333results about "Frequency analysis" patented technology

The invention discloses an automatic anchor point searching and processing method for grid-connected test data of a photovoltaic inverter, and belongs to the technical field of automatic test of a power system. According to the method, a three-phase voltage and current signal output by a power grid simulator and an inverter power instruction signal are aligned through a high-precision time synchronization device; wavelet transform multi-scale noise reduction and moving average filtering combined preprocessing is adopted to improve the signal-to-noise ratio; identifying a voltage zero crossing point candidate set, a drop starting point candidate set and a recovery termination point candidate set based on a self-adaptive dynamic threshold value; transient energy characteristic verification is introduced for a voltage drop starting point; effective anchor points are confirmed through time window association of power instruction step changes. According to the method, the problems of low efficiency of manual key event point identification, misjudgment caused by noise interference, grid event and inverter response time sequence correlation missing and the like are solved, and the automation degree of test data analysis, anchor point positioning precision and control response time sequence analysis reliability are remarkably improved.

The invention relates to the technical field of prediction algorithms, and discloses a high-precision active power filtering and prediction algorithm for a three-phase ammeter, which comprises the following steps: acquiring original signals of three-phase voltage and current for baseline correction, performing time-frequency analysis on non-stationary harmonic waves and noise of the original signals, and dynamically adjusting filtering parameters; voltage and current phase alignment is carried out through FIR phase shift and zero crossing point detection, a phase-locked loop is constructed by using GRU to track the frequency of a power grid, the sampling frequency is dynamically adjusted, and frequency mutation is detected; iapFFT transformation is optimized to suppress spectrum leakage, a phase error is corrected through a deep learning network, and weak harmonic detection is enhanced by using an attention mechanism; classifying harmonic waves, and adaptively calculating total active power; dimensionality reduction is carried out on historical power and environmental parameters through an auto-encoder, and future active power is predicted; low-power-consumption hardware is adapted, and training efficiency and data security are optimized; three-phase signals are processed in parallel, and FPGA storage and FFT / FIR cores are optimized for filtering processing; and dynamically adjusting parameters of the phase-locked loop.

The invention belongs to the technical field of power equipment state monitoring, and discloses a cable branch box operation state intelligent evaluation system based on multi-sensor fusion, which comprises a state acquisition module used for acquiring a partial discharge signal, a voltage fluctuation signal, a terminal temperature signal and a terminal contact resistance signal of a cable branch box in an operation process, constructing a multi-source operation state parameter set of the cable branch box through time synchronization and physical quantity normalization processing; the mutual coupling analysis module is used for performing transient correlation deduction on the partial discharge signal and the corresponding voltage fluctuation signal based on the multi-source operation state parameter set to obtain a partial discharge-voltage coupling amount; when the partial discharge-voltage coupling amount exceeds a preset partial discharge-voltage coupling amount threshold value, determining that partial discharge abnormity caused by insulation degradation exists in the cable branch box; comprehensive and accurate evaluation of the operation state of the cable branch box is realized, and reliable support is provided for safe operation and maintenance of equipment.

The invention relates to the technical field of transformer fault detection, in particular to a converter transformer fault diagnosis method and device based on robot return data. The method comprises the following steps: accessing an original partial discharge signal of the converter transformer acquired by an on-site inspection robot into a diagnosis platform in the form of a dynamic return data packet by adopting a target communication mode to obtain a filtered pure partial discharge signal in a time domain; obtaining a dominant mode representing the characteristics of the pure partial discharge signal; inputting the dominant mode into the trained classifier to obtain a fault defect type of the converter transformer corresponding to the pure partial discharge signal; and visualizing the fault defect position and type of the converter transformer and the original partial discharge signal on the three-dimensional model of the converter transformer. According to the embodiment of the invention, the identification precision of the defect type of the converter transformer is improved, and the fault information of the converter transformer is visually displayed.

The invention relates to the technical field of power distribution network fault detection, and discloses a power distribution network high-resistance grounding fault intelligent detection method, system and device and a medium, and the method comprises the steps: collecting a power distribution network line transient signal which comprises a transient zero-sequence voltage signal and a transient zero-sequence current signal; preprocessing the transient signal and extracting a multi-dimensional feature set for representing high-resistance grounding fault characteristics, wherein the multi-dimensional feature set comprises a transient energy feature, a wavelet entropy feature and a harmonic component feature; and inputting the extracted multi-dimensional feature set into a pre-trained machine learning model, and simultaneously outputting a judgment result of the high-resistance grounding fault and an estimated value of the grounding resistance through the machine learning model. According to the method, the transient energy, the multi-scale wavelet entropy, the odd harmonic amplitude and the phase, which are derived from different analysis domains and have complementary physical meanings, are deeply fused, so that the problem that a single feature is weak in characterization capability and easy to fail under the conditions of high noise and high resistance is effectively solved.

The invention relates to the technical field of power system court management, and particularly discloses a court identification and user binding method based on a special transformer acquisition terminal, which comprises the following steps: separating harmonic interference generated by start and stop of an electric welding machine through a kurtosis index and time-frequency energy entropy fusion detection method, and extracting a fundamental voltage and a pure power signal; constructing a dynamic time bending model containing phase consistency and gradient feature constraint based on the fundamental wave voltage, and calculating voltage track similarity to judge electrical coupling; for the users with electrical coupling, dynamic weight power cross-correlation analysis is fused to generate a comprehensive decision value, and a space-time diagram neural network is utilized to update a transformer area topology structure online in combination with a historical topology change event, so that the dynamic determination of the transformer area to which the users belong is realized; through multi-dimensional feature fusion and anti-interference algorithm design, the problems of phase deviation and waveform distortion caused by electric welding machine harmonic waves are reduced, and the transformer area identification accuracy and real-time performance are improved.

The application discloses a kind of non-contact track frequency shift signal online monitoring method and system, applied to intelligent monitoring technical field, method includes: receiving first measured voltage and second measured voltage;First measured voltage and second measured voltage are input first conditioning circuit by first transmission line, receive the first output voltage output by first conditioning circuit, and the parallel transmission line formed after first measured voltage and second measured voltage are connected in parallel by second transmission line and third transmission line are input second conditioning circuit, receive the second output voltage output by second conditioning circuit;According to first output voltage and second output voltage, calculate first measured voltage.The application is realized by the way of double-path simultaneous monitoring, reduces the influence of the related capacitance value change caused by environmental conditions on monitoring result, to effectively improve monitoring precision, and then provides solid foundation for non-contact frequency shift signal back-end processing.

The invention relates to the technical field of air door motor control, and discloses an air door motor control method and system based on current detection, and the method comprises the steps: carrying out the single-phase current signal collection of an air door motor system, and obtaining a current change signal in the opening and closing process of an air door; carrying out FFT (Fast Fourier Transform) and wavelet decomposition processing on the current change signal to obtain a current characteristic spectrum component and a time domain characteristic; processing the current characteristic frequency spectrum component and the time domain characteristic to obtain an air door load current characteristic; iterative learning control is executed, and air door rotating speed control parameters are generated; the PWM duty ratio is calculated, and air door motor driving pulses are generated; according to the air door motor control method, a complete air door motor control protection mechanism is established, abnormal conditions such as stalling can be detected and coped with in time, the safety of an air door motor system is improved, and the service life of the air door motor system is prolonged.

The invention discloses a GIS ultrahigh frequency sensor ultrasonic cooperative detection system based on piezoelectric energization, and relates to the field of electric power detection, and the system comprises an excitation module which is used for transmitting a piezoelectric excitation signal with a specific frequency to a preset detection region in GIS equipment, so as to trigger the potential partial discharge acoustoelectric signal radiation of the region; the sensing module is used for receiving ultrahigh-frequency electromagnetic signals and ultrasonic vibration signals radiated by partial discharge in the GIS equipment; the excitation frequency, the filtering bandwidth and the sampling rate are dynamically optimized according to the detection result, the detection accuracy and efficiency are continuously improved, and reliable and effective guarantee is provided for safe operation and defect early warning of GIS equipment.

The invention belongs to the technical field of gap measurement, and particularly relates to a high-temperature-resistant transparent shell type eddy current tip gap measuring device and method, and the device comprises a sensor probe module, a signal conditioning module, a data collection module and a data processing module. The sensor probe module is mounted on the outer wall of the casing; the sensor probe module comprises a permanent magnet excitation source, a soft magnet magnetic core and a receiving coil; the signal conditioning module is electrically connected with the receiving coil and is used for amplifying, filtering and integrating the weak induction signal; the data acquisition module is electrically connected with the signal conditioning module and converts an analog signal into a digital signal; the data processing module is used for processing the acquired digital signals and extracting blade tip clearance information.

The invention relates to the technical field of radio frequency measurement, and discloses a method for measuring the high-frequency characteristic of a radio frequency coaxial probe. The method comprises the following steps: acquiring high-frequency response data of a radio frequency coaxial probe, segmenting a full frequency band based on a predefined frequency band division strategy, and identifying a key frequency band region; according to the response amplitude and phase distribution of the key frequency band region, screening a reference frequency band and extracting an impedance reference value, optimizing impedance matching parameters of a non-reference frequency band based on the reference value, and generating a frequency band impedance optimization parameter set; recombining a full-band impedance distribution sequence according to the parameter set to generate an initial impedance matching scheme; and finally, monitoring the high-frequency transmission deviation under the initial scheme in real time, counting the impedance fluctuation quantity and the phase offset, and generating an impedance correction instruction. The method effectively improves the stability and reliability of the measurement of the high-frequency characteristic of the radio frequency coaxial probe by accurately identifying the key frequency band in a segmented manner, guiding the impedance parameter optimization by the reference value and combining a dynamic correction mechanism.

Provided are a method and apparatus for detecting a failure of a solar module. The method includes obtaining real-time power generation data of each of a plurality of solar modules included in at least one solar array, setting a reference value using at least one of past power generation data of the plurality of solar modules and specifications of the plurality of solar modules, determining each of the plurality of solar modules to be either a normal solar module or an abnormal solar module by comparing the reference value with a power generation amount of each of the plurality of solar modules, which is calculated using the real-time power generation data, and providing an interface displaying a solar module determined to be the abnormal solar module.

The invention discloses a frequency sweep measurement method and system. The method comprises the following steps: acquiring a fundamental frequency reference phase of each measured equipment access point at a measurement moment; executing rough scanning of the first-stage injection; analyzing the coarse scanning response data to identify a target frequency band which needs to be subjected to second preset resolution measurement; executing fine scanning of second-stage injection for the target frequency band; and analyzing the fine scanning response data, and obtaining a stability contribution evaluation result of each tested device to the power grid system based on an analysis result of the fine scanning response data and an analysis result of the coarse scanning response data. According to the scheme of the invention, the method can achieve the quick recognition of the potential key frequency region in a broadband range through the hierarchical rough scanning and fine scanning strategies, and avoids the time-consuming high-resolution measurement in a whole frequency band. And then, high-resolution fine scanning is performed on the identified target frequency bands in a targeted manner, so that accurate and detailed response data can be obtained in the key region.

The invention discloses a transformer substation AC power supply residual current detection method and device, and the method comprises the steps: carrying out the vector synthesis of three-phase current data and zero line current data, forming a current difference sequence, exporting a residual current reference curve, and carrying out the fluctuation analysis of the residual current reference curve, and judging the leakage characteristics. After effective leakage features are formed through harmonic elimination, dominant frequency components are locked through frequency spectrum decomposition; calibrating a leakage type identifier according to the dominant frequency component and forming segmented leakage distribution; a deviation degree is formed by means of segmented leakage distribution and residual current reference curve deviation analysis, a correction deviation value is formed through load fluctuation compensation, and a standard exceeding coefficient is formed according to threshold value comparison to detect abnormal nodes to form hidden danger data; establishing a judgment rule based on the hidden danger data and the leakage type identifier to form a detection evaluation index; and executing path tracking on the detection evaluation indexes to form leakage position information, forming a disposal priority through intensity analysis to generate a residual current detection report, and realizing leakage current classification identification and self-adaptive evaluation.

The invention discloses a fault monitoring and positioning method for a high-voltage drop-out fuse, and relates to the technical field of power equipment fault monitoring, and the method comprises the steps: obtaining original monitoring sequences corresponding to current and voltage sensors disposed at upper and lower ports of a target fuse; activating a working mode recognizer to execute working mode recognition of the target fuse, establishing a global mode label, executing adaptive matching of a mode fingerprint database, and establishing a standard comparison fingerprint with a trust identifier; establishing residual spectrum characteristics; and establishing a fault discrimination vector, carrying out space fault positioning by using the fault discrimination vector, and generating a fault positioning result. According to the invention, the technical problems of insufficient fault monitoring and positioning accuracy, lack of visual presentation capability and low monitoring and positioning efficiency of the high-voltage drop-out fuse in the prior art are solved, and accurate positioning and visual presentation of the fault of the high-voltage drop-out fuse are realized. And the accuracy and efficiency of fault monitoring and positioning are improved.

The invention discloses a power distribution network reliability intelligent analysis method and analysis system, particularly relates to the technical field of power system fault detection, and is used for solving the problems of misjudgment and missed judgment caused by fault feature weakening and harmonic interference in a bidirectional power flow scene in an existing method. The method comprises the following steps: firstly, synchronously collecting fundamental wave and harmonic components of nodes of a power distribution network, extracting a current amplitude change rate and a phase offset by adopting time-frequency domain conjoint analysis, and generating dynamic distribution characteristics by combining harmonic energy clustering; identifying high-frequency interference components in a bidirectional power flow mode by quantizing a phase deviation direction and harmonic energy aggregation characteristics; based on a harmonic frequency band coupling effect and a current dynamic association relationship, an adaptive detection threshold function is constructed, and accurate separation of fault features is realized; and finally, combining a real-time fault judgment result with historical repair data to generate a reliability evaluation parameter. And the sensitivity of fault detection and the rationality of reliability evaluation in a complex operation environment are remarkably improved.

The invention relates to the technical field of power system monitoring, discloses an anti-harmonic PT current monitoring system and method, and aims to solve the problem of secondary side current signal distortion of a voltage transformer caused by power grid harmonic pollution in the prior art. The method comprises the steps of electrifying and initializing a system, starting a high-speed analog-to-digital converter to acquire a voltage signal, executing fast Fourier transform to identify dominant harmonic waves, calculating and configuring a capacitance value of a tunable LC trap unit to suppress specific harmonic waves, and finally outputting a high-fidelity analog voltage signal in direct proportion to fundamental current. The system comprises a current-voltage conversion module, a tunable LC notch filter array, a high-speed analog-to-digital converter, a digital signal processing unit and a microcontroller. According to the technical scheme, dynamic self-adaptive suppression and precise selective harmonic wave blocking of power grid harmonic waves can be realized, low delay and high fidelity characteristics are guaranteed, and the engineering practicability and reliability of the system are improved.

The invention belongs to the technical field of electronic information, and relates to an online low-voltage load monitoring and abnormal tripping positioning method and a related device. According to the method, electrical parameters of all monitoring points are collected in real time, key parameters are calculated after analog-to-digital conversion and filtering denoising, and the key parameters are compared with a set threshold value to judge whether the monitoring points are in an abnormal state or not; once an abnormal state is found, an early warning is generated and uploaded to a remote platform; and continuously monitoring the state of the main switch or the total current at the same time, and when tripping occurs, backtracking an abnormal record within a preset time period before tripping, and positioning the last or the most serious abnormal monitoring point as an abnormal source. The system comprises a data acquisition module, an analog-to-digital conversion module, a preprocessing module, a calculation module, a judgment module, an early warning module, a trip monitoring module and a positioning module. According to the invention, early warning before a fault and rapid positioning after tripping are realized, and the intelligent level, the operation and maintenance efficiency and the power supply reliability of the power distribution network are improved.

To provide an electric signal detector, a diagnosis device, a partial discharge detection system, a partial discharge detection method, and a program, which can detect occurrence of partial discharges with high accuracy.SOLUTION: An electric signal detector comprises: a first reception unit 12 for receiving an electric signal generated in a cubicle 4; a wide-band filter F0 for extracting an electric signal of a first frequency band from the received electric signal; a plurality of narrow-band filers F1-F3 for extracting an electric signal of a frequency band which is a portion of the first frequency band; a selection switch 14 for selecting the wide-band filter F0 and one of the narrow-band filters F1-F3; a level determination unit 20 for determining whether or not the level of the electric signal extracted by the wide-band filter F0 is greater than or equal to a threshold level; and a control unit 22 for sequentially selecting the narrow-band filters F1-F3 by switching the selection switch 14 when the electric signal level is determined to be higher than or equal to the threshold level, and transmitting the electric signals extracted by the narrow-band filters F1-F3 to the diagnosis device 3 that diagnoses occurrence of a partial discharge.SELECTED DRAWING: Figure 2

The invention discloses a wireless high-voltage current measurement method with a filtering anti-interference function, and belongs to the technical field of robot coordination control. The method comprises the following steps: obtaining an original discrete voltage signal sequence; calculating a discrete voltage signal sequence transient strength index; performing variational mode decomposition on the original discrete voltage signal sequence by using a mode number and a penalty parameter to obtain a group of intrinsic mode functions; respectively synthesizing the classified modes into corresponding interference reference signals; respectively inputting the orthogonal interference reference signals into a filter channel to estimate various interference components and carrying out dynamic adjustment; and a pure high-voltage wire current time domain signal is restored. According to the method, signal characteristics are sensed in real time by adopting the VMD, subsequent key parameters are dynamically adjusted, and the denoising performance is improved; a multi-feature modal intelligent classification method is adopted, mathematical modals with unknown physical meanings are mapped to four physical sets of useful signals, power frequency, high frequency and transient states, and decoupling of signals and noise in a time-frequency domain is achieved.

The present disclosure provides a battery. The battery includes a case formed of a conductive material, a sensing member attached to one surface of the case and including a conductor formed of a conductive material and a dielectric having at least a part thereof disposed between the case and the conductor, and a monitoring circuit electrically connected to the conductor and the case, wherein the monitoring circuit may monitor whether the battery is deformed based on an amount of change in a capacitance formed between the conductor and the one surface of the case.

The invention discloses a non-contact track frequency shift signal on-line monitoring method and system, and is applied to the technical field of intelligent monitoring, and the method comprises the steps: receiving a first measured voltage and a second measured voltage; a first measured voltage and a second measured voltage are input into a first conditioning circuit through a first transmission line to receive a first output voltage output by the first conditioning circuit; the first measured voltage and the second measured voltage are connected in parallel through a second transmission line and a third transmission line to form a parallel transmission line, and the parallel transmission line is input into the second conditioning circuit to receive a second output voltage output by the second conditioning circuit; and calculating a first measured voltage according to the first output voltage and the second output voltage. According to the non-contact frequency shift signal monitoring system, the influence of the change of the capacitance value of the related capacitor caused by the environmental condition on the monitoring result is reduced in a double-path simultaneous monitoring mode, so that the monitoring precision is effectively improved, and a solid basis is provided for the back-end processing of the non-contact frequency shift signal.

A battery state diagnosis apparatus includes a processor configured to extract battery impedance by obtaining voltage and current signals outputted from a battery management system of an electric vehicle, removing noise by performing first signal processing on the voltage and current signals outputted from the battery management system, and extracting a frequency characteristic by performing second signal processing on the voltage and current signals from which the noise has been removed, and a storage configured to store data and algorithms driven by the processor.

The application discloses a handheld spectrum analyzer real-time spectrum signal processing system and processing method, the system comprises a pre-processing unit, an ADC unit, an FPGA and an ARM which are connected in sequence, the FPGA comprises a digital down conversion unit, a multi-rate decimation filter unit, a real-time FFT operation unit and a real-time detection unit which are connected in sequence, and a grid mapping unit, a vector connection unit and a fluorescence statistical unit which are connected with the real-time FFT operation unit in sequence, the ARM comprises a real-time spectrum diagram and waterfall diagram unit which is connected with the real-time detection unit, and a fluorescence display unit which is connected with the fluorescence statistical unit. The application adopts parallel frame real-time detection and vector connection-based digital fluorescence statistical method to compress multiple spectrum data, reduces the requirement of a large number of spectrum data on screen refreshing, adopts vector connection to make fluorescence statistics, so that the measured signal is easier to distinguish, and the application meets the test requirement of a handheld instrument.

The invention discloses a detection control device, a detection control method and a petroleum logging neutron tube system. The detection control device comprises a radio frequency power supply, an impedance matching module, a filtering module, a current detection module and a control module, the radio frequency power supply is used for providing radio frequency energy for the radio frequency electrode, so that working gas in an ion source in the neutron generator generates plasma; the current detection module is used for providing direct current voltage for the radio frequency electrode and detecting information of direct current flowing through the radio frequency electrode; the filtering module is used for preventing radio frequency energy from entering the current detection module and preventing direct current from entering the radio frequency power supply; the control module is used for controlling the output power of the radio frequency power supply according to the direct current information. According to the detection control device, the detection control method and the petroleum logging neutron tube system, the density of plasma in the neutron generator can be obtained in real time, a stable and reliable feedback signal is provided for output power control of a radio frequency power supply, and the stability of neutron output is ensured.

The present invention relates to a motor control center having a compact structure, which is capable of performing predictive maintenance for a motor connected to the motor control center by having, integrally formed with the motor control center in order to detect the operation state of the motor in real time: a current measurement module which measures a current flowing in a power supply line for supplying power from the motor control center to the motor; a detection server which detects the state of the motor on the basis of the measurement information of the current measurement module; and an image output module which outputs and provides the detection information of the detection server in the form of an image.

This invention discloses a system for measuring the local spectrum of 4.6 GHz low-clutter waves in plasma, used to measure the local low-clutter power and spectral broadening information in a scraped layer. A 30 GHz microwave source generates a backscattered signal at a specific location in the scraped layer. This backscattered signal is transmitted into the tokamak plasma via a horn antenna in ordinary mode. The new microwave signal, with a frequency of 34.6 GHz, is generated by backscattering at a second horn antenna. This 34.6 GHz microwave signal is then frequency-differentiated by a mixer to 3.5 GHz, and further frequency-differiated by a second 4.6 GHz local oscillator signal to 1.1 GHz. The signal is finally fed into a spectrum analyzer. Unlike conventional copper loop antenna measurements, this system can reflect the local low-clutter power and spectral information, thus enabling more accurate analysis of the parasitic effects of low-clutter waves in the scraped layer.

A system and a method of calculating the current consumption of components in a vehicle are disclosed. The system may include a controller and a memory stored thereon instructions for executing the method. The method comprising: receiving from at least one magnetic flux sensor located at a known location in the vehicle, a magnetic flux pattern at various frequencies, indicative of the magnetic field at the location; identifying at least one first magnetic flux maximum at a first frequency corresponding to a first component of the vehicle; and calculating a first current consumption of the first component based on the at least one first magnetic flux maximum.

A method and system for testing the conversion losses of terahertz mixers capable of eliminating the influence of radio frequency sources includes grouping a mixer to be tested and at least two reference mixers in pairs; in each group, inputting a signal of a preset frequency and a preset power at an intermediate frequency port of a first mixer, and after up-conversion, outputting same to a second mixer to be down-converted, so as to obtain an output power with the frequency same as the preset frequency, and obtain the relationship between a first output power and a first preset power and the losses of two mixers; according to the relationship between the loss of the mixer in each group and the power, obtaining the loss of the mixer to be tested.

A method of measuring a delay time of a propagation of a signal in a line in a circuit structure, the method comprises irradiating the line by pulses of a charged particle beam, wherein a pulse repetition frequency of the pulses of the charged particle beam is varied. The method further comprises measuring, for each of the pulse repetition frequencies, a secondary charged particle emission responsive to the irradiating the line by the pulses of the charged particle beam at the respective pulse repetition frequency, and deriving the delay time of the line based on the secondary charged particle emission responsive to the varying of the pulse repetition frequency.