219results about How to "Discovered in time" patented technology

The invention relates to the field of electric meter box monitoring, and discloses an anti-electricity-stealing method and system for an intelligent electric meter box, which is used for solving the problem of false alarm caused by harmonic interference when anti-electricity-stealing early warning is carried out, and comprises the following steps: collecting time domain signals of current and voltage in the intelligent electric meter box in a historical detection time period; converting the time domain signal into a frequency domain signal, extracting harmonic information of each harmonic, and establishing a normal harmonic feature model to obtain a target harmonic range; the method comprises the following steps: acquiring time domain signals of current and voltage in an intelligent electric meter box in real time, extracting harmonic information, performing filtering processing according to a target harmonic range, performing first abnormality judgment by using an abnormality detection algorithm, performing multi-parameter joint evaluation if abnormality is judged for the first time, and performing second abnormality judgment according to a multi-parameter joint evaluation result. And electricity larceny early warning is carried out according to the second abnormal judgment result, so that false alarm and missing alarm are effectively reduced, and the adaptability of the system to a complex electricity larceny mode is remarkably enhanced.

The invention discloses a full-automatic laser welding forming system, which relates to the technical field of laser welding, and comprises a laser generation and light beam modulation module, a material conveying and positioning module, a welding execution module, a visual inspection and monitoring module, an intelligent self-adaptive control module and an energy recovery and reutilization module, the material module accurately conveys and positions materials; the welding module robot is accurate in operation; the visual module detects welding seams; the intelligent module performs self-adaptive control; the energy module recycles energy. The welding quality is improved, and defects are reduced; the production efficiency is improved and the cost is reduced; operation is simple, and manpower requirements are reduced; energy is saved, environment is protected, and green concept is met; real-time monitoring is achieved, and the product quality and the management level are guaranteed.

The invention belongs to the technical field of fire sensing and detection, and provides a fire sensing method and related device for a double-layer cable tunnel structure, and the method comprises the steps: respectively collecting the temperature, smoke and image data of a double-layer cable tunnel, and carrying out the double-layer data linkage; respectively constructing a temperature distribution model, a smoke diffusion model and an image target detection model according to the collected temperature, smoke and image data; and performing temperature, smoke and image multi-modal data fusion based on the temperature distribution model, the smoke diffusion model and the image target detection model, and when the fused data meets a set fire threshold, determining that a fire occurs. Through the fire sensing and verification method aiming at the characteristics of the double-layer cable tunnel, scientific and reliable decision support is provided for improving tunnel fire safety management, the safety of personnel and equipment in the tunnel is ensured, and meanwhile, the standardization process of the fire sensing technology is promoted.

The invention discloses a working face earth surface rock movement digital intelligent observation and through-structure safety intelligent prediction method, and belongs to the technical field of mining industry and information, and the method comprises the following steps: determining a structure movement deformation safety early warning value; moving deformation data are collected and preprocessed; analyzing a dynamic change rule of surface movement deformation by applying finite element analysis; building a structure movement deformation prediction model; the structure movement deformation prediction model is trained and verified, and the trained model is used for structure movement deformation prediction; comprehensively evaluating safety and stability; and correcting parameters of the prediction model and continuously evaluating until the structure is safely pushed and mined. The invention provides a novel way with great potential for accurately predicting the rock migration trend and guaranteeing the safety of important facilities such as structures.

The invention discloses a wind power plant blade icing prediction method and device, equipment and a medium, and relates to the field of wind power generation. The method comprises the following steps: acquiring predicted meteorological data of a wind power plant in a future preset time period, wherein the predicted meteorological data comprises temperature and humidity; and inputting the predicted meteorological data into a pre-trained blade icing prediction model, processing the predicted meteorological data by the blade icing prediction model, and outputting a blade icing prediction result of the wind power plant, the blade icing prediction result representing a blade icing condition in a future preset time period. The blade icing prediction model is obtained through training according to historical sample data of the wind power plant, the historical sample data comprises meteorological data in historical icing time and meteorological data in historical non-icing time, the meteorological data comprises temperature and humidity, and the historical sample data has labels used for representing blade icing conditions corresponding to the meteorological data. According to the embodiment of the invention, the safety risk of the wind power plant can be reduced.

The invention provides gear box full-automatic multi-station assembling equipment, and relates to the technical field of gear box assembling, the gear box full-automatic multi-station assembling equipment comprises a workbench, and the workbench is provided with a first disc cutting mechanism and a second disc cutting mechanism; a bearing pedestal feeding mechanism, a main shaft direction selecting mechanism, a roller feeding mechanism, a pin roller and steel ball feeding mechanism, a pin roller and steel ball detecting mechanism, an inner gear feeding mechanism, a first transmission fluted disc feeding mechanism, a first oil injection mechanism, a transmission gear feeding mechanism and a gear detecting mechanism are sequentially arranged on the periphery of the first disc dividing mechanism. The first disc cutting mechanism, the second disc cutting mechanism and a plurality of mechanisms around the first disc cutting mechanism and the second disc cutting mechanism are arranged on the workbench, all working procedures needed for gearbox assembly are highly integrated, continuous automatic operation of a series of working procedures from part feeding to assembly and detection is achieved, the assembly time is effectively shortened, the assembly efficiency is improved, and the production cost is reduced. Labor input is reduced, labor cost is reduced, and the quality of final products is effectively improved.

The invention discloses a computer network information security monitoring method, which relates to the technical field of network information security monitoring, and comprises the following steps of: monitoring and collecting network flow data in real time by using a monitoring and collecting module, extracting and recording historical network flow data, judging the abnormal degree of the current flow by using a comprehensive evaluation and adjustment module, and judging the abnormal degree of the current flow. The method comprises the following steps: evaluating the overall risk level of network security, adjusting a network security policy, generating a policy adjustment report, executing the adjusted network security policy by using a security execution module based on the policy adjustment report, and continuously monitoring network traffic by using a monitoring acquisition module. The beneficial effects and optimization innovation of comprehensive assessment, dynamic risk assessment, flexible strategy adjustment and sensitivity improvement are realized, and the optimization and innovation not only solve the problems and defects in the prior art, but also improve the accuracy and reliability of the monitoring system. And a more comprehensive and effective guarantee is provided for computer network information security.

The invention relates to the technical field of environmental protection monitoring, and discloses an intelligent environmental protection monitoring method and system for a pollution source, a pollution source monitoring area is divided into a plurality of monitoring sub-areas, a plurality of data monitoring units are arranged in each monitoring sub-area, and related data of pollutants in the monitoring sub-areas are collected and analyzed in real time, so that the pollution source monitoring area is divided into a plurality of monitoring sub-areas; pollution state difference values are calculated by analyzing pollutant related data between adjacent monitoring sub-areas, and environmental pollution degree coefficients are calculated by analyzing the pollution state difference values collected in a period of time, so that the environmental pollution condition in each monitoring sub-area is detected. According to the method and the system, the monitoring sub-areas with the abnormal pollution degree are monitored, the environmental pollution degree in each monitoring sub-area is detected, and early warning response is performed on the monitored monitoring sub-areas with the abnormal pollution degree, so that more refined monitoring and management of pollution sources can be comprehensively realized, environmental problems can be found in time, and the accuracy of a pollution abnormity detection result is further improved.

The invention provides an intelligent visual inspection method on an inductor hot-pressing production line and related equipment, and relates to the field of quality control of automatic production lines. The method comprises the steps that image information of various inductors of different models is obtained firstly, the image information comprises boundary dimensions and surface defect information, and after preprocessing, a quality judgment model is constructed by combining a deep learning algorithm and qualified inductor image information; and after receiving a detection starting instruction of the display end, shooting a to-be-detected inductor by using a plurality of image acquisition devices pre-deployed in a key area of the production line to obtain a to-be-analyzed image, and inputting the to-be-analyzed image into the model to judge the quality of the inductor. And if the detection result is not matched with the quality threshold value of the qualified inductor of the corresponding model, an unqualified prompt message is sent to the display end, so that efficient and accurate detection of the inductor quality is realized.

The invention relates to the technical field of poultry health monitoring, and particularly discloses a poultry monitoring method and system based on the Internet of Things, and the method comprises the steps: S1, installing intelligent foot rings for all poultry, carrying out the weighing, breeding the poultry with similar weight values in different breeding regions according to a preset breeding number, pressure sensors are installed below the poultry feeders in all the breeding areas; s2, collecting body temperature information and motion information of the corresponding poultry at a preset collection frequency through an intelligent foot ring, and collecting weight information of poultry feeders in each breeding area through a pressure sensor; according to the method, the body temperature information is preliminarily monitored and analyzed, the weight change data of all the poultry feeders are analyzed through the poultry monitoring center, whether the poultry possibly getting sick exists in the breeding area or not is judged, and therefore the health state of the bred poultry can be monitored, and when the poultry has the risk of getting sick, the poultry feeders can get sick; and the patient can be found and treated in time.

The invention relates to the technical field of deep foundation pit monitoring, and discloses a deep foundation pit micro-deformation InSAR remote sensing method and system and a storage medium. The method comprises the following steps: synchronously acquiring data through a ground radar and an InSAR satellite, and obtaining a point target set and an original scattering characteristic sequence; obtaining a net deformation phase sequence without influence through registration residual correction, phase deduction and weighted fusion processing, and carrying out phase consistency quality control and unwrapping processing to obtain an accumulated deformation quantity sequence; constructing a deformation mechanism correlation characteristic matrix based on correlation analysis of the cumulative deformation quantity sequence and radar reflection intensity amplitude attenuation characteristics; and fusing the deformation mechanism correlation feature matrix and the real-time differential interference image group, extracting deformation rate and phase gradient change, and further generating a deep foundation pit local micro-deformation risk early warning index set. According to the invention, the tiny deformation of the surrounding area of the foundation pit can be effectively detected, potential risks are warned in advance, and the safety and monitoring efficiency in the construction process are improved.

The invention discloses a pipeline monitoring and maintenance method based on unmanned aerial vehicles (UAVs), and relates to the technical field of pipeline monitoring. The method comprises the following steps: obtaining structural data of a pipeline to be monitored and surrounding network signal strength data, calculating structural similarity and network similarity between the pipeline to be monitored and each pipeline in a monitored pipeline set, and screening out a target monitoring pipeline set and a corresponding UAV set with similar structures and network conditions; calculating a priority index of each target UAV through the remaining power and image upload quality characteristics; selecting a UAV with the highest priority index to perform a monitoring task, and judging whether the pipeline needs maintenance; in this way, for a pipeline that is firstly introduced with UAVs for pipeline monitoring, a suitable UAV can be selected according to actual conditions to monitor the pipeline to be monitored, so that the monitoring data is relatively comprehensive and has high accuracy, and minute cracks or leakage points in the pipeline can be discovered in time, and the pipeline can be maintained in time, thereby reducing the possibility of risks in the pipeline.

The invention discloses a foreign matter detection method for a belt conveyor, and belongs to the technical field of coal transportation metal detection. Comprising a fluxgate sensor and a signal acquisition unit. Wherein the fluxgate sensor and the signal acquisition unit are integrated into an integrated unit, and a Doppler array structure is constructed by a plurality of integrated units; the signal acquisition unit comprises an excitation signal generation part, a signal processing part, an AD acquisition part and a data processing algorithm part; according to the metal detection device, the magnetic sensor is fixed above the conveying belt through the non-magnetic support, magnetic field environment data generated when no abnormal metal exists serves as the background, magnetic abnormal signals generated by metal on the conveying belt below are detected through the magnetic sensor, and local voice alarm is accessed locally or a sealing-tape machine is controlled to stop. Iron metal in the coal flow is detected, the relative size of the iron metal and the relative position after shutdown are judged, and identification is more accurate.

The present invention belongs to the technical field of operation monitoring and control of sewage treatment coarse screen equipment, and relates to an operation monitoring and control system for sewage treatment coarse screen equipment. The present invention helps to timely discover and solve abnormal or inefficient problems in the operation of sewage treatment coarse screen equipment by analyzing the operation feedback index of sewage treatment coarse screen equipment, ensuring that the sewage treatment coarse screen equipment is always in the best working state, and helps to timely discover and remove debris on the sewage treatment coarse screen equipment by analyzing the cleaning feedback index of the sewage treatment coarse screen equipment, reducing the impact and wear of the debris on the sewage treatment coarse screen equipment, which is conducive to extending the service life of the equipment, and by analyzing the cleaning effect of the front and rear water bodies of the sewage treatment coarse screen equipment, it is conducive to targeted equipment maintenance and adjustment of equipment with unqualified cleaning effects, ensuring that the cleaning effect of the front and rear water bodies of the coarse screen equipment meets the standards, and reducing the degree of pollution to the environment.

The invention discloses a dangerous cargo risk early warning method and system and a computer program. The dangerous cargo risk early warning method comprises the steps of obtaining multi-source monitoring data; analyzing the multi-source monitoring data through a preset rule engine and a trained dangerous cargo risk prediction model to obtain a risk prediction result; and performing early warning according to a risk prediction result. According to the technical scheme provided by the invention, the historical and real-time multi-source monitoring data is acquired, and the rule engine and the machine learning algorithm are used for predicting dangerous cargo risk factors, so that dangerous cargo risk early warning is more real-time and accurate; compared with manual inspection and video monitoring, data can be acquired more frequently, and key information is synchronized in a data center; multiple data sources are covered, and the influence of various factors on a monitoring station can be considered more comprehensively; by means of automatic data collection and intelligent data analysis, manpower resources can be saved, problems and risks can be found more timely, and therefore potential loss and cost are reduced.

The invention relates to the technical field of projection display, in particular to an alarm display method, display equipment, a storage medium and a vehicle. According to whether the interior of the vehicle is in the noisy environment or not, the vehicle is divided into different levels, and the required projection information is displayed in the corresponding display mode on the corresponding level, so that the alarm prompting capability in the noisy environment is enhanced, a user can timely find the alarm information in the projection information, and the user experience is improved. And the driving behavior of the driver is not excessively interfered. The method can adapt to different environments, adopts a flexible alarm form in the display area of the HUD projection, improves the alarm capability for a driver, and optimizes the watching experience of a user.

The invention provides an embankment anti-seepage treatment method based on water conservancy construction, and relates to the field of water conservancy projects, and the method comprises the following steps: A, excavating at an embankment position needing to be implemented according to a construction drawing to form an embankment foundation, constructing on the embankment foundation to form anti-seepage geotechnical cloth, and compacting the anti-seepage geotechnical cloth; b, an anti-seepage panel is constructed on the anti-seepage geotechnical cloth, and the anti-seepage panel is compacted; c, paving a cushion layer and a transition layer on the anti-seepage panel according to construction requirements; d, burying different intelligent sensors at different parts of the constructed dike, and constructing a real-time monitoring network; and E, transmitting the data acquired by the sensor to a remote monitoring platform through the Internet of Things technology, and analyzing and processing the data. A traditional water conservancy construction dike anti-seepage method is improved, a physical anti-seepage structure and an intelligent monitoring technology are combined, leakage problem early warning can be timely and accurately carried out, effective repairing measures are rapidly taken after early warning, and the dike anti-seepage treatment performance is greatly improved.

The invention discloses a method and system for analyzing the detection coverage rate of a railway track dynamic inspection tester, and relates to the technical field of railway track safety detection, and the method comprises the steps: collecting track dynamic detection data obtained by each railway track dynamic inspection tester; the obtained track dynamic detection data are screened and cleaned, and data meeting preset conditions are filtered out; based on the filtered data, the coverage condition of the railway track dynamic inspection tester on each line is analyzed, and visual display is carried out; and automatically generating a coverage rate report in a spreadsheet type according to an analysis result of the coverage condition. According to the method, the coverage condition of the railway track dynamic inspection tester on each line is accurately analyzed, and the analysis result is intuitively displayed, so that a manager can better understand and analyze track dynamic detection coverage rate data, the accuracy and efficiency of data interpretation are improved, and the reliability of data interpretation is improved. The locomotive running route provided with the railway track dynamic inspection tester is reasonably deployed, and the coverage rate of track dynamic detection is increased.

The invention provides a road intelligent maintenance method and system based on an equivalent axle number and a medium, and belongs to the technical field of road maintenance and big data. The method comprises the following steps: acquiring road vehicle passing information and road state information of a preset area in a preset time period, extracting road design parameter information and road disease detection information according to the road state information, querying according to the road vehicle passing information to obtain equivalent axle number data, processing to obtain accumulated equivalent axle number data, and determining the road design parameter information and the road disease detection information according to the accumulated equivalent axle number data. A road tolerance index is obtained in combination with road design parameter information, a road damage degree index is obtained according to road disease detection information, the road damage degree index is compared with the road tolerance index, a road damage resistance matching degree index is obtained, and whether road damage is normal or not is judged. According to the method, the quantitative conversion from the original data to the evaluation result is realized, the actual condition of the road can be accurately reflected based on professional knowledge and practical experience, and the comprehensiveness and accuracy of the evaluation are ensured.

The invention discloses a cross-belt sorting machine, a lifting sorting machine, a cross-belt sorting system and a sorting method.The cross-belt sorting machine comprises a circle of lifting sorting machine moving along a track, the lifting sorting machine comprises a lifting mechanism and a conveying assembly driven by the lifting mechanism to ascend and descend, and a rotation driving assembly is arranged on the lifting mechanism; the rotary driving assembly is provided with a conveying assembly so that the conveying assembly can horizontally rotate around the longitudinal axis perpendicular to the conveying face of the conveying assembly. The conveying direction of the conveying assembly can be adjusted during sorting, so that the parcels output by the conveying assembly can overcome inertia force borne by the parcels in the moving direction of the lifting sorting machine, and the moving direction of the parcels is closer to be perpendicular to the moving direction of the lifting sorting machine; in this way, the parcels can be accurately sorted under the smaller sorting grid openings, more sorting grid openings can be arranged under the same size, and / or on the basis of the sorting grid openings of the same size, the higher loop line running speed is adopted.

The invention provides a cache verification method based on a multi-core processor architecture, electronic equipment and a storage medium, the cache verification method comprises the following steps: aligning an address of a main memory according to an address of a cache unit, and allocating a space for the cache unit in the main memory; the allocation space of the cache unit is equally divided into a first part and a second part, a DMA controller is used for executing write operation on the first part, and meanwhile a CPU processor is used for executing write operation on the second part; and comparing the current data in the allocation space to verify the consistency of the cache units. According to the method, testing and verification can be synchronously carried out in the initial stage of chip design, problems can be found more timely, the testing period is shorter, and the positions of the problems can be located more quickly; the test efficiency is higher, the problem is found more quickly, and the user experience is improved.

The embodiment of the invention discloses a file checking method and device based on a knowledge graph, equipment and a computer medium. A specific embodiment of the method comprises the following steps: constructing a file checking entity relationship knowledge graph; obtaining a check case sample from a check case sample database; reading a to-be-checked file corresponding to the file checking instruction from a to-be-checked file database; carrying out key check field extraction processing on the to-be-checked file to obtain a key check field text information set; generating a checking result corresponding to the to-be-checked file according to the key checking field text information set and the file checking entity relation knowledge graph; and marking the to-be-checked file, controlling an associated file display terminal to display a checking result and the marked checking file, and controlling associated abnormal file early warning equipment to give out an early warning prompt tone. According to the embodiment, the file checking efficiency and accuracy can be remarkably improved.

The utility model discloses an intelligent lubrication management cloud platform, which relates to the technical field of intelligent manufacturing, and comprises a control module used for receiving data and sending out a control signal; the detection module is electrically connected with the control module through a cable and is used for detecting the flow, pressure and liquid level of the lubricating liquid; the transmission module is in communication connection with the control module, and the transmission module is used for receiving a control signal sent by the control module, transmitting the control signal to the power module and transmitting a work log to the data storage module; the power module is electrically connected with the transmission module, and the power module executes the control signal sent by the control module to lubricate the equipment; the data storage module is electrically connected with the control module, the data storage module is in network connection with the transmission module, the oil injection condition of the lubricator can be remotely monitored, monitoring check and parameter adjustment can be remotely carried out anytime and anywhere through a mobile phone and a computer, and centralized management is facilitated.

The invention relates to the field of bolt detection, in particular to an automatic bolt looseness detection and alarm device. The device main body comprises a power supply assembly and a plurality of alarm assemblies, each alarm assembly comprises an indicating lamp and a buzzer alarm, the indicating lamps are used for detecting looseness of bolts and nuts, the buzzer alarms are used for detecting breakage of the bolts, and the power supply assembly comprises a solar panel. According to the invention, the electromagnetic induction principle and the circuit on-off change are utilized to realize the automatic detection and alarm functions of the two key states of bolt loosening and fracture, and a reliable monitoring means is provided for guaranteeing the safe operation of facilities and equipment. Different power supply connection modes are designed for fixed parts made of different materials, higher universality and applicability are achieved, limitation of the material properties of the fixed parts is avoided, and the application range is wider. A power supply assembly composed of a solar panel, a charging controller and a storage battery is adopted, clean energy solar energy is used for supplying power, and external power supplies such as an external mains supply are not needed.

The invention provides an information decision-making method and system based on collection session big data analysis, and the method comprises the steps: firstly obtaining collection session big data, and then generating sample collection session training data for a session data streams in the collection session big data through enhancing key semantic nodes of collection target users in the session data streams. In the process, if a risk fraud event exists in the semantic representation vector associated with the key semantic node of the collection target user, the risk fraud event is included into sample collection session training data. And finally, parameter learning is performed on the collection session decision network by using the sample collection session training data, so that the collection session decision network for completing parameter learning, which can accurately decide whether risk fraud events exist in the collection session data, is generated, and key information in the collection session big data is deeply mined, so that the risk fraud events in the collection session data can be accurately determined. And efficient identification of risk fraud events is realized.

The invention discloses a termite luring and monitoring device which comprises a trapping and killing device, a monitoring device and a mounting structure, the trapping and killing device comprises a shell with a bottom plate, a positioning device with a luring core and a top cover structure, the luring core is arranged in a mode of gradually shrinking inwards from the position close to the shell, and the luring core can extend out of the shell; the orthographic projection area of the lure to the top surface accounts for more than 50% of the area of the top surface of the shell; the monitoring device comprises an imaging acquisition module, a formic acid sensor, a controller and a wireless communication module; the imaging acquisition module is used for acquiring images of termite activities in the shell, the formic acid sensor is used for acquiring the concentration of formic acid gas in the shell, the controller is used for analyzing data acquired by the imaging acquisition module and the formic acid sensor, and the wireless communication module is mounted on the cover plate and is used for wirelessly transmitting a result analyzed by the controller. The mounting structure is located on the housing. According to the termite trapping device, the transverse space is reasonably utilized, termites can be conveniently observed and monitored, the termite trapping efficiency is improved, and the monitoring result is more accurate.

The invention discloses a network security threat perception device and method based on knowledge reasoning and algorithm service, and the device comprises a security threat perception and research and judgment subsystem which is configured to complete network security threat perception, and achieves the suspected threat research and judgment together with a knowledge extension subsystem, and generates a defense plan; the knowledge base knowledge extension and service subsystem is configured to extract knowledge from the network security threat field data for knowledge extension and provide knowledge service for the threat perception subsystem and knowledge base users; the intelligent algorithm model training and application subsystem is configured to perform intelligent enabling on a situation threat perception model uploaded by the threat perception subsystem, a knowledge reasoning model uploaded by the knowledge extension subsystem, a semantic association model uploaded by the semantic fusion subsystem and the like in the algorithm training subsystem; and the semantic knowledge fusion and application subsystem is configured to complete dynamic expansion, visual display and application service of the network security threat knowledge graph.

The invention provides a building electrical safety detection method and system, and relates to the technical field of electrical detection, and the method comprises the steps of first collection, second collection, first processing, second processing, third processing, model construction, model training, fault recognition and the like. The compressed sensing algorithm and the morphological filter are used, noise and interference signals in the data are effectively removed, the accuracy of fault detection of the electrical equipment in a complex electromagnetic environment in a high-rise building is improved, faults of the electrical equipment can be found in time, corresponding maintenance measures can be taken, and the fault detection efficiency is improved. And safe and stable operation of an electrical system is ensured.

The invention relates to the technical field of power generation equipment data monitoring, in particular to a new energy power generation equipment accurate monitoring and operation data analysis method. Comprising the following steps: data acquisition and storage: deploying sensors at key nodes to acquire data; evaluating a running state, extracting key indexes such as equipment efficiency, energy consumption and environmental adaptability, and quantifying a scoring standard; an evaluation function is constructed, an analytic hierarchy process and an entropy weight method are combined to determine a weight, and a normalized weight value and a comprehensive evaluation value are calculated; carrying out anomaly detection and early warning, defining an early warning level based on the comprehensive evaluation value, and carrying out mean shift detection; early warning operation and emergency response are carried out, a feedback mechanism is established, and emergency measures under different early warning levels are formulated. According to the method, the equipment operation state monitoring accuracy, the data evaluation scientificity and the abnormity processing timeliness and effectiveness are improved, and stable operation and efficient power generation of the new energy power generation equipment are guaranteed.

The utility model discloses a detachable supporting assembly for a giant circular ring. The detachable supporting assembly comprises a lining plate, a first supporting rod, a second supporting rod and an adapter plate. The plurality of lining plates are uniformly arranged in a circle along the inner wall of the ring and are fixed with the inner wall of the ring by spot welding, the adapter plate is located at the center of the ring, the length of the two first support rods is slightly smaller than the diameter of the ring, two ends are connected with the lining plates through bolts, and the middle is connected with the adapter plate through bolts; the second inner supporting rods are arranged in the radial direction, the outer ends of the second inner supporting rods are connected with the inner lining plate through bolts, and the inner ends of the second inner supporting rods are connected with the adapter plate through bolts. The inner supporting assembly is simple in structure and convenient to construct, on the premise that stable supporting is guaranteed, mounting and dismounting difficulty is lowered, mounting time is shortened, labor cost is saved, meanwhile, welding workload is reduced, worker fatigue and welding quality reduction caused by long-time welding are avoided, the inner supporting assembly can be positioned and corrected through bolts, and the production efficiency is improved. Compared with an all-welded structure, stress concentration can be effectively reduced.