132results about How to "Avoid critical failure" patented technology

The invention provides a wind generating set remote on-line multi-mode health state monitoring and fault diagnosis system. The system comprises a wind speed / generated energy monitoring device, a temperature / vibration monitoring device, a voice frequency monitoring device and video monitoring device. The system is characterized by further comprising a lower computer and an upper computer, wherein the lower computer is connected with a wind generating set, and the upper computer is connected with a network client. Meanwhile, the audio and video technique is utilized, and remote observation of the operation state of the set is achieved. The system has the advantages of being simple in operation, and capable of achieving remote monitoring and remote diagnosis of faults.

The invention relates to a method for monitoring mechanical states of high-voltage isolating switches and emitting warning, and belongs to the field of technologies for monitoring power transformation equipment in an online manner. The method for monitoring the mechanical states of the high-voltage isolating switches and emitting warning has the advantages that working currents, which represent the magnitude of operation resistance, of driving motors are monitored during opening or closing operation on the high-voltage isolating switches in real time, so that operation resistance change conditions can be comprehensively monitored in integral operation procedures, defects such as jamming and movement failure of equipment can be timely found out, and equipment state maintenance or state evaluation can be effectively supported; the method is simple in implementation and simple, clear and reliable in principle, and increase of the complexity of the original equipment can be prevented when the method is implemented; the mechanical states of the high-voltage isolating switches can be diagnosed in real time, defect types of the mechanical states of the high-voltage isolating switches can be intelligently judged, warning can be timely emitted, accordingly, severe faults of the equipment can be effectively prevented, and economic loss and social influence can be reduced.

The invention discloses a rainwater-collection recycling system and a construction method thereof. The rainwater-collection recycling system comprises a control system, an initial-rainwater flow dividing well, a water storage pool, a first lifting well, a filtering disinfecting chamber, a clean water pool and a second lifting well, wherein the initial-rainwater flow dividing well, the water storage pool, the first lifting well, the filtering disinfecting chamber, the clean water pool and the second lifting well are sequentially communicated. The first lifting well is communicated with the bottom of the water storage pool and arranged in the water storage pool, and the second lifting well is communicated with the bottom of the clean water pool, arranged in the clean water pool and connected with a recycling point pipe; a stopping weir is arranged in the initial-rainwater flow dividing well, a flow discarding groove is formed in the lower portion of the stopping weir, a rainwater feeding pipe is arranged on the side wall of a water distribution area, the height of the rainwater feeding pipe and the height of the pipe bottom of a first water discharging pipe are larger than or equal to the height of the groove top of the flow discarding groove, and the pipe bottom of an overflowing pipe is flush with the groove bottom of the flow discarding groove; a plurality of back washing pipes are laid on the bottom of the water storage pool, the outer surface of the water storage pool and the outer surface of the clean water pool are sequentially covered with an anti-seepage film layer preventing water seepage and a geotechnical cloth layer from inside to outside, construction and maintenance are convenient, and the recycled rainwater quality is high.

The invention discloses an over temperature protection method for an ISG (Integrated Starter Generator) of a hybrid electric vehicle. When the ISG is about to achieve a temperature threshold value, the purpose of preventing the ISG from being burnt due to overhigh temperature is achieved by virtue of restricting the power of the ISG. By virtue of the motor, ISG over temperature protection is timely and effective, and charge and discharge performances of an entire-vehicle power battery are slightly influenced.

The invention relates to the field of transformer parameter regulation and control, in particular to a parameter optimization method and device for a coupling type transformer. The method comprises the following steps: acquiring multi-dimensional real-time working monitoring parameters and real-time working environment state parameters of the coupling type transformer; performing nonlinear dynamic analysis and global state sensing modeling on the multi-dimensional real-time working monitoring parameters so as to construct a transformer global state sensing model; performing multi-parameter combination definition on the multi-dimensional real-time working monitoring parameters, performing dynamic operation simulation based on a transformer global state sensing model, and collecting operation simulation response data of a plurality of schemes; performing multi-target dynamic balance analysis on the operation simulation response data of the plurality of schemes to obtain an optimal transformer working parameter combination; and carrying out environment dynamic parameter change analysis on the real-time working environment state parameters, and constructing a real-time environment condition distribution field. According to the invention, efficient and self-adaptive adjustment transformer parameter optimization is realized.

The invention discloses a failure monitoring method and failure monitoring system for bake cylinders of a motor train unit. The monitoring method comprises the following steps of obtaining pressure measuring data of the brake cylinders in the braking process under the normal working condition to form a training data set; calculating variable between-psu variance of each sample in the training data set and determining the threshold of the variable between-psu variance; acquiring the pressure measuring data of each brake cylinder at current time in real time to be used as a test sample, and judging whether the test sample fails or not by using the threshold of the variable between-psu variance; and if yes, sequentially obtaining the restructured contribution value of the pressure measuring data of each brake cylinder in the test sample, and determining the brake cylinder of the maximum restructured contribution value to be the failing brake cylinder. According to the method, failures can be timely detected and separated, and the failing brake cylinder or a pipeline where the failing brake cylinder is arranged can be indicated, so that predication of a major failure can be realized, and the method provides a certain reference for the timely maintenance and replacement for components; therefore, the generation of even more serious failures can be effectively avoided.

The invention provides a bridge structure fatigue crack propagation prediction method and system, and relates to the technical field of artificial intelligence. According to the method, structural parameter information of a bridge is collected, a three-dimensional model of the bridge structure is established through finite element analysis, and a fatigue crack propagation prediction model is established based on the fracture mechanics theory and a fatigue damage accumulation model; performing expansion simulation on preset cracks in the three-dimensional model of the bridge structure, calculating a crack expansion rate and predicting a crack expansion path, correcting a crack expansion simulation result in combination with an actual working environment and a load condition of the bridge structure, and calculating a crack expansion simulation result according to the corrected crack expansion simulation result. And predicting crack propagation information of the bridge structure in the preset time period. The method can accurately predict the expansion path, rate and future state of the crack under a complex working condition, thereby providing a scientific basis for maintenance and repair of the bridge, realizing real-time feedback and dynamic adjustment, ensuring high efficiency and accuracy of a prediction result, and providing a scientific basis for maintenance management of the bridge.

The invention discloses an abnormity identification method and a monitoring platform for domestic sewage treatment facility. The method comprises the following steps: S1, acquiring current and outletflow data of a sewage lift pump in a normal working state within a specific time, and current and outlet flow data of the sewage lift pump before a fault occurs and within a specific time, so as to construct an abnormity analysis data set, S2, performing clustering analysis on the abnormity analysis data set through a clustering algorithm to obtain an abnormity data cluster; S3, obtaining a numerical boundary according to the exception type data cluster, and constructing an abnormity identification model; S4, collecting current and outlet flow data of the sewage lift pump, and inputting the current and outlet flow data into the abnormality identification model to perform abnormality judgment, and further performing sequential analysis on the abnormal data cluster to obtain a time boundary,and adding the time boundary into the abnormal recognition model. According to the abnormity identification method, comprehensive judgment is carried out on the data in the time boundary, and early warning can be carried out on initial abnormal operation of the sewage treatment facility.

The invention relates to the technical field of new energy power station control, and particularly discloses a new energy power station perception control method and system, and the method comprises the steps: S1, data collection, S2, state perception, S3, monitoring and early warning, S4, decision and optimization control, S5, execution and feedback, S6, intelligent operation and maintenance, and S7, self-healing scheduling. The deep neural network DNN is utilized to process a large amount of sensor data, so that the system can learn modes from complex historical data, accurately identify conditions such as power fluctuation and voltage abnormity, and timely discover potential abnormity through real-time updating of the model, so that the possibility of misinformation and missing report is reduced, and the reliability of the system is improved. The system monitors the operation state of the power station in real time, can quickly recognize and classify abnormal conditions, provides instant data support for decision making, can take measures in advance through abnormal prediction, prevents problems from being further expanded, and can recognize equipment needing to be maintained and prevents faults from being expanded through patrol inspection and prediction analysis of the unmanned aerial vehicle.

The invention discloses a method for monitoring the inherent frequency of a wind generation set tower. The method comprises the steps that vibrating acceleration instantaneous values of the two points in the tower are measured, wherein the axes of the two points are symmetric; the two vibrating acceleration instantaneous values are subjected to weighted calculation and fast Fourier transformation, and a corresponding frequency domain signal is obtained; the frequency domain signal is detected by a peak detector and filtered, and the instantaneous value of the inherent frequency of the tower is obtained; the instantaneous value is compared with a basic value, a difference value is obtained, if the difference value is larger than a threshold, an alarm is sent out and shut-down is conducted. When the vibrating acceleration signals of the tower is obtained in real time, the instantaneous value and the basic value of the inherent frequency of the tower are obtained through real-time calculation and moving average calculation, the tower failure monitoring effect is achieved, the major failure of the tower is avoided, and safe and effective running of a wind generation set is ensured.

The invention discloses an anomaly detection method and an anomaly detection system, which relate to the field of detection. The anomaly detection method comprises the steps of: acquiring a multi-dimensional time sequence matrix used for representing a normal state of an object to be detected; establishing a two-dimensional self-organized mapping feature network structure, and performing iterativetraining on the multi-dimensional time sequence matrix by means of the two-dimensional self-organized mapping feature network structure, so as to obtain a multivariable state estimation memory matrix; and performing anomaly detection on data to be detected of the object to be detected according to the multivariable state estimation memory matrix. The anomaly detection method and the anomaly detection system provided by the invention improve the precision of anomaly detection of complex hop data, and can effectively solve the problem of high erroneous detection rate of anomaly detection of thecomplex hop data.

The invention relates to an anticipated accident selection method for an electric power system with uncertain injection power. The method comprises the following steps: (1) performing static security analysis modeling on the electric power system with uncertain bus injection power; (2) generating anticipated accident set data information; (3) simulating anticipated accidents and determining that an uncertain amount of electric power system state information is contained after the accidents; (4) determining system state interval indexes after the anticipated accidents; (5) comparing corresponding interval indexes of the accident set; (6) sequencing fault indexes and selecting an anticipated event. By adopting the static safety analysis anticipated accident selection method for the system, system running personnel can know the static safety level of the electric power system within a future period of time, and the power grid running reliability and stability are enhanced.

The invention provides a wine cabinet allowing a wine bottle to be stored and taken out automatically and a control method of the wine cabinet. The wine cabinet comprises a hollow cabinet body, multiple wine bottle retaining members, a wine bottle storage and take-out mechanism and a control device, wherein wine storage spaces are defined in the hollow cabinet body, and a storage and take-out opening is formed in the top wall of the hollow cabinet body; the multiple wine bottle retaining members are fixed on the circumferential side wall of the hollow cabinet body; the wine bottle storage and take-out mechanism is configured to perform storage and take-out operation on the wine bottle and comprises a motion actuation mechanism and a wine bottle take-out and storage member fixed on the motion actuation mechanism; the control device comprises a self-inspection module and a motion control module, the self-inspection module is configured to determine that the wine bottle take-out and storage member is located in a preset original position, and the motion control module is configured to drive the motion actuation mechanism to drive the wine bottle take-out and storage member to store the wine bottle on a designated wine bottle retaining member or take out the wine bottle from the designated wine bottle retaining member from the original position. Accordingly, whether the wine bottle storage and take-out mechanism is located in the preset original position can be determined before the storage and take-out process, and the wine cabinet allowing the wine bottle to be stored and taken out automatically can store and take out the wine bottle reliably.

The invention discloses a centralized monitoring transformer substation risk identification early warning system and a working method thereof, and relates to the field of electric power operation andmaintenance. A traditional monitoring means is difficult to realize effective management and control on three monitoring risks of equipment defects, frequent light words and suppression signals. The centralized monitoring transformer substation risk identification early warning system synchronously collects data of a master station and a station server, performs statistical analysis, calculation,verification and special analysis on the data including equipment defects, frequent light words and suppression signals, and generates an intelligent risk identification result and a corresponding risk list based on a centralized monitoring risk library; corresponding on-site operation and maintenance units and automatic operation and maintenance personnel are informed and disposed according to safety risk levels, and timely management and control of the equipment defects, constant light words and suppression signals are realized. According to the technical scheme, the risk online management and control rate is improved, the risk management and control time limit is shortened, and the power grid monitoring risk management and control level is improved.

The invention discloses a control method for a head shaking system. The head shaking system comprises a shell, a head shaking assembly, a magnet, a detection assembly, a head shaking rotating shaft and a two-way synchronous motor; the detection assembly is used for generating a midpoint detection signal when the magnet approaches; the control method comprises the following steps: judging whether the midpoint detection signal is detected within a first preset time; if the midpoint detection signal is not detected, increasing a count value; judging whether the count value reaches a preset threshold; if the count value reaches the preset threshold value, controlling the two-way synchronous motor to stop rotating; if the midpoint detection signal is detected, controlling the two-way synchronous motor to continue rotating in the original head shaking direction, and after a second preset time, controlling the two-way synchronous motor to rotate reversely to change the head shaking direction. According to the control method, the head shaking system can be controlled to work normally, and corresponding treatment can be performed in fault or abnormal situations, so that the stability of the system is improved. The invention also discloses the head shaking system, a fan and a warm air blower.

The invention relates to a cable buffer layer state evaluation method based on electric field analysis, and the method is mainly characterized in that the method comprises the following steps: carrying out the state detection of an XLPE cable in an operation state, and checking an XLPE cable which may have a defect; acquiring characteristic parameters of the XLPE cable which may have defects; building a cable structure platform by utilizing finite element software COMSOL, and building a finite element simulation model; adding a physical field; adding materials; setting boundary conditions; setting the grid as a physical field control network; setting a research type, and calculating electric field intensity; and judging the state of the cable buffer layer according to the calculated electric field intensity. The invention is not limited to qualitative analysis of the defect problem of the cable buffer layer any more, a quantitative analysis model is established based on a finite element method, a clear judgment basis is provided, maintainers can make accurate pre-judgment and take measures in advance, serious faults are avoided, and safe and reliable operation of an urban power system is guaranteed.

The invention discloses an old community photovoltaic building integrated reconstruction design method, and particularly relates to the technical field of building reconstruction design, and the method comprises the following steps: firstly, obtaining the three-dimensional structure data of a building through scanning equipment, and determining a suitable photovoltaic installation region based on a preset reconstruction region grade; calculating the bearing capacity of the photovoltaic module according to the transformation area, determining the total weight of the bearable photovoltaic module, and designing the initial distribution of the module; an inclination angle and an azimuth angle of a photovoltaic module are optimized through sunlight analysis, after installation is completed, an inverter is used for converting direct current into alternating current, the alternating current is connected to an intelligent power grid system, finally operation data are collected regularly, and a neural network is used for predicting faults and evaluating a health state. According to the invention, a feasible scheme is provided for large-scale popularization of renewable energy sources, the installation of the photovoltaic system can make full use of the idle space of old buildings, the utilization efficiency of solar energy resources is improved, the dependence on traditional energy sources is reduced, and the energy consumption of old communities is reduced.

The invention discloses an automobile fault diagnosis method and system, and belongs to the technical field of fault diagnosis, and the system comprises an automobile fault identification model, an automobile fault knowledge graph model and a reasoning diagnosis integration model. S100, acquiring a natural language description text of the automobile fault, preprocessing the natural language description text of the automobile fault, and extracting a description entity related to the automobile fault; s200, constructing an automobile fault identification model, inputting the description entity related to the automobile fault into the automobile fault identification model, and outputting a fault type; s300, constructing an automobile fault knowledge graph model, inputting a description entity and a fault type related to the automobile fault into the automobile fault knowledge graph model in combination with Cypher to perform semantic similarity matching, and querying a matched answer; and S400, constructing a reasoning and diagnosis integrated model, inputting the description entity and the answer related to the automobile fault into the reasoning and diagnosis integrated model in combination with prompt, and outputting a fault analysis result and a visual correlation analysis result.

The invention provides an assembly line fault identification method and system, and belongs to the technical field of assembly line fault identification, and the method comprises the steps: obtaining the multi-mode monitoring data of an assembly line; for the obtained multi-modal monitoring data, fusing the multi-modal monitoring data through a preset data fusion strategy to obtain fused data; wherein the data fusion weights corresponding to different dimensions of data in the data fusion strategy are dynamically adjusted based on the distance between the sensor data; based on the fusion data, a pre-trained space-time adaptive multi-modal analysis network model is utilized to obtain a fault identification result; wherein the space-time adaptive multi-modal analysis network model specifically executes the following processing processes: based on the fusion data, respectively extracting features of the fusion data on different time scales and distribution and relation of the fusion data on a spatial dimension, and obtaining time features and spatial features; and performing dynamic fusion on the time features and the space features to obtain fusion features.

The invention relates to the field of power electronization power system and discloses an overcurrent protection method of a direct current converter. The method comprises the steps of setting a direct current converter output current instantaneous protection value according to a design margin in an element selection process, making overload and fault current limiting index requirements of the direct current converter by a system to be clear, determining a voltage-current characteristic of direct current converter steady-state output, fitting a mathematical relationship between power and a maintenance time, and forming protection scheme according to the normal, overload, fault current limiting and instantaneous overcurrent working conditions. According to the overcurrent protection method of the direct current converter, the requirements of system selective protection is fully considered, with the coordination with other protection elements of the system or a device, the complete overcurrent protection function of the direct current converter in the normal, overload, fault current limiting and instantaneous overcurrent working conditions is realized, and the power supply continuity of an power electronization power distribution network is improved.

The invention relates to the technical field of equipment state evaluation, in particular to an evaluation method and system for the health state of offshore operation equipment. The method comprises the following steps: acquiring component data of offshore operation equipment; performing initial life marking on the data of the offshore operation equipment component to generate initial life marking data of the offshore operation equipment component; performing real-time operation data acquisition on the data of the offshore operation equipment component to generate real-time operation data of the offshore operation equipment component; performing component division on the real-time operation data of the components of the offshore operation equipment based on the components of the initial life mark data to generate novel component operation data and old component operation data; performing environment change influence analysis on the operation data of the novel part to generate an external change influence factor of the novel part. According to the invention, through multi-dimensional data acquisition, environment and electrical influence analysis, fatigue damage assessment and intelligent prediction, the accuracy of health state assessment of the offshore operation equipment is improved.

The invention discloses a method and system for monitoring a fault of a secondary exciter. The method comprises: phase voltages of a secondary exciter end are detected in real time; if all positive sequence voltages in the detected phase voltages are reduced to be a first threshold value and negative sequence voltages occur at the same time, inter-turn short circuit fault occurrence is determinedand alarming is carried out; if the phase voltages include three-phase voltages and the three-phase voltages are simultaneously lowered to be second threshold values or the phase voltages include two-phase voltages and negative sequence voltages occur in the two-phase voltages, inter-phase short circuit fault occurrence is determined and alarming is carried out; and if a zero-sequence voltage occurs, grounding short-circuit fault occurrence is determined and alarming is carried out. According to the invention, uninterrupted real-time monitoring is carried out during the running of the motor and thus the operating state, a fault part, and a fault cause of the single machine are determined. Alarming is carried out accurately before a serious fault occurring at a permanent-magnet auxiliary exciter and thus emergency measures are taken conveniently, so that the serious fault occurrence of burning the secondary exciter is avoided.

The invention provides a multi-sensor fusion turning tool state monitoring method and system, which relates to the technical field of turning tool state monitoring, and includes the following steps: collecting acoustic emission signals and current signals during the working process of turning tools; analyzing the acoustic emission signals and current signals After feature extraction, normalization processing is performed; the normalized data is input into the neural network model for result identification; in the above steps, after the steps of collecting acoustic emission signals and current signals, the step of determining the limit wear of the turning tool is also included, The turning tool limit wear judgment and feature extraction are carried out in parallel; the turning tool limit wear judgment method is as follows: in the light load area, through the acoustic emission signal judgment; in the medium load area, through the acoustic emission signal and current signal cooperative judgment; The load area is judged by the current signal. The invention combines the acoustic emission signal and the current signal to monitor the tool wear state, thus widening the monitoring range and improving the success rate of monitoring precision discrimination.

The invention relates to an ultraviolet light catalyzed waste water degradation reactor dilation method for self inspection of lamp source states and belongs to the technical field of waste water treatment. Problems that functions and states of electrodeless lamps cannot be known instantly, cavities of quartz tubes for shielding the electrodeless lamps have water burst, catalyst can be lost, microwave energy is wasted, capacity of single tanks is small, degradation reaction endpoint time is difficult to tell and the like exist in the prior art. The ultraviolet light catalyzed waste water degradation reactor dilation method is used for solving the problems and comprises: guiding one end of an optical fiber to the periphery of a quartz tube, enabling the end of the optical fiber to point to the inner cavity of the quartz tube, enabling the other end of the optical fiber to adhere to and point to a detection window of an ultraviolet light strength detector. The ultraviolet light catalyzed waste water degradation reactor dilation method further comprises other steps and totally solves all relevant problems.

The invention relates to a health state evaluation method, system and device for a numerical control machine tool and a medium, and the method comprises the steps: training model parameters of a health state analysis model based on each pre-obtained training sample data set, and calculating a corresponding likelihood probability, forming a preset model parameter set representing different preset working condition states of the machine tool by each group of trained model parameters, and forming a preset likelihood probability set by each likelihood probability; and based on the obtained preset model parameter set and the preset likelihood probability set, evaluating the health state of the current numerical control machine tool. According to the method, the historical monitoring data of the numerical control machine tool is utilized to construct the multi-dimensional data vector, the health state of the numerical control machine tool is evaluated by calculating the health degree, the number of machine tool sensors does not need to be increased, the model has wider practicability, the calculation complexity is reduced, and accurate, rapid and real-time health degree evaluation is achieved; the method can be widely applied to the numerical control machine tool health state monitoring field.

The invention provides an automatic production stamping method for automobile warm air heat exchanger accessories with reinforcing ribs, which belongs to the field of automobile processing and comprises the steps of die debugging, processing parameter setting, sensor mounting, processing flow execution, processing position control, processing quality control, finished product inspection and processing parameter optimization. Important machining procedures such as notching, reinforcing rib stamping, bending, cutting-off and material returning are continuously carried out, that is, multiple procedures are completed in one die, high integration of the machining procedures is achieved, all the procedures can be closely connected, transferring and repositioning of semi-finished products among all the procedures are reduced, and the production efficiency is improved. And meanwhile, the die replacement and debugging time is shortened, the production period is shortened, the optical sensor used for monitoring the position deviation of the material belt and the piezoresistive flexible sensor used for monitoring the pressure distribution of the material belt are additionally arranged, accurate positioning of the material belt in the stamping process is achieved, and the stability of the stamping quality is ensured.

The invention belongs to the technical field of aero-engine fault diagnosis, and relates to an aero-engine blade damage online identification method. Comprising the following steps: establishing a damage-free blade finite element model, and calculating modal frequency and vibration mode of each order; establishing a non-damage blade test model, and identifying test modal frequency and vibration mode; taking the previous 10-order test modal frequency as a target value, taking the blade material parameter as a variable, correcting the blade finite element model, obtaining an accurate finite element model, and calculating a stiffness matrix of each element, where the unit stiffness matrix is assembled into an overall vibration mode stiffness matrix; measuring blade vibration parameters in a working state; reading vibration parameters and rotating speed parameters in real time through an online monitoring system, correcting the finite element model to complete damage positioning, calculating the modal strain energy change rate to complete damage evaluation, and displaying an alarm when the damage amount exceeds the limit. The blade damage position and the damage degree can be determined online to complete feedback, serious faults are prevented, the repair cost is reduced, and the flight safety is guaranteed.