based on the remote diagnosis capability, the method is used for more convenient vehicle fault diagnosis and fault prediction analysis, improves the after-sales diagnosis efficiency, and reduces the fault analysis cost.

The invention discloses an intelligent port comprehensive management system based on big data, and relates to the technical field of port energy management, and the system comprises a data collection and integration module which is used for deploying a plurality of sensors in each key region of a port, and a data collection device which is used for collecting the data of the ship position, the cargo flow, the device state and the environmental condition in real time, and through real-time data collection and integration, management personnel can quickly know the operation condition of the port. The intelligent port comprehensive management system based on big data has the advantages of real-time data collection and integration, intelligent scheduling and operation optimization, and the system can quickly respond to port operation requirements and adjust resource configuration and operation strategies in real time, so that the waiting time of ships and cargoes is shortened, the loading and unloading operation and prediction analysis are optimized, and the management efficiency is improved. The resource utilization rate and the efficiency of the operation process are remarkably improved, and managers can make decisions more accurately according to the data analysis result, so that the operation cost is reduced, and the customer satisfaction is improved.

The invention discloses an intelligent early warning method for colorless tea drink production based on machine learning. The method comprises the following steps: acquiring data of colorless tea drink production; calculating the similarity between the production data value corresponding to the colorless tea drink production data and all production data values in the historical safety production data corresponding to the production data; establishing an intelligent early warning model of colorless tea drink production by using the obtained historical safety production data, and verifying the intelligent early warning model; an intelligent early warning model is adopted to carry out online detection on colorless tea drink production; through principal component analysis, partial least squares regression and support vector machine classifier machine learning technologies, the influence of single production parameter change on production safety and the potential safety hazard probability in the whole production process can be predicted more accurately; according to the method, the limitation of dependence on manual monitoring and experience judgment traditionally is overcome, potential risks are recognized in advance through data analysis and model prediction, and the safety of the production process is remarkably improved.

The invention is suitable for the technical field of monitoring management, and particularly relates to a civil engineering safety monitoring management method and system, and the method comprises the steps: S100, positioning the position of a potential safety hazard in a civil engineering construction site, carrying out the rating of the potential safety hazard, obtaining the control authority of a lighting device at the position, editing the lighting mode of the lighting device, and carrying out the recognition of the potential safety hazard; the illumination mode comprises normally-on and flicker, and establishing a corresponding relation between the rating and flicker frequency; and S200, recording the generation time of the potential safety hazard, cutting the potential safety hazard into a plurality of segments, mapping the grade into the segments, updating the flicker frequency, and constructing a monitoring lake. Through cooperation with the output template, the monitoring result of the potential safety hazard can be visually displayed, data support is provided for monitoring management, and through arrangement of the multi-level electronic fence, the safety of the position of the potential safety hazard is greatly improved, intruders are prevented from entering by mistake, accidents are greatly reduced, and the construction efficiency is improved.

The invention relates to a vehicle wading early warning system, which captures a real-time video stream of a road surface around a vehicle through a camera module, and extracts road conditions, waterlogging depth, weather changes and topographic features from the video stream in combination with an intelligent video analysis module based on a convolutional neural network (CNN) and a Transform architecture. The system queries historical data and real-time weather information through networking, analyzes the distance between a vehicle chassis and the ground and tire pressure changes, performs real-time wading risk assessment in combination with the accumulated water depth, can predict the change trend of the accumulated water depth through an accumulated water dynamic change prediction module, provides an early warning function, and improves the wading risk of a vehicle. The cross-motorcade wading early warning module enables multiple vehicles to share real-time wading information based on V2V communication and improves the collaborative early warning capability of the motorcade, and the satellite communication module sends compressed pictures, GPS position information and distress signals to a rescue center at regular time when the vehicles are in danger and synchronizes data to a cloud end during normal operation to provide support for subsequent rescue.

The invention provides a traffic light passing calculation method and system based on the Internet of Things. The method comprises the following steps: receiving a real-time data stream from an Internet of Things intelligent sensor network, and carrying out space-time consistency processing through a high-precision space-time synchronization technology to generate a traffic condition dynamic panorama; a causal inference algorithm is used for inferring a causal relationship, direct and indirect influence paths are calculated, a space-time sequence modeling technology is used for capturing space-time characteristics, a time-varying rule is simulated, and a future traffic state estimation model is generated; an evolutionary strategy optimization algorithm is used to simulate a natural evolutionary process, an optimal traffic light switching strategy is searched, a multi-objective optimization technology is used to consider a mutual exclusion objective, constraint conditions are introduced to carry out comprehensive evaluation, and a traffic light switching strategy evaluation result is generated; a feedback circulation mechanism is introduced, a model operation result is collected in real time, an adaptability improvement report is automatically formed, and a traffic light passing calculation scheme is generated. According to the technical scheme provided by the invention, the traffic light passing calculation efficiency is remarkably improved.

The invention relates to the technical field of energy storage risk prediction, and particularly discloses an electrochemical energy storage risk prediction method, which comprises the following steps of: determining a risk characteristic value of an electrochemical energy storage system, obtaining an abnormal deviation value of an operation environment of the electrochemical energy storage system, and obtaining a risk judgment threshold value of the electrochemical energy storage system; according to the method, the real-time operation state of the electrochemical energy storage system is monitored, whether the electrochemical energy storage system has risks or not is judged by combining a risk judgment threshold value of the electrochemical energy storage system, and the risk level of the electrochemical energy storage system with the risks is determined. According to the method, the problems that the existing risk management system is not easy to carry out and is lack of comprehensive analysis are solved, rapid response and implementation of effective rectification measures are facilitated, the accident occurrence probability is remarkably reduced, the efficiency and pertinence of maintenance work are improved, a perfect risk judgment threshold system is established, potential risks can be systematically identified and evaluated, and the overall risk management capability is improved.

The invention discloses a convenient-to-adjust welding workstation for hardware machining, and relates to the technical field of adjusting welding, the convenient-to-adjust welding workstation for hardware machining comprises an equipment frame, a welding mechanism is fixedly mounted on the outer wall of the equipment frame, a first motor is fixedly mounted on the surface of the equipment frame, and the convenient-to-adjust welding workstation for hardware machining further comprises a clamping device; wherein the clamping device comprises a rotating rod, a fixing plate, a rotating pipe, an electric push rod, a clamping plate, a large gear, a second motor, a connecting rod, a circular plate and a small gear, and the rotating rod is fixedly installed at the output end of the first motor. The hardware is fixed in the welding process, the situation that the hardware is damaged due to the fact that the hardware shakes in the welding process and falls off can be prevented, meanwhile, the non-welded side is rotated, the hardware can be adjusted to the optimal position more easily, and unnecessary torsion and stretching are reduced.