1172 results about "Insulation resistance" patented technology

The invention discloses an insulation detection method for an electric automobile, belongs to the technical field of high-voltage safety monitoring of the electric automobile, and solves the problem that the insulation detection precision is reduced due to electromagnetic interference, impedance fluctuation and capacitive effect coupling in a dynamic load switching process. According to the scheme, a test sequence of discrete frequency points is applied to a high-voltage system; measuring a response current value through a current sensor and calculating a ground distributed capacitance value; connecting a test voltage source between positive and negative electrodes of the high-voltage system through a coupling circuit; applying a first pulse signal during no-load, dynamically setting the width according to the capacitance value, measuring a first response current value, and calculating an initial insulation resistance value; a second pulse signal with the same parameter is applied in the load state window, a second response current value is measured, and differential filtering is carried out in combination with the initial value to eliminate load noise; and comparing the filtered insulation resistance value with a threshold value, and outputting a fault signal when the insulation resistance value is lower than the threshold value. The method is used for monitoring the insulation state of the high-voltage system in real time and accurately early warning faults.

The invention relates to a low-voltage motor insulation resistance online monitoring and early warning method, system and device and a medium. The method comprises the following steps: firstly, acquiring multi-dimensional operation data through a data acquisition link to form an original monitoring data set; preprocessing the original monitoring data set, and focusing core information through dimension reduction processing to obtain a key parameter set; and then inputting the key parameter set into a dynamic correlation model constructed based on a long short-term memory network, and outputting a prediction result of the variation trend of the insulation resistance value along with time and the deterioration degree quantification. And finally, carrying out early warning analysis based on a prediction result, and generating early warning fault features in combination with a real degradation judgment process. According to the method, the insulation resistance trend and the degradation degree are accurately predicted, the defect of insufficient real-time performance of off-line detection is overcome, the accuracy and the pertinence of fault early warning are improved, and equipment shutdown and safety risks caused by insulation faults are effectively reduced.

The invention belongs to the technical field of low-voltage switch cabinet operation control, and particularly discloses an intelligent low-voltage switch cabinet system based on a building intelligent function, which comprises an operation sensing module, a spatial topology module, a fusion diagnosis module, a fault positioning module and a dynamic protection module, current and insulation resistance are synchronously detected at a circuit wiring terminal of the low-voltage switch cabinet, temperature and humidity distribution data of the surrounding environment are collected, and then coupling characteristics between the current and temperature rise are fused. And carrying out visual display of coupling and time sequence correlation in the built three-dimensional heat-electricity correlation topological graph in the switch cabinet by utilizing the time sequence correlation between the insulation resistance and the humidity change, so as to realize comprehensive identification of potential faults. According to the method, the sensitivity and the accuracy of fault identification are effectively improved, early fault symptoms such as poor contact and insulation degradation can be found earlier, the early warning capability of the system is enhanced, and the safety and the stability of operation of the switch cabinet are guaranteed.

The invention discloses a water pump motor fault detection method and system, and belongs to the technical field of detection, and the method comprises the steps: building an electrical operation state model based on current, voltage and three-phase balance degree, and outputting an electrical state coefficient; predicting a resistance degradation trend by using the historical winding / insulation resistance data set, and generating a resistance prediction coefficient; combining the electrical state, the amplitude under the load and the flow of the water pump to construct a vibration-flow matching coefficient; fusing the resistance prediction coefficient, the noise index and the temperature index, and outputting a fault evaluation coefficient through a fault evaluation model; and when the fault evaluation coefficient exceeds a threshold value, shutdown is triggered. The system correspondingly comprises an electrical analysis module, a resistance prediction module, a state evaluation module and a fault decision module. According to the invention, early fault accurate detection is realized by fusing multiple parameters, and the reliability of the water pump motor is improved.

The invention discloses an insulation resistance and capacitance measuring circuit and method based on monopulse double-edge analysis, and relates to the related field of the electrical insulation online monitoring technology, and the circuit comprises a detected object and an insulation detection circuit. The insulation detection circuit comprises a controlled pulse voltage source, a coupling resistance network, a current sensor, a switch control module, a signal modulation circuit and a processor. The measurement method implemented based on the circuit comprises the following steps: injecting a common-mode voltage pulse into a transmission line of the power transmission system by adopting a pulse transmitter; pulse current response is collected in real time, a current oscillogram is drawn, and a three-point sampling method is introduced to record a current value for insulation impedance parameter calculation; according to a load condition, a double-edge verification method is applied based on a pulse current attenuation characteristic, and insulation impedance parameters including a resistive component and a capacitive component are independently calculated by analyzing a pulse current rising edge and a pulse current falling edge. According to the invention, non-intrusive synchronous monitoring of resistive and capacitive components of line-to-ground impedance is realized, and the detection precision is improved.

The invention discloses a comprehensive management system for intelligent power distribution, and the system comprises a sensing layer which is provided with a plurality of sensors, the sensors are disposed on power distribution equipment, and are used for collecting the operation data of a power distribution system in real time, and the operation data comprise a current I, a voltage U, a power P, an equipment temperature T, a power factor cos phi, and an insulation resistance R; the transmission layer is used for transmitting the operation data to a data layer; the data layer is used for preprocessing the operation data to generate standardized data, and preprocessing comprises data cleaning and normalization conversion; and the application layer comprises a fault early warning module, a predictive maintenance module, an energy consumption analysis module and a remote control module, and the application layer realizes collaborative management by calling the standardized data. Multi-dimensional data fusion, a dynamic intelligent algorithm and a module interaction mechanism are introduced, and full-process intelligence of power distribution management is achieved.

The invention discloses a square lithium ion battery external insulation damage detection method, system, medium and equipment, and the method comprises the steps: carrying out the electrochemical impedance spectrum measurement of a square battery with an external insulation state to be detected, and obtaining an electrochemical impedance spectrum; building an equivalent circuit based on the electrochemical impedance spectrum to obtain each characterization electrical element parameter in the equivalent circuit; high-frequency insulation resistance and interface capacitance in the equivalent circuit are extracted, and the damage condition of the outer insulation film of the square lithium ion battery is detected through parameter differences.

The invention relates to the technical field of on-line monitoring, in particular to an insulation fault on-line monitoring method and system for a medical IT system control cabinet. The method comprises the following steps: selecting a non-integer frequency multiplication detection frequency according to equivalent ground distributed capacitance in a previous monitoring period, and superposing the non-integer frequency multiplication detection frequency with a fundamental frequency to form a composite signal injection system; collecting signals to calculate a voltage instantaneous harmonic distortion rate change gradient, and selecting a time window to split the leakage current according to the change gradient; on the basis of dispersion estimation signal-to-noise ratio weighted fusion current vectors, insulation resistance and distributed capacitance are calculated; constructing a four-dimensional original feature vector composed of the insulation parameter, the phase difference and the intermodulation component energy; constructing a diagonal weighting matrix based on the resistance-capacitance ratio and the gradient to transform a feature vector, and determining the fault attribution through the Mahalanobis distance calculation with the fault template library. According to the scheme, harmonic interference can be avoided, calculation stability can be improved, insulation instantaneous sudden change can be quickly responded, and different fault types can be accurately distinguished to guide maintenance.

The invention relates to the field of lightning arrester parameter measurement, in particular to a lightning arrester parameter measurement system and method.The lightning arrester parameter measurement system comprises an induction unit, a detection unit, a data processing unit and a control and positioning unit and is used for generating and focusing laser on the surface of a lightning arrester, collecting an electrical signal and an optical signal of plasma and sending the electrical signal and the optical signal to a processor; the feature quantity is obtained through a feature extraction algorithm, and core parameters of the inversion lightning arrester are calculated through mechanical learning. Plasma is generated through laser focusing, reduction of errors caused by direct electrical connection and contact resistance with a lightning arrester is avoided, the problems of potential safety hazards and interference of traditional contact type measurement are solved, laser focus global scanning, real-time dynamic monitoring and efficient measurement are achieved through the three-dimensional electric translation platform, and the measurement precision is improved. All key areas on the surface of the lightning arrester are covered, compared with single parameter inversion in the prior art, multiple parameters and microscopic parameters are considered, and the prediction precision of key core parameters such as insulation resistance based on the random forest model is further improved.

The invention belongs to the technical field of power distribution switches, and particularly discloses a test mechanism suitable for a switch cabinet handle, which comprises a substrate, the upper end of the substrate is fixedly connected with a plurality of support frames, the upper ends of the support frames are fixedly connected with a support plate, and the upper end of the support plate is provided with a transmission groove. A rotating assembly used for rotating the handle is arranged on the base plate corresponding to the transmission groove, a detection assembly used for detecting the insulation state of the rotating handle is arranged on the side, close to the rotating assembly, of the supporting plate, and when the handle rotates along with the second square rod, the first square rod, the transmission block and the trigger protruding block are driven to rotate synchronously. The trigger bump can instantly extrude the micro-touch switch, the power supply module and the resistance detector are started, through a detection loop formed by a lead, insulation resistance changes of the connection part of the handle and the square rod under the action of mechanical friction and stress in the rotation process are accurately captured, dynamic insulation data of the handle are captured, and an electrical property detection test of the handle is realized.

The invention relates to the technical field of cable fault positioning, in particular to a cable fault accurate positioning method based on multi-channel synchronous acquisition, which comprises the following steps: S1, constructing a multi-channel adaptive acquisition system which comprises a main controller, a multi-channel acquisition module, a synchronous control module and a data transmission module; s2, multi-channel data synchronous acquisition is carried out through the synchronous control module, wherein the multi-channel data comprises impedance data, temperature data, partial discharge signals and insulation resistance data; during use, through a multi-channel adaptive acquisition design, monitoring channels can be flexibly selected according to cable materials, operation years and environmental conditions, different aging fault characteristics are comprehensively covered, the fault omission ratio and the false alarm rate are reduced, different types of low-voltage cables are adapted, a synchronous scheme of constant-temperature crystal oscillator and hardware triggering is adopted, and the reliability of the system is improved. The method does not need to depend on a GPS / PTP time service module, is favorable for saving cost input, and eliminates environmental interference and single parameter false triggering.

The invention, which belongs to the technical field of the direct-current charging pile, provides a direct-current charging pile rapid detection diagnosis debugging system comprising a detection host, a multi-channel data acquisition module, an electric energy quality analysis module, an insulation resistance test module, a grounding resistance test module, a communication protocol analysis module, a temperature monitoring module and a fault simulation module. Parallel data acquisition is realized by adopting 16 independent analog signal acquisition channels and 8 digital signal acquisition channels, a parallel processing unit matched with the number of detection channels is started by utilizing a CUDA flow technology, preliminary fault screening is carried out at a GPU end through a rapid shallow model, and a layered diagnosis mechanism of accurate fault analysis is carried out at a CPU end through a deep model. And in combination with the charging pile fault identification model, real-time monitoring of the operation state of the charging pile and accurate identification and positioning of the fault are realized, and the technical problems of low real-time processing efficiency of multi-channel data and insufficient fault diagnosis accuracy are solved.

The invention provides a photovoltaic system and an insulation resistance detection method thereof, the photovoltaic system comprises a plurality of photovoltaic modules, a plurality of low-voltage switches, a plurality of high-voltage switches and a detection control circuit, the low-voltage switches are connected with one or more photovoltaic modules to form a second photovoltaic module, and the high-voltage switches are connected with the detection control circuit. The high-voltage switches are connected with one or more second photovoltaic modules which are connected in parallel, and the detection control circuit is connected with the low-voltage switches and the high-voltage switches, controls the high-voltage switches to be turned off in sequence, controls the corresponding low-voltage switches to be switched to a second switch state, determines the faulted first photovoltaic module according to the insulation resistance of the photovoltaic system, and ends the operation. The method does not need to employ a mode of manually plugging and unplugging the string or changing the voltage of the string, can achieve the detection of all fault assemblies, improves the detection precision, and improves the detection range.

The embodiment of the invention relates to the technical field of data processing, and provides a cable insulation and loop detection method and a related device, and the method comprises the steps: inputting a reference test voltage to a to-be-detected object; acquiring a current signal flowing through the to-be-detected object to which the reference test voltage is applied; determining an initial insulation resistance value according to the reference test voltage and the current signal; obtaining correction environment parameters of the to-be-detected object; generating target correction information according to the correction environment parameters; and correcting the initial insulation resistance value by using the target correction information to obtain a target insulation resistance value, thereby improving the accuracy of performing cable insulation and loop detection on the to-be-detected object.

The invention discloses a processing process fault prediction method for essential oil production, and relates to the technical field of essential oil processing, and the method comprises the steps: constructing an environment equipment coupling model, and drawing an electrical equipment insulation resistance attenuation curve through a salt mist deposition experiment; environment disturbance variables are introduced into the generative adversarial network, and an anomaly detector capable of recognizing salt spray corrosion characteristics and humidity condensation characteristics is trained; capturing time-space correlation between temperature mutation and quality fluctuation through a self-attention mechanism; calculating a probability density function of the residual service life of the equipment in real time, and automatically correcting a temperature over-limit threshold value based on the residual service life distribution; calculating the contribution degree of each node to the fault through intervention simulation; and constructing a digital twinborn model containing thermodynamic and hydrodynamic characteristics. Through environment dynamic modeling, causal reasoning and digital twinning methods, the key problems of low fault prediction precision, poor traceability efficiency and lack of quantitative support in decision making in essential oil production are solved.

The invention discloses a transformer substation secondary equipment fault detection platform and an analysis method. The platform comprises a mobile bearing unit, an instrument integration unit, an integrated power supply and safety protection unit, an image acquisition unit and a data fusion analysis unit. The platform carries a relay protection tester, a mutual inductor comprehensive characteristic tester and an insulation resistance meter in an integrated manner, and is equipped with an image acquisition system, so that convenient movement and multi-source data acquisition of detection equipment are realized. And the data fusion analysis unit adopts a multi-modal fusion deep learning model to carry out collaborative analysis on the electrical detection data and the visual data, and outputs a diagnosis conclusion containing accurate fault positioning and basic causes through feature extraction and fusion. According to the method, the problems of low efficiency and inaccurate diagnosis caused by inconvenient equipment carrying and data isolated analysis in traditional debugging are effectively solved, and the intelligent level, the safety and the reliability of operation and maintenance of the secondary equipment of the transformer substation are remarkably improved.

The invention provides a GIS equipment withstand voltage test system and method, and relates to the technical field of GIS equipment withstand voltage test. Comprising the steps of obtaining parameter information and installation environment data of GIS equipment, constructing a three-dimensional digital twinborn model of the GIS equipment in combination with an electric field simulation engine, generating a withstand voltage test scheme and planning an optimal path. Acquiring partial discharge data and insulation resistance data under different voltage stresses by using an AI noise reduction algorithm according to the optimal path, carrying out multi-modal fusion processing on the partial discharge data and the insulation resistance data, extracting features by using a deep learning model, obtaining insulation defect and performance attenuation data, and carrying out multi-modal fusion processing on the insulation defect and performance attenuation data. And carrying out space mapping association with the three-dimensional digital twinborn model to generate a GIS equipment withstand voltage test evaluation report, thereby providing a powerful basis for equipment operation and maintenance. According to the invention, the three-dimensional digital twinborn model is constructed to generate the GIS equipment voltage withstanding test evaluation report, so that the accuracy of the GIS equipment voltage withstanding test is improved.

The invention discloses an insulation state monitoring system and method for a rotor winding of a pumped storage unit, and relates to the technical field of insulation state monitoring. Electrical performance parameters and environmental parameters of the rotor winding are analyzed, an insulation resistance model is constructed, and the insulation resistance of the rotor winding is output through an insulation resistance model expression; according to the mode, online monitoring of the insulation state can be achieved, meanwhile, the accuracy of insulation state monitoring is effectively improved through multi-parameter coupling analysis, then the monitored insulation state corresponds to fault characteristics of the pumped storage unit, and when the pumped storage unit breaks down, the fault of the pumped storage unit can be monitored. According to the method, fault causes can be accurately positioned, the monitored insulation resistance values are fitted to obtain an insulation state change curve, the insulation deterioration trend is warned in advance, and therefore the sudden fault risk is reduced.

The invention relates to a cable early-stage fault parameter extraction method and system fusing temperature rise process data, and relates to the technical field of cable fault monitoring, and the method comprises the steps: receiving multi-node temperature rise data uploaded by a temperature measurement optical fiber for a to-be-detected cable in a conduction state, comparing the multi-node temperature rise data with a cable rated condition, extracting deviation information with a standard temperature rise curve, and calculating the temperature rise process data of the to-be-detected cable; setting first and second fault characteristic indexes; drawing up a fault parameter extraction atlas in combination with the deviation information and the first and second fault characteristic indexes; and according to the attenuation coefficient, the early fault calorific value under different equivalent insulation resistances is taken as a core association feature, a fault influence range is evaluated, and a dynamic threshold adjustment rule is used for fault reminding. The cable fault detection method solves the problems that in traditional cable fault detection, early fault feature capture is not sensitive, missing detection is prone to occurring, and the fault judgment accuracy is insufficient due to the fact that the cable operation state and environmental factors are not fully combined.

The invention relates to the technical field of power grid planning, in particular to a power distribution network dynamic planning system based on digital twinning, which comprises an acquisition module, a simulation module, a first judgment module, a determination module, a second judgment module, an adjustment module, a correction module and an output module. According to the invention, the current and voltage of the equipment and the post-earthquake position offset, inclination angle and insulation resistance value are collected in real time, and the simulation analysis of the digital twin model is combined, so that fault equipment and abnormal equipment can be accurately identified; an acquisition period and a coincidence rate threshold value are dynamically adjusted, monitoring efficiency and accuracy are optimized, a power distribution planning report is generated at the same time, and a scientific basis is provided for optimized operation of the power distribution network; especially in emergency situations such as after an earthquake, quick response and power supply recovery can be realized, the influence of disasters on a power grid is reduced, and the problems of inaccurate monitoring and inflexible planning caused by complex influence of the earthquake and excessive dependence on static parameters are effectively solved.

The invention relates to the technical field of insulation degradation detection, in particular to an insulation characteristic degradation detection method for an underwater wet-plugging electric connector, which is characterized in that a multi-angle appearance image of the connector is acquired through a pressure-resistant underwater camera device, and the image quality and the recognition accuracy are improved by adopting a defogging and color correction technology. And further extracting defect characteristics such as cracks, corrosion and aging on the surface of the connector through an image by virtue of a graph neural network model, realizing automatic identification and positioning of defect types, and then executing a local electrical test on the identified defect region to obtain electrical parameters such as insulation resistance, capacitance value and medium absorption ratio. Image recognition information and electrical test data are constructed into a feature matrix, a fusion evaluation model composed of a logistic regression model and a weighted scoring mechanism is input, an insulation degradation degree value is output, and a detection result is generated, so that the accuracy of insulation detection of the underwater wet-plugging electric connector is improved, and the detection time is effectively shortened.

There is provided a circuit for monitoring an insulating property of a fuel cell stack, comprising: a low-frequency voltage source for negatively injecting a low-frequency signal only to a high-voltage bus of the fuel cell stack; a first resistor; and a second resistor; wherein the low-frequency voltage source, the first resistor and the second resistor are connected in series, and the low-frequency voltage source, the first resistor and the second resistor which are connected in series are connected with a high-voltage bus negative ground insulation resistor of the fuel cell stack in parallel; and the voltage on the first resistor can be measured so as to be used for determining the insulating property of the fuel cell stack. Therefore, the low-frequency voltage source only injects the low-frequency signal at the negative single side of the high-voltage bus, so that only the insulating property of the negative single side of the high-voltage bus is reduced, and the insulating property of the positive side of the high-voltage bus is not influenced.

The invention discloses an intelligent insulation parameter dynamic monitoring and regulation system based on a GD32 microcontroller, and belongs to the field of power electronic insulation monitoring. According to the system, a distributed monitoring network is constructed by taking GD32 as a core processor, a multi-channel time-sharing sampling and dynamic impedance measurement algorithm is integrated, GA / GB dual-channel independent sampling is realized by virtue of a state machine, and the sampling efficiency is improved by 80% compared with that of a traditional scheme. A programmable resistance network and a low-noise operational amplifier are adopted, 1 pF to 100 nF impedance matching and 5-200-time dynamic gain adjustment are achieved, an optical coupler switching dynamic impedance measurement method is originally created, four sets of voltage are adopted for time-sharing conduction of a solid-state relay, and 1.5% high precision is achieved through an improved voltage division model. LC-pi type filtering is adopted at a signal input end, and the high-frequency noise suppression ratio is larger than 20 dB; and a CAN module is newly added, so that a CAN2.0B extension frame and an adjustable Baud rate of 10k-1Mbps are supported. Actual measurement shows that the system can measure 10-65M omega insulation resistance in new energy and rail transit scenes, the dynamic response is smaller than or equal to 200ms, the system is suitable for the fields of medical equipment, industrial sensors and the like, and the overall performance is improved by three times compared with that of a traditional scheme.

The invention provides an insulation resistance detection method and system of an energy storage system and a storage medium, and relates to the technical field of safety monitoring of the energy storage system. The method comprises the following steps: monitoring the total voltage of the energy storage system; calculating the change rate of the total voltage; comparing the change rate with a preset rate threshold; when the change rate is smaller than a preset rate threshold value, calculating a first insulation resistance value by adopting an unbalanced bridge method based on the current total voltage, and outputting the first insulation resistance value as an effective insulation resistance value; and when the change rate is greater than or equal to a preset rate threshold value, calculating a second insulation resistance value by adopting an unbalanced bridge method based on the current total voltage, comparing the second insulation resistance value with a stored reference insulation resistance value, and selecting an effective insulation resistance value output this time according to a comparison result. According to the method, the defect that the traditional BMS insulation detection function is insufficient in adaptability in the application of the super capacitor is overcome, and the anti-interference capability and the operation safety of the system are enhanced.

The invention relates to an insulation fault identification method and system, electronic equipment, a medium and a product, and belongs to the technical field of electronics. The method comprises the steps that when the insulation resistance value of a vehicle is smaller than a preset first resistance value, whether the vehicle is subjected to direct current charging operation within a preset first time period or not is judged; if the direct current charging operation is not carried out on the vehicle, whether a first difference value between the maximum value and the minimum value of the insulation resistance value in a preset second time period is larger than a preset second resistance value or not is judged; if the first difference value is not larger than the preset second resistance value, whether the air conditioner of the vehicle is used or not within a preset third time period is judged; if the air conditioner is used, the insulation fault type of the vehicle is determined according to the temperature parameters related to the air conditioner. By analyzing the big data related to the vehicle insulation fault, the insulation fault type can be quickly determined, so that the insulation fault positioning efficiency is improved, the troubleshooting period is shortened, the economic loss caused by continuous existence of the fault is reduced, and the maintenance cost is reduced.

The invention provides a battery insulation state detection method, device and equipment, and relates to the technical field of battery safety monitoring. The method comprises the following steps: acquiring multi-physical field measurement data of a to-be-detected battery; the multi-physical field measurement data comprises insulation resistance data, leakage current ripple data, space temperature data and space humidity data; based on the multi-physical field measurement data, obtaining an impedance characteristic, a ripple energy characteristic, a temperature characteristic and a humidity characteristic; obtaining time-varying features corresponding to the impedance feature, the ripple energy feature, the temperature feature and the humidity feature; the time-varying feature comprises a variation trend and / or degree in a preset time period; and evaluating the insulation state of the battery based on the impedance characteristic, the ripple energy characteristic, the temperature characteristic, the humidity characteristic and each time-varying characteristic to obtain an insulation state evaluation result of the to-be-detected battery. According to the invention, accurate detection of the insulation state of the battery is realized, and the safety of the energy storage system is further improved.

The invention relates to the technical field of motor test equipment, in particular to a multifunctional motor test operation system and method, and the method comprises the steps: a parameter detection module synchronously collects voltage, current, frequency, temperature, vibration, insulation resistance and DC resistance parameters, and converts the parameters into electric signals; the data processing module carries out amplification, filtering and analog-to-digital conversion on the electric signal to obtain a measured value; the storage module stores the measured value; and the report generation module automatically generates a test run report containing parameter analysis and qualification conclusions through a preset template based on the stored value. The parameter detection module synchronously collects various parameters and converts the parameters into electric signals, the data processing module processes the signals to obtain accurate measured values, the storage module stores data, and the report generation module automatically generates a test run report containing analysis and conclusion based on the stored values. The problems that the function is single, data integration is difficult and report generation is tedious are solved, the testing efficiency and accuracy are remarkably improved, and manual errors are avoided.

The invention discloses a high-voltage motor pagoda structure direct insulation automatic detection device, which comprises a background system, a pagoda structure detection device and a display device, and is characterized in that the background system is electrically connected with the pagoda structure detection device and the display device; the appearance of the pagoda structure detection device is a pagoda structure, the upper end of the pagoda structure is a high-voltage current-limiting resistor fixedly sealed by a silicone rubber umbrella skirt structure, and the lower end of the pagoda structure is a metal shell. A motor running state input module, a relay output module, a microprocessor, a DC2500 / 5000V boosting module, a high-voltage isolation relay, a current sampling module and an analog-to-digital conversion module are arranged in the metal shell; the motor operation state input module, the relay output module, the microprocessor, the DC2500 / 5000V boost module, the current sampling module, the analog-to-digital conversion module and the high-voltage isolation relay are connected in sequence, and the device can automatically complete insulation resistance detection before the high-voltage motor is put into operation, does not need manual terminal disassembly and assembly, shortens the detection time, and improves the detection accuracy.

The invention relates to the technical field of new energy automobile high-voltage safety, and particularly provides a new energy automobile high-voltage safety protection method and system based on multistage linkage outage, and the method comprises the steps: a sensor layer continuously collects high-voltage system parameters, and forms an original data stream; the high-voltage system parameters comprise insulation resistance, collision acceleration, battery pack pressure, temperature and the like; original data flows are processed by a multi-level diagnosis center, and fault level judgment is obtained by combining fault codes and timestamps recorded by a fault latch memory through multi-source data fusion and threshold comparison; and an execution instruction is formed through fault level judgment, and an execution mechanism is driven to perform corresponding power-off operation. The system comprises a data flow acquisition module, a diagnosis central processing module and a power-off operation execution module. According to the invention, when abnormal working conditions such as collision, insulation fault, short circuit and the like of the vehicle occur, a rapid, accurate and reliable high-voltage safety protection device is realized through multi-stage collaborative diagnosis and staged power-off.

The invention relates to a base metal high-voltage multilayer ceramic dielectric capacitor and a preparation method, the base metal high-voltage multilayer ceramic dielectric capacitor is formed by stacking and firing dielectric layers, and each dielectric layer comprises a dielectric layer and an electrode printed on the dielectric layer. The dielectric layer comprises the following raw materials: a BMYT main matrix, an NN material, magnesium oxide, manganous-manganic oxide, zirconium dioxide, calcium carbonate, strontium carbonate and rare earth oxide; through the raw material composition and the preparation method of the ceramic dielectric capacitor, the prepared ceramic dielectric capacitor has excellent performances of high dielectric constant, high voltage resistance, stable dielectric-temperature characteristic curve, low loss, high insulation resistance, long-term high-voltage reliability and the like under the condition of high dielectric thickness (30 microns before firing).