923results about "Electric winding testing" patented technology

PCT No. PCT / FI97 / 00359 Sec. 371 Date Dec. 4, 1999 Sec. 102(e) Date Dec. 4, 1999 PCT Filed Jun. 9, 1997 PCT Pub. No. WO97 / 48026 PCT Pub. Date Dec. 18, 1997A method and a valve apparatus for surveying the condition of a control valve. The position of the valve (101) is adjusted by means of an actuator (103) controlled by an electropneumatic positioner (104) and operated by means of pressure medium. The operation of the valve is monitored by sensors (109, 110, 107) that read the readings from the control signal, the input pressure of the positioner, the difference between the input and output pressure of the actuator, and the position of the valve. A fault causing a deviating reading will be located by using the readings given by the sensors and deduction rules stored in the microprocessor of the actuator. In an initial situation, when the valve is in balance state, the readings given by the sensors are stored at least from the control signal, valve position and the difference between the input and output pressure of the actuator. When the operation is continued, the readings given by the sensors are compared with the readings of the initial situation. If the deviations exceed certain limit values and remain there continuously for a certain period of time, a fault message will be given that indicates the location of the fault.

Systems, methods and devices which utilize Spread Spectrum Time Domain Reflectometry (SSTDR) techniques to measure degradation of electronic components are provided. Such measurements may be implemented while the components “live” or otherwise functioning within an overall system. In one embodiment, monitoring a power converter in a high power system is accomplished. In this embodiment, degradation of components within the power converter (e.g. metal-oxide-semiconductor field-effect transistors (MOSFETs), capacitors, insulated-gate bipolar transistors (IGBTs), and the like) may be monitored by processing data from reflections of an SSTDR signal to determine changes in impedance, capacitance, or any other changes that may be characteristic of components degrading. For example, an aging MOSFET may experience an increase of drain to source resistance which adds additional resistance to a current path within a power converter. Such a change is able to be analyzed monitored upon processing the reflected test signals.

The apparatus for partial discharge detection of turn-to-turn insulation in motor has a surge generator for generating a surge voltage to the windings of the motor by applying a pulse voltage, and a partial discharge current detector for detecting partial discharge currents between the winding turns of the motor. The surge generator generates in and between the windings of the motor the surge voltage that has the rise time and fall time corresponding to the rise time of the surge voltage observed at the motor terminal when the motor is driven by an inverter, and that is repeated at a frequency of 50 Hz to 20 kHz.

The invention provides a sensing device, a power reception device,a power transmission device, a non-contact power transmission system, and a sensing method, wherein the sensing device includes a circuit including at least a coil electromagnetically coupled to an outside; a temperature detection unit for detecting a temperature of the coil; a sensing unit for measuring a Q value of the circuit; and a correction unit for correcting the Q value measured by the sensing unit based on temperature information detected by the temperature detection unit.

The invention discloses a transformer fault classification and identification method based on a vibration analysis method. The method comprises the following steps: S1) selecting a transformer test object, and collecting transformer vibration signals under different states as sample data; S2) calculating the sample data by utilizing a Hilbert-Huang transform EEMD (ensemble empirical mode decomposition) method to obtain an intrinsic mode function; S3) extracting characteristic vector V in each intrinsic mode function component; S4) carrying out dimensionality reduction on the characteristic vector through a principal component analysis method, coordinates being projected to a two-dimensional image; S5) carrying out classification on the sample data through a K neighbor method; S6) calculating the distance between a test sample and an original sample through a distance formula; S7) carrying out mode recognition; and S8) outputting corresponding transformer fault type in mode recognition. Operation state of a transformer can be judged visually and effectively.

The invention discloses a transformer fault analysis system based on acoustic shock detection. The transformer fault analysis system comprises a data acquisition system and a data analysis system which are mutually connected, and is characterized in that the data acquisition system comprises an acoustic data acquisition module and a transformer parameter acquisition module, the acoustic data acquisition module comprises a sound intensity sensor, a vibration sensor and a sound sensor, the data analysis system comprises a clock system, a signal feature extraction and classification module and asignal recognition and fault diagnosis module, and the signal feature extraction and classification module and the signal recognition and fault diagnosis module are connected with the clock system; and the signal feature extraction and classification module comprises a feature extraction module and a feature database, the feature extraction module is connected with the data acquisition system, andthe signal recognition and fault diagnosis module operates on a microcomputer system. The transformer fault analysis system represents an automatic recognition and identification technology for the operating state of a transformer through acquiring acoustic signals of the transformer and performing state recognition and marking on the acoustic signals, and finally achieves fault analysis and diagnosis for the transformer.

The invention discloses a system and method for judging interior looseness of a power transformer. The system for judging and initially positioning interior looseness of the power transformer comprises a signal conditioning circuit, a data acquisition instrument, a data analysis module and three vibration sensors, wherein the signal conditioning circuit, the data acquisition instrument and the data analysis module are sequentially connected. The three vibration sensors are connected with the data acquisition instrument through the signal conditioning circuit and measure vibration signals of three phases of the power transformer correspondingly, the vibration signals are amplified, filtered and denoised by the signal conditioning circuit and then transmitted to the data acquisition instrument, the data acquisition instrument transmits the acquired vibration signals to the data analysis module, and the data analysis module stores and processes the vibration signals and carries out fault judgment. The looseness fault of the transformer is judged through 100 Hz signals in the vibration signals according to the characteristic of change of the vibration signals along with the looseness degree.

The current invention relates to a monitoring and analysis device and a method for monitoring and analysis that utilizes the unintended electromagnetic emissions of electrically powered systems. The present invention monitors electrical devices by taking detailed measurements of the electromagnetic fields emitted by any component or system utilizing electricity. The measurements will be analyzed to both record a baseline score for future measurements and to be used in detailed analysis to determine the status of the analyzed system or component.

A method for monitoring the state of health (SOH) of a solenoid powered by a battery includes measuring a voltage and a current supplied to the solenoid by the battery, using a processor to determine each of an equivalent resistance and inductance of the solenoid using the voltage and the current, comparing the equivalent resistance and the equivalent inductance to a corresponding calibrated threshold, and recording deviations from the corresponding calibrated thresholds as a pair of SOH values. A trend of the SOH values is continuously monitored, and an appropriate control action is taken when either SOH value drops below a calibrated lower limit. A solenoid monitoring system includes a solenoid, voltage and current sensors, and a controller having an algorithm for continuously monitoring a state of health (SOH) of the solenoid as set forth above.

The invention relates to a technique for discerning a status of an armature of a high-speed solenoid at any time during its operational cycle. In high speed solenoids, motion of an armature does not occur until after a finite and indeterminate lapse of time after application of a driving voltage. In the present invention, a pulsed driving voltage is used to drive the solenoid. A resultant current in a coil of the solenoid exhibits discontinuities in its rate of change when the armature moves. Occurrences of the discontinuities are used to produce control signals and coordinate operation of the solenoids and other controllable events. Occurrence of these discontinuities exactly correlates with armature motion. Consequently, time lapse between application of voltage and motion of the armature becomes inconsequential in design of a control system. In other words, control and coordination of operation of high-speed solenoids can be performed without consideration of uncertainties of the time lapse. In an exemplary illustration, the invention is applied to controlling speed of a turbine generator of a type used in space vehicles. High-speed solenoids are used to control bursts of hydrogen and oxygen flow into a combustion chamber of the turbine generator. Speed control is maintained by controlling a rate and duration of the bursts.

A transformer diagnosis apparatus and method which can advantageously be used for on-line diagnosis of a transformer, and by which transformer properties may be monitored and / or determined. The diagnosis method includes collecting, for at least two different transformer loads, measurements of a current being indicative of the transformer load, as well as measurements of at least one further transformer AC signal. The method further includes deriving, from the collected measurements, at least two values of a quantity which depends on a transformer property as well as on transformer load; and determining, from the derived values, a set of coefficient(s) of a relation for how the quantity is expected to vary with transformer load. The method further includes using the determined coefficient(s) in performing a diagnosis of the transformer.

The invention provides a permanent magnet synchronous motor inter-turn shorted-circuit fault diagnosis method. The method uses a Hall current sensor to collect a current signal at a stator end. The current signal is subjected to FFT analysis using a Nicolet data acquisition instrument, then the harmonic amplitude is processed, a fault coefficient of the collected current signal is compared with a preset fault coefficient, and that whether the permanent magnet synchronous motor has an inter-turn shorted-circuit fault or not is determined.

The present invention provides a method and apparatus for determining the functional status of an electromagnetic valve having a solenoid and plunger including determining the electro-mechanical switching time of a valve based on characteristics of an electrical characteristic responsive to the solenoid; comparing the valve electro-mechanical switching time to a predetermined value; and generating a valve status signal dependant on the results of the comparison.

The invention relates to a power transformer winding deformation state multi-information detection method and device, and belongs to the technical field of power equipment fault diagnosis. The method comprises the steps of detecting current, voltage and a phase angle at a high voltage side and a low voltage side, detecting ultrasonic signals, detecting vibration signals, thereby realizing online detection, fault phase detection, fault position detection and fault type detection for the winding deformation state, and effectively solving a problem that the running state, the fault position and the fault type of a power transformer winding cannot be effectively detected because of the simplified detection signals. The device comprises a voltage transformer, a current transformer, an ultrasonic probe, a vibration sensor, a signal conditioning circuit, an AD conversion circuit and a central processing unit, wherein the output ends of the voltage transformer, the current transformer, the ultrasonic probe and the vibration sensor are connected with the input end of the signal conditioning circuit, the output end of the signal conditioning circuit is connected with the input end of the central processing unit through the AD conversion circuit, and the output end of the central processing unit is connected with a communication bus.

The present invention discloses a method and a system for on-line diagnosis of transformer winding deformation. The method comprises: injecting a sweep signal from a high-voltage lead-out line of a transformer winding by way of magnetic field induction; acquiring an excitation current signal induced on the high-voltage lead-out line of the transformer winding; obtaining the response current signal on the neutral ground line of the transformer winding; obtaining the frequency response curve according to the transfer function relationship, which is constructed by using the excitation current signal and the response current signal, of the transformer winding; based on the diagnosis method in the DLT911-2004 standard, diagnosing the frequency response curve; and determining the deformation of the transformer winding. According to the invention, the excitation signal injection and response signal measurement do not need direct electrical connection with the transformer winding, making the high-voltage transformer winding operate in a high-voltage and high-current condition and realizing the real-time detection of the transformer winding deformation online.

The invention discloses a permanent magnet synchronous motor fault diagnosis method based on deep learning. Main faults of a permanent magnet synchronous motor comprise stator winding open circuit, stator winding short circuit, eccentricity, demagnetization, rotating shaft bending, bearing faults and the like. According to the method, a stator current signal, a vibration signal and a noise signalof a motor are respectively acquired through a current sensor, a vibration sensor and a sound sensor. The method comprises the following steps: 1) preprocessing a signal; 2) extracting the time-domain, frequency-domain and time-frequency characteristics of the signal; 3) training a deep neural network based on characteristic big data; and 4) diagnosing the fault type of the permanent magnet synchronous motor based on deep learning. According to the method, multiple sensors and multiple fault features are fused, and the method has higher applicability than similar methods.

The invention discloses a method for establishing the corresponding relationship between the transformer winding deformation fault and sweep frequency impedance characteristic. The method comprises the following steps: establishing an equivalent circuit model for a transformer winding; performing circuit parameter fault simulation; carrying out the sweep frequency impedance testing and simulating of a winding deformation fault; using the correlation coefficient method to calculate the relevant coefficients before and after the changes of the sweep frequency impedance curve; using the three-dimensional finite element method to calculate the electric parameters at the winding deformation state; and through the comparison and analysis of the above two, obtaining the corresponding relationship between the electric parameter change and the type of the transformer winding deformation fault. Compared with the prior art, the method of the invention can establish the corresponding relationship between the winding deformation and the sweep frequency impedance change characteristic directly and quantitatively so that deep explanation is possible for the sweep frequency impedance characteristic curve, that the transformer winding deformation diagnosing precision is increased, and that the large amount of human labor, material and financial devotion of the oil extraction hanging hood are reduced when the transformer is subject to offline maintenance.

The invention relates to an aviation electromechanical actuator fault diagnosis method based on the symbolic dynamic information entropy theory and the improved Parks clustering algorithm. Symbolization processing of amplitude time series of bus current of an inverter side of an electromagnetic actuator can be carried out, and the calculated information entropy value and the calculated maximum amplitude of the bus current time series can be used as the two characteristic quantities of the electromechanical actuator fault diagnosis, and then a standard fault characteristic matrix based on training samples can be established, and then the fault types of the sample to be detected can be determined by calculating the distance between the sample to be detected and the fault characteristic matrix by adopting the improved Parks clustering algorithm. Compared to the conventional methods, the characteristic extraction and fault diagnosis method provided by the invention is advantageous in that the calculation is simple, and the required data size is small, and various electromechanical actuator faults can be effectively identified and diagnosed.

The invention relates to an offshore doubly fed motor stator winding turn-to-turn short circuit early fault identification method, and is used for judging the doubly fed motor stator winding turn-to-turn short circuit and determining the phase of the turn-to-turn short circuit. The method comprises the following steps that 1) the three-phase signals of an offshore doubly fed motor under fault identification are acquired, including the stator three-phase voltage, the rotor three-phase voltage, the stator three-phase current, the rotor three-phase current and the rotor rotating speed; 2) the three-phase signals are converted to a dq axis coordinate system, the motor parameters are acquired, then the three-phase signals are converted to an alphabeta axis coordinate system, the estimated stator current is acquired through an observer, and the estimated current difference is calculated and decomposed so that a fault severity factor xi is obtained; and 3) when the amplitude of the fault severity factor xi caused by the turn-to-turn short circuit fault reaches the fault early warning value, the stator winding turn-to-turn short circuit fault occurs on the offshore doubly fed motor under fault identification. Compared with the methods in the prior art, the offshore doubly fed motor stator winding turn-to-turn short circuit early fault identification method has the advantages that the fault phase can be reliably located and the robustness is high.

A method for detecting actuation of an armature associated with a solenoid includes providing a voltage potential to a solenoid coil associated with the solenoid. The method also includes measuring a current flowing through the solenoid coil. The method further includes switching the voltage potential off when the measured current reaches a predetermined maximum value. The method also includes switching the voltage potential on when the measured current reaches a predetermined minimum value. The method further includes measuring a time period between pulses associated with the switching on and off of the voltage potential. The method also includes comparing the measured time period between pulses with predetermined data indicative of an inductance growth level associated with the coil. The method further includes determining, based on the comparison, a pull-in time of an armature associated with the solenoid.

The disclosure discloses a power transformer winding fault positioning method based on deep convolutional neural network integrated with visual identification, including 1) a winding equivalent circuit is established, and a transfer function thereof is calculated; 2) a sine wave excitation source is set at one end of the power transformer winding to obtain the amplitude-frequency characteristic curve of each winding node; 3) circuits under various fault statuses are subjected to scanning frequency response analysis to extract amplitude-frequency characteristics; 4) a feature matrix is established based on the obtained amplitude-frequency characteristics; 5) scanning frequency response analysis is performed on the diagnosed power transformer to form a feature matrix; 6) the feature matrix is converted into an image, simulation and historical detection data are used as a training set, and a deep convolutional neural network is input for training; 7) diagnosed transformer is subjected to fault classification and positioning.

The present invention relates to a transformer diagnosis apparatus and method which can advantageously be used for on-line diagnosis of a transformer, and by which transformer properties may be monitored and / or determined. The diagnosis method comprises collecting, for at least two different transformer loads, measurements of a current being indicative of the transformer load, as well as measurements of at least one further transformer AC signal. The method further comprises deriving, from the collected measurements, at least two values of a quantity which depends on a transformer property as well as on transformer load; and determining, from the derived values, a set of coefficient(s) of a relation for how said quantity is expected to vary with transformer load. The method further comprises using the determined coefficient (s) in performing a diagnosis of the transformer.

A method for detecting actuation of an armature associated with a solenoid includes providing a voltage potential to a solenoid coil associated with the solenoid. The method also includes measuring a current flowing through the solenoid coil. The method further includes switching the voltage potential off when the measured current reaches a predetermined maximum value. The method also includes switching the voltage potential on when the measured current reaches a predetermined minimum value. The method further includes measuring a time period between pulses associated with the switching on and off of the voltage potential. The method also includes comparing the measured time period between pulses with predetermined data indicative of an inductance growth level associated with the coil. The method further includes determining, based on the comparison, a pull-in time of an armature associated with the solenoid.

A method of monitoring a solenoid (1) of a directional control valve (DCV) associated with a subsea control module (6) in a subsea hydrocarbon production system is disclosed. A voltage is applied across a coil of the solenoid, for moving the armature (4) thereof, and a current through the coil is sensed to produce an indication of if and when the armature is moved.

A method of determining change in actuator position includes determining a slope of the inductor current with time and determining whether the slope exceeds a first predetermined slope for a first predetermined time, determining whether the slope is less than a second predetermined slope for a second predetermined time when the slope exceeds the first predetermined slope for the first predetermined time, and determining whether the slope exceeds a third predetermined slope for a third predetermined time when the slope is less than the second predetermined slope for the second predetermined time. The method further includes determining the change in actuator position when the slope exceeds the third predetermined slope for the third predetermined time.

The invention discloses a permanent magnet synchronous motor turn-to-turn short circuit fault diagnosis method based on magnetic field distribution monitoring. The method is characterized by, to begin with, in the steady state, carrying out analysis on an equivalent circuit obtained when the permanent magnet synchronous motor has turn-to-turn short circuit fault, and obtaining a series of diagnosis steps; and through the diagnosis steps, judging whether the motor has the turn-to-turn short circuit fault by utilizing a high-frequency component of stator tooth magnetic flux.

The invention discloses a transformer winding state recognition method based on a fuzzy adaptive resonance neural network. The transformer winding state recognition method comprises the steps of (1) arranging monitoring points of a vibration sensor, setting the sampling frequency and the sampling time of a data acquisition instrument, and acquiring transformer vibration signals; (2) performing wavelet packet decomposition and reconstruction on the transformer vibration signals; (3) extracting vibration signal sub-band energy values; (4) analyzing the vibration signal sub-band energy values of each vibration monitoring point, and selecting feature band energy of valid monitoring points to construct a feature vector so as to act as input of the fuzzy adaptive resonance neural network; (5) building the fuzzy adaptive resonance neural network, adjusting network parameters until set precision is reached; and (6) performing recognition on transformer winding state through the fuzzy adaptive resonance neural network. The transformer winding state recognition method can judge a transformer winding pressing state accurately and quickly, and can be applied to online monitoring and recognition for the transformer winding pressing state.

The invention discloses a steam turbine generator rotor turn-to-turn short circuit diagnosis device based on a detection coil. The device is characterized by comprising the U-shaped detection coil radially mounted inside a generator in a manner of stretching across a stator iron core section, a high-resistance-value resistor is parallelly connected at an outlet of the U-shaped detection coil, the U-shaped detection coil is composed of high-strength alloy, surrounds the stator iron core section and is contactless with the stator iron core section and a stator winding, and the bottom of the U-shaped detection coil is positioned in an air gap between a stator and a rotor. The invention further discloses a diagnosis method based on the device. By the device and the method, the defects of the prior art can be improved, and the diagnosis level of faults of this kind is raised.

The present invention relates to an apparatus for measuring winding resistances of windings in a delta-connected transformer, comprising at least a first and a second DC current source (S1, S2) connected each between the phase ends of a first (A) and a second leg (C; B) respectively of the primary side (P) of the transformer and at least a third DC current source (S3) connected between two nodes (a, b) of the secondary side (S) of the transformer. Furthermore the invention relates to a method for measuring a winding resistance of windings in delta-connected transformers, comprising the steps of applying a first and a second measuring current to each one of two corresponding legs (C, B), applying a third measuring current (I2) between two nodes (b, a) of a pair of windings on the secondary side (S) and measuring at least a winding resistance of the winding between said nodes (b, a) on the secondary side (S) of the transformer and / or the winding resistance of a leg (A) of the primary side (P) as soon as an inductive voltage drop in the windings substantially equals zero.