6870 results about "Electrical equipment" patented technology

The invention relates to the technical field of intelligent power distribution and electrical equipment state monitoring, in particular to an intelligent power distribution cabinet data acquisition control system and method, and the method comprises the steps: presetting a temperature sensor and a Hall sensor at the lap joint of a circuit breaker contact and a copper bar of an intelligent power distribution cabinet; calibrating inherent parameters of the system; in response to starting operation of the intelligent power distribution cabinet, the following steps are triggered: obtaining real-time load current, real-time environment temperature and actual temperature through filtering processing; generating a theoretical healthy temperature through a thermoelectric coupling evolution equation; calculating aging resistance increment through dynamic impedance differential evolution processing; generating an aging resistance estimated value through contact state multi-dimensional evaluation; generating a dynamic current limit value through an intelligent current limiting control model; outputting a control signal to adjust the operation state of the intelligent power distribution cabinet; according to the invention, the problem that a traditional single threshold scheme cannot accurately identify a real health state is solved, and the sensitivity and accuracy of contact aging detection are remarkably improved.

The invention discloses a non-intrusive household load identification method based on CUSUM event detection and a convolutional neural network, which is applied to total load data output by an intelligent electric meter installed at a user total incoming line, and comprises the following steps: data preprocessing; carrying out load event detection based on a sliding window bilateral CUSUM algorithm so as to determine an occurrence moment and a continuous interval of a load event; in a continuous interval corresponding to each load event, calculating an active power variation delta P, a reactive power variation delta Q, a current harmonic distortion variation delta Ihd and a current span Itc in steady-state data segments before and after the load event, and combining to form a multi-dimensional event feature vector; the method comprises the following steps: sequentially executing the steps on operation data of each electric device in a family in different operation modes to obtain a multi-dimensional event feature vector marked with a device type and an operation state label, and constructing a standardized device load feature database; and training a convolutional neural network classification model and realizing load identification.

The invention discloses a live detection method for insulation defects of high-voltage power equipment. The method comprises the following steps: firstly, synchronously arranging ultrahigh frequency sensors and acoustic emission sensors on a plurality of monitoring points on the surface of a gas insulated switchgear shell to form an array, and synchronously acquiring signals for filtering pretreatment; then, pulse events are extracted from the two types of signals respectively, and associated pulses in a time window are matched into matched pulse pairs representing the same discharge source; then, carrying out time-frequency transformation on the ultrahigh frequency and acoustic emission pulse waveform in each matched pulse pair, carrying out joint noise reduction by calculating a coherence coefficient between time-frequency distribution matrixes, and extracting a joint feature vector containing an energy ratio, a time parameter ratio and a frequency difference from the denoised time-frequency matrix; according to the invention, multi-source signals are fused, and high-sensitivity detection, high-precision positioning and high-accuracy identification of insulation defects are realized.

The invention discloses a method and a system for determining optimal parameters of an X-ray excited extra-high voltage composite apparatus, and relates to the technical field of extra-high voltage electrical equipment detection. The method comprises the following steps: remotely operating the X-ray machine and calculating partial discharge intensity; for the current irradiation position, the tube voltage and the tube current are gradually adjusted, parameters are dynamically optimized based on the quantitative relation between the partial discharge intensity and the radiation dose rate change rate, and the optimal parameters are recorded; and changing position repetition parameter optimization, and constructing a BP neural network model after data set training optimization so as to predict an optimal irradiation position. The optimized BP neural network adopts an improved sparrow search algorithm to optimize an initial weight and a threshold value, and combines Bayesian to optimize a learning rate and a hidden node number. Accurate optimization of excitation parameters and irradiation positions is achieved, detection accuracy and safety are both considered, the optimal irradiation position positioning efficiency is improved, and the method is suitable for ultra-high voltage GIS detection of different voltage grades.

The invention relates to the field of intelligent control of electromagnetic appliances, and provides a control method and system for online fault diagnosis of a magnetic latching relay, and the method comprises the steps: responding to an external control instruction, collecting real-time bus voltage and real-time environment temperature data, constructing environment state characteristics through a magnetothermal coupling algorithm, and generating an initial PWM drive duty ratio; pulse modulation voltage is loaded, a current sampling sequence is collected, a current change rate sequence is obtained through moving average filtering and electromechanical coupling decoupling, extreme value searching is executed to extract counter electromotive force distortion characteristics, and a dynamic current sequential sequence is generated; a fusion input tensor is constructed, armature state probability distribution is output through a gating circulation unit, and a real-time energy compensation instruction is generated in a displacement interval before closing; and according to the real-time energy compensation instruction, respectively generating an enhanced driving waveform, a delayed driving waveform or a vibration driving waveform. According to the method, multi-mode physical characteristic perception and depth time sequence deduction are fused, and online fault diagnosis and active intervention closed loop of the magnetic latching relay are realized.

The invention relates to the technical field of electrical equipment state monitoring and fault early warning, and particularly discloses an electrical cabinet condensation risk online monitoring method and system, and the method comprises the steps: synchronously collecting the physical parameters of the same microscopic space point in an electrical cabinet; calculating the classical dew point temperature by adopting a Magnus formula; performing quantification processing on the air pressure micro-fluctuation data in the time window, and calculating information entropy of micro-air pressure fluctuation; the wall surface temperature gradient and the air flowing state are fused, and the equivalent dew point temperature is calculated; real-time safety margin is calculated, and the instantaneous change rate of the safety margin is solved; constructing a condensation risk trend index; comparing with a preset threshold value, generating an early warning signal and a risk diagnosis label, and completing condensation risk monitoring; the system comprises a multi-physical field sensing unit, an embedded processing unit, a self-adaptive control unit, a man-machine interaction unit and a communication unit which are integrated in the same shell.

The invention relates to the technical field of electrical equipment fault diagnosis, in particular to an electrical equipment fault diagnosis method and system based on a knowledge graph, and the method comprises the steps: obtaining the multi-mode sensing data of electrical equipment, and constructing a fault diagnosis knowledge graph; mapping entities and relationships in the atlas to a low-dimensional continuous vector space by adopting a knowledge representation learning algorithm, and extracting semantic feature vectors; inputting the data into a graph neural network model to learn neighborhood information, executing link prediction and knowledge completion, and determining a potential fault causal chain in a preset operation environment; and matching the causal chain with the logic rule base, performing causal logic derivation on the diagnosis result in combination with a large-scale language model, and outputting a fault root cause analysis report and an operation and maintenance management decision suggestion. According to the method, multi-modal perception data and knowledge representation learning are deeply fused, implicit fault association which is not explicitly recorded in historical operation and maintenance data is mined by using a graph neural network, and interpretable analysis is provided in combination with a language model.

The invention provides a compact intelligent switch cabinet, which belongs to the technical field of intelligent switch cabinets and comprises an intelligent switch cabinet body, a switch cabinet back plate is arranged on the outer wall of one side of the intelligent switch cabinet body, and a switch cabinet door is hinged to the outer wall of the other side of the intelligent switch cabinet body. A transverse partition plate is arranged in the middle of the inner side wall of the intelligent switch cabinet body, a concave hole is formed in the outer wall of one side of the transverse partition plate, and an electrical equipment compact installation assembly and a locking linkage assembly are arranged on the inner side of the intelligent switch cabinet body. According to the electrical equipment compact installation assembly, electrical equipment can be adaptively and horizontally arranged and installed in the intelligent switch cabinet according to the thickness of the electrical equipment, so that the space occupied by tiled installation of the electrical equipment is reduced, and the electrical equipment installed in the intelligent switch cabinet can be conveniently overhauled, replaced and installed; and the intelligent switch cabinet can be manufactured to be more compact and can be flexibly expanded so as to adapt to frequently-changed power utilization requirements.

The invention provides an electrical button, which has a accommodating groove with a accommodating cavity, an elastic fixing member and a rigid pressing member are arranged on the accommodating groove; the elastic fixing member has an upper ring cover and a lower ring cover, forming a first clamping groove; the upper ring cover and the lower ring cover The outer periphery of the ring cover is connected by the cap wall, and the lower end of the cap wall is clamped in the connecting groove of the side wall of the receiving groove; the outer periphery of the lower end of the cap wall is provided with an upper fixing edge and a lower fixing edge to form a second clamping groove; The first clamping plate in the first clamping groove, the first clamping plate is provided with a pressing plate; the first clamping plate is provided with a guide post, and the lower end of the guide post is provided with a moving contact; the bottom surface of the receiving cavity is provided with a first static contact and the second static contact; the outer guide post is provided with an elastic piece, the upper end of the elastic piece is provided with an upper fixed end, and the lower end is set with a lower fixed end; the upper fixed end is clamped in the upper fixing groove of the first clamping plate, and the lower fixed end is clamped Connected to the lower fixing groove in the receiving cavity. The invention realizes double reset through the cap wall and the elastic member, so as to avoid the push button from being dead; the sealing performance is good, and dust and water are prevented from entering.

The invention discloses a sealing structure for a test, and an aging test and leakage rate detection method and system. The sealing structure comprises a tested sealing assembly and an air cavity assembly integrated in the tested sealing assembly, and serialized test samples with different filling rates and compression rates are formed by regulating and controlling the groove width and the groove depth of a sealing ring mounting groove so as to simulate various actual sealing states. An aging test adopts a multi-factor coupling accelerated aging method, and a plurality of material characterization means are combined to systematically evaluate the evolution rule of the sealing performance. According to leakage rate detection, static pressure maintaining and dynamic pressure adjusting dual-mode measurement is achieved through an air tightness detector, and the sealing characteristics under different pressure conditions are comprehensively reflected. According to the invention, direct and systematic detection of the leakage rate of the sealing structure is realized, and an innovative solution is provided for sealing performance evaluation and service life prediction of electrical equipment.

The invention discloses an anti-condensation and humidity control system of a low-voltage switch cabinet, and relates to the technical field of environment regulation and control of low-voltage electrical equipment, and the system comprises a data collection module which collects data through a multi-region temperature and humidity sensor; the humidity prediction module is used for predicting 30-minute humidity by using a long-short-term memory neural network in combination with cabinet body parameters and historical data, and pre-evaluating the condensation risk; the anti-condensation execution module is used for starting a PTC heating device, an axial flow ventilation device or a semiconductor dehumidification device according to the prediction result; the system linkage module interacts with an electric power monitoring system and adjusts parameters of the execution device when the load is high; the parameter self-learning module is used for optimizing the prediction model and recording optimal threshold values of the device in different environments; and the safety protection module is used for monitoring the heating temperature and the condensate water level and switching an emergency strategy when a fault occurs. The system has the advantages of comprehensive monitoring, accurate prediction, cooperative operation of execution devices, adaptation to different environments and loads, reduction of condensation faults, prolongation of the service life of elements, and improvement of the operation reliability of the switch cabinet.

The invention discloses an automatic welding mechanism of a foil winding machine, and relates to the technical field of electrical equipment manufacturing, the automatic welding mechanism comprises a supporting plate, and first supporting rods are symmetrically arranged at the top of the supporting plate; the traction mechanism is arranged on the first supporting rod; the supporting frame is arranged on the supporting plate, and a feeding belt is arranged at the top of the supporting frame; and the foil winding mechanism is arranged on one side of the traction mechanism and comprises a pair of mounting plates and a pair of mounting plates which are respectively arranged on the pair of mounting plates. By integrating the feeding and traction mechanism, the foil winding mechanism, the induction mechanism, the cutting and tensioning adjusting device, the positioning and welding device and the limiting mechanism and optimizing the cooperative relation and action logic of all the components, full-process automation from foil belt feeding, tension control, fixed-length winding, automatic cutting to precise positioning and welding of the tail end of a foil roll is achieved.

The invention belongs to the technical field of electrical equipment state monitoring, and particularly discloses an electrical equipment intelligent online monitoring system and method based on multi-parameter fusion. Comprising the following steps: synchronously acquiring a partial discharge parameter, a mechanical characteristic parameter and a temperature rise parameter during operation of equipment, performing signal preprocessing on the parameters respectively, and constructing a multi-dimensional feature vector for diagnosis; the multi-dimensional feature vector is combined with a time sequence correlation model, a trend correlation model and an intelligent diagnosis model to output the multi-dimensional feature vector, collaborative decision making is carried out on an analysis result through a D-S evidence theory, and an equipment state evaluation conclusion and early warning information are generated and output in a visual form; according to the method, the monitoring limitation of a single parameter is overcome, early warning can be realized while the diagnosis accuracy is improved, the operation and maintenance efficiency is further improved, and the comprehensive diagnosis after deep analysis is also helpful for operation and maintenance personnel to take corresponding measures in time.

The invention relates to the technical field of electrical equipment state monitoring, in particular to an intelligent circuit breaker electrical life detection method and system based on data analysis. The method comprises the following steps: synchronously acquiring opening coil voltage and current sequences, a main loop current sequence and environment temperature data when a circuit breaker acts, extracting actually measured action time based on the coil data, and calculating a mechanical health degree factor by combining the environment temperature and the actually measured action time; after decoupling correction is carried out on an electrodynamic force interference factor derived by a peak current of a main loop, a mechanism wear state index is obtained; a nonlinear damage model containing basic electric heat loss and mechanical degradation acceleration factors is constructed, a single-time electric life loss value is calculated, historical loss values are accumulated, a dynamic threshold value is combined to realize full-life-cycle prediction, and evaluation interference of environmental factors and large-current electrodynamic force is eliminated through deep data analysis. The nonlinear acceleration effect of mechanism hysteresis on contact ablation is quantified, and the detection precision is remarkably improved.

The invention discloses a method and a system, and relates to the technical field of relay protection. The method comprises the following steps of: acquiring electrical data of a synchronous parallel point, inputting two paths of voltage data, setting a setting value, judging the state of the synchronous parallel point based on the input two paths of voltage data, and performing manual intervention on asynchronous protection after asynchronous protection quits. According to the grid-connected asynchronous protection method provided by the invention, the state of a synchronous parallel point can be accurately judged by comparing the output two paths of voltage data with the setting value set in the device, the fault condition and position of a power grid can be more accurately judged, the abnormal state can be quickly detected, a circuit breaker can be timely pulled open, and the safety of the power grid is ensured. The method prevents generation of strong impact current, prevents burning loss of equipment, effectively protects electrical primary equipment, compares timing time with a setting value set by a system, ensures that non-synchronous protection does not continue to work due to misoperation, and enables an electric power system to recover to normal more quickly. According to the invention, better effects are achieved in the aspects of preventing electric appliance burnout and response time.

The invention discloses a multi-layer insulation space power equipment pile head warning lamp capable of being installed without power outage and an installation method, and aims to solve the problems that an existing insulation protective cover is fast in aging, poor in insulation, not firm in fixation and incapable of being installed without power outage, and the multi-layer insulation space power equipment pile head warning lamp comprises a cover body, a left sliding block, a right sliding block and two sets of turnover type locking mechanisms. According to the cover body, an inner layer plate, an outer layer plate and a connecting plate form a double-layer structure, a left sliding way and a right sliding way are formed, a sliding block adopts a double-layer insulation design and is matched with a one-way ratchet structure to achieve self-locking, two sets of overturning type locking mechanisms complete mechanical locking of a notch, a pressing rod is driven to operate through an insulating rod during installation, power failure is not needed, and installation is convenient. Fixing is completed through the three steps of positioning, locking and sliding block closing, the protective cover is arranged in a suspended mode, the insulation distance is increased, insulation is stable, wind resistance is high, aging is slow, warning can be achieved, and the protective cover is suitable for protection of various power equipment heads and excellent in practicability.

The application relates to the technical field of electrical equipment, in particular to a primary and secondary fusion complete column circuit breaker, which comprises a circuit breaker main body, one side of the circuit breaker main body is provided with an operating handle, the operating handle is fixedly connected with a take-up seat arranged at both ends, a winding shaft is rotatably connected in the take-up seat, a steel wire rope is fixedly arranged on the winding shaft, a protective cover is movably inserted on one side of the take-up seat, an air extraction seat is fixedly connected on the other side of the take-up seat, a fixing frame is fixedly connected on the take-up seat, a transmission mechanism is rotatably connected on the fixing frame, the steel wire rope is arranged at both ends of the operating handle, the winding shaft can be used to lift the handle connected with the steel wire rope, the operator does not need to directly contact the handle, especially in the case that the power column is high or not easy to approach, the operation can be realized by pulling the steel wire rope, the convenience of operation is improved, the need of climbing or using a ladder is avoided, and the risk of high-altitude operation is effectively avoided.

The invention provides a circuit breaker monitoring method and system based on multi-state sensing, a medium and equipment, and relates to the technical field of electrical equipment monitoring. According to the technical scheme provided by the invention, the initial influence weight of the directed edge is dynamically updated into the target influence weight according to the weight adjustment rule corresponding to the event type of the operation event, so that the fault propagation map accurately reflects the actual change of the influence relationship of the current operation event on the components. And calculating the first node health degree of each node based on the updated target influence weight and the multi-dimensional state data, accurately evaluating the current health state of the circuit breaker, predicting the second node health degree within the duration of the operation event, and realizing the pre-judgment of the development trend of the health state. According to the first node health degree and the second node health degree, the monitoring mode is determined, and the early warning response of the corresponding level is triggered, so that the timeliness and pertinence of early warning are ensured, and the accuracy of monitoring and early warning of the circuit breaker can be improved.

The invention discloses an electric power inspection method fusing semantic extraction, propagation and updating. The method comprises the following steps: step 1, acquiring electrical equipment images in various scenes and preprocessing the electrical equipment images; fusing the preprocessed data set with a public data set and a data set in an internal database of the power grid; 2, obtaining a high-confidence target detection result and a pixel-level fault area segmentation mask; 3, fusing the high-confidence target detection result and the pixel-level fault area segmentation mask, extracting fusion information by using a MobileNetV3 model, enhancing feature expression, and generating accurate description information; 4, comparing and fusing the accurate description information with a historical semantic database, and constructing a multi-dimensional semantic map; and 5, carrying out structured coding on the multi-dimensional semantic map to realize reliable lightweight transmission in a network-free area, and synchronously completing equipment positioning and state information reporting. According to the method, efficient and stable return of the routing inspection semantic information is realized.

The invention relates to the technical field of electrical equipment fault detection, and discloses an electrical equipment fault detection method and system based on reinforcement learning, and the method comprises the steps: collecting the multi-modal operation data of an electrical equipment group, and constructing a dynamic heterogeneous data set; according to the dynamic heterogeneous data set, a change mode of equipment operation is extracted, and distribution feature representation is determined; according to the distribution feature representation, constructing an inter-equipment association graph model, and generating an association-enhanced feature representation; carrying out anomaly detection on the association enhanced feature expression, judging node deviation and backtracking to obtain a potential fault starting point; according to the potential fault starting point, simulating a propagation dynamic state between nodes and tracking a chain reaction path to obtain a fault propagation sequence; and carrying out reaction intensity calculation on the fault propagation sequence, generating an early warning signal, outputting the early warning signal, backtracking and updating the graph model according to the early warning signal, and determining a final fault source position. According to the method, early warning, propagation tracking and accurate traceability of faults of the electrical equipment group can be realized.

The invention discloses a hydropower engineering electromechanical equipment installation detail control method based on a three-dimensional laser scanning technology, and the method comprises the steps: S1, setting and determining the instrument parameters of a three-dimensional laser scanner, and collecting the point cloud data of a target region through the three-dimensional laser scanner; s2, remotely reading the point cloud data through a computer, uploading the point cloud data to a cloud database in a file stream form, and storing the point cloud data; s3, performing iterative fitting on the plane model by using a random sample consensus algorithm RANSAC and removing inner points, fitting a target ball model by multiplexing the RANSAC algorithm in the residual point cloud data after the plane model is removed, and screening target ball parameters with the maximum number of inner points; s4, constructing a combined reference model based on the electromechanical equipment to be installed and the virtual target ball, and performing coordinate deviation value comparison with the actually measured target ball model to obtain a deviation value; and S5, generating an installation detail adjustment scheme according to the coordinate deviation value, and sending the adjustment scheme to a mobile client of the field installation personnel.

The invention belongs to the technical field of electrical equipment safety monitoring, and provides an intelligent wire and cable distributed optical fiber temperature measurement early warning method and system, and the method comprises the steps: laying a distributed optical fiber temperature sensor network along a cable, and synchronously demodulating the temperature and strain information based on a distributed optical fiber sensing principle; the temperature, the strain information and the load current are uploaded to a cloud platform through a wireless communication module; operating a time-space fusion diagnosis model driven by a cable physical mechanism on a cloud platform to distinguish and position an abnormal overheating section caused by a current Joule heating effect, insulation loss or contact resistance dramatic increase; and after the abnormity is confirmed, the cloud platform generates a control instruction for the abnormal overheating section to cut off power supply, and an intelligent self-healing process can be started. According to the invention, physical root identification, accurate positioning and safe self-healing of the cable overheating fault are realized, and the safety of cable operation is greatly improved.

The invention discloses a super-amphiphobic flame-retardant ice-resistant coating as well as a preparation method and application of the super-amphiphobic flame-retardant ice-resistant coating with a multi-layer surface coating, and belongs to the technical field of functional materials of electrical equipment. The coating comprises micron-sized ammonium polyphosphate, a nano-sized inorganic filler, fluorinated alkyl silane and a fluorine surfactant, the super-amphiphobic, flame-retardant and ice-resistant coating is constructed through multi-scale components, and the super-amphiphobic, flame-retardant and ice-resistant coating is spontaneously assembled on the surface of a base material in the coating process to form a coating surface with a molecular nanometer, micrometer and macroscopic multi-level structure; the coating shows good super-amphiphobic characteristics, the contact angle of the structure surface after long-time placement under the room temperature condition is basically kept unchanged, the contact angle to water and oil is still larger than 150 degrees after multiple times of cyclic friction and washing, meanwhile, the coating has excellent flame retardance, ice resistance and wear resistance, the icing delay time is greatly prolonged, and the coating has the good anti-freezing effect. And no open fire is generated when the cable is in contact with an external fire source, so that the cable has important engineering application value for electric power facilities under harsh environmental conditions.

The invention discloses a defect detection method and system based on insulator multi-modal image fusion, and relates to the technical field of electrical equipment defect detection, multi-modal image fusion is performed based on an attention mechanism improved RFN-Nest image fusion model, fusion of infrared image temperature anomaly features and visual image structure detail features is enhanced, and the defect detection accuracy is improved. The information entropy, mutual information and other indexes of the generated fusion image are remarkably superior to those of an original model and a traditional fusion method, high-quality data support is provided for a detection task, then defect detection is carried out based on an attention mechanism improved YOLOv8 target detection model, the defect feature discrimination capability and the anti-interference capability are improved, and the detection efficiency is improved. The problems of missing report and false report of insulator defects in a complex scene are effectively solved, the performance is remarkably improved compared with a traditional independent link design scheme, and the method can be directly applied to an actual electric power inspection scene.

The invention relates to the technical field of fire prevention, and discloses a high-and-low-voltage power distribution room fire prevention early warning system based on potassium ion aerosol fire extinguishing, which comprises a smoke fire detection module used for detecting fire related data inside and outside a high-and-low-voltage power distribution room; the fire related data comprises smoke data and temperature data; the comprehensive evaluation module is used for judging whether an adopted evaluation model is a temperature evaluation model or a smoke evaluation model according to the fire related data; the fireproof grade classification module is used for grading fireproof grades in the high and low voltage power distribution room according to the screened evaluation model; the fire prevention measure implementation module is used for starting the potassium ion aerial fog fire extinguishing equipment in the corresponding fire prevention subareas to extinguish fire according to different grades; the electrical characteristic monitoring module is used for monitoring the load current and arc signal intensity of electrical equipment in the high-low voltage power distribution room and the temperature change rate of key nodes in real time; according to the invention, multi-dimensional accurate monitoring and graded prevention and control of the fire risk of the high and low voltage power distribution room are realized.

The invention discloses a multi-task NILM low-voltage transformer area energy management system, and aims to solve the problems that a traditional low-voltage transformer area energy management system (EMS) is low in load identification precision and does not give consideration to operation cost and user satisfaction. According to the system, firstly, through an NILM module based on a multi-task recurrent neural network (taking a GRU as a core), power utilization states and power consumption of various electric appliances are decomposed from total load data of an intelligent electric meter, and a user power utilization behavior portrait is constructed; and taking the portrait as an input, and carrying out cooperative scheduling on photovoltaic, energy storage and controllable loads in a transformer area through a multi-objective optimization model considering system operation cost and user satisfaction. Experimental verification shows that compared with a traditional EMS, the operation cost of the system is reduced by 32.59%, the user satisfaction degree is improved by 65.89%, the load identification precision of an NILM module is remarkably superior to that of CNN, LSTM and a single-task GRU model (MAE is as low as 1.574 W, and the F1 score is as high as 0.973), and intelligent and economical operation of a low-voltage transformer area can be effectively promoted.

The invention provides a relay zero-crossing time-delay calibration circuit and electrical equipment. The relay zero-crossing time-delay calibration circuit comprises a sampling circuit, a comparison module, a logic circuit and an output interface used for an external control equipment port, the sampling circuit is respectively connected with a static contact and a movable contact of the relay and is used for sampling voltage values of the static contact and the movable contact of the relay, outputting the voltage value of the static contact through a first output end of the sampling circuit and outputting the voltage value of the movable contact through a second output end of the sampling circuit; the comparison module is respectively connected with the first output end and the second output end, and the output end is connected with the logic circuit; the comparison module is used for outputting an effective driving signal to the logic circuit under the condition that the static contact voltage value is equal to the movable contact voltage value; and the logic circuit is connected with the output interface and is used for pulling up or pulling down the potential of the output interface when the effective driving signal is received.

This invention relates to a sampling device and method for sulfur hexafluoride (SF6) and its mixed gases used in electrical equipment. The sampling device includes an equipment connection module, a sampling module, a gas filling module, and a vacuuming module. The equipment connection module, used to connect the electrical equipment and the gas sampler, consists of an equipment connection valve, a diaphragm pump, and corresponding pipelines. The sampling module, used for gas buffering, consists of a sampling cylinder, a pressure detection unit, a sampling valve, a gas filling valve, a tail gas valve, and corresponding pipelines. The gas filling module, used to fill the sampling container, consists of a booster pump, a sampling container connection valve, and corresponding pipelines. The vacuuming module, used for vacuuming and tail gas collection, consists of a vacuum pump, a tail gas collection device, and its connection valves. The sampling method utilizes appropriate flushing and vacuuming methods when the gas pressure is higher or lower than 0.2 MPa. This sampling device and method can improve the accuracy of sampling sulfur hexafluoride gas or sulfur hexafluoride mixed insulating gases.

The invention relates to a commercial place illegal power utilization identification system and method based on a non-intermediary technology, and relates to the technical field of electric power supervision, and the system comprises a metering module which collects the voltage and current data of various electric appliances; the main control CPU is used for generating an electric appliance operation waveform file based on the data, converting and outputting the electric appliance operation waveform file to the non-intrusive load identification module, analyzing whether illegal electricity utilization exists in an electricity utilization place, including a living risk probability and a charging risk probability, and generating and uploading alarm data when the illegal electricity utilization is detected; the non-intrusive load identification module is used for identifying and analyzing the waveform file and outputting the use condition of the electric appliance to the main control CPU; and the dual-mode communication module receives the alarm data uploaded by the master control CPU and uploads the alarm data to an acquisition master station through dual-mode carrier communication, and all the modules are in telecommunication connection. According to the invention, accurate identification and traceability positioning of hidden illegal power consumption behaviors can be realized.

The invention provides a water immersion and electric leakage monitoring method, device, system and equipment for power equipment, and relates to the technical field of power equipment safety monitoring. The method comprises the following steps: acquiring electrical monitoring data of a grounding wire of power equipment and water level monitoring data of an area where the power equipment is located; judging whether an electric leakage event occurs or not according to the electrical monitoring data; water immersion event judgment is conducted according to the water level monitoring data, when the water level monitoring data exceed a preset water level threshold value, visual review operation is triggered, and whether a water immersion event occurs or not is judged based on the result of the visual review operation; and determining different alarm levels according to a combination condition between the judgment result of the water immersion event and the judgment result of the electric leakage event, and executing alarm responses corresponding to the alarm levels. According to the method, the electrical monitoring data is obtained in a non-contact manner, and a dual verification mechanism of'water level threshold triggering + visual rechecking 'is established, so that the water immersion and electric leakage states of the electrical equipment can be quickly and accurately identified.