43results about How to "Realize online fault diagnosis" patented technology

The present invention relates to a distributed intelligent motor monitoring system. The system includes a locale bottom layer intelligent monitoring substation, a high layer intelligent monitoring main station, and a modular system application software for executing data acquisition and information processing to realize motor monitoring function. Wherein, the monitoring substation is connected to the motor in corresponding position, and is composed of an intelligent monitoring module including monitoring instrument, instrument and data sampler, the intelligent monitoring main station is composed of computers for realizing motor information centralized processing and intelligent monitoring, the substation and the main station is interconnected by data communication network. The system can realize the real time acquisition and local/remote monitoring for the parameters of single or multiple motors, the motor running status recognition and failure diagnosis function. The system not only can be used as the special equipment for delivery tests and type approval test for the motor manufacturer, but also can be broadly used for the motor real time monitoring or on line failure monitoring for the industrial department such as metallurgy, chemical industry, petroleum and pharmacy.

This invention provides an on-line monitor and fault diagnosis method for PWR nuclear power plant including the following steps: 1, data collection, 2, digit filtration and pre-process, 3, acquiring extremum points to carry out polygon process to the waveforms, 4, merging the extremum points and eliminating single peaks, 5, identifying character points of the waveforms in terms of upgrading, transmission and keeping to check current and waving amplitude, 6, judging step sequence and operation time and diagnoses fault, 7, comparing the consistency of four rod-beam operations of a sub-set to estimate them according to deviations and finish single-step analysis of the sub-set waveform, 8, collecting and displaying waveforms, storing effective data and storing action recordings.

The invention discloses a method and a device for diagnosing an information fusion fault of an underwater robot propeller. The device comprises a signal acquisition and preprocessing device and a fault identification device, wherein the fault identification device compares propeller voltage and current signals acquired by the signal acquisition and preprocessing device with voltage and current signals in the state of normal rotating speed, detects whether a fault occurs or not, and calculates size of the blocking fault. The method and the device fill the blank in fault diagnosis of the underwater robot propeller, and have the advantages that rotating speed signals of the underwater robot propeller acquired by a rotating speed sensor can be processed by a neural network of a cerabellar modearticulation controller (CMAC); the neural network of the CMAC is trained by classical fault mode data of the propeller; the trained neural network of the CMAC is used to identify the fault and calculate the blocking size of the fault so as to realize fault online diagnosis for the propeller; and the method and the device not only can diagnose the fault condition of the underwater robot propeller, but also can forecast the numerical values of the propeller in normal working state.

A method for on-line diagnosing gradually-changing fault of electronic current transformers comprises the following steps: collecting output signals of electronic transformers of a whole transformer substation, calculating instant value of theoretical current at the tail ends of power transmission lines and on secondary sides of transformers at any moment, comparing the instant value of the theoretical current with the corresponding collected value, respectively calculating residual errors of the electronic current transformers at the front and tail end of each power transformation line and the primary side and the secondary side of each transformer, judging whether gradually-changing fault occurs on the electronic current transformers by comparing the residual errors with preset threshold values, and simultaneously performing Kirchhoff detection by injecting current into a busbar to position a fault transformer. The method is easy and convenient to operate, high in calculation accuracy, and capable of achieving on-line diagnosis on the gradually-changing fault under the condition that the electronic current transformers have no power failure or offline and require no other additional hardware device.

The invention discloses a method for testing initial position angle of a motor rotor and solves the technical problem that the prior art is high in requirements on initial position angle testing conditions of the motor rotor and difficult in actual operation. The method includes following steps: step 1, applying a current i on a to-be-tested motor to enable the same to run; step 2, after the motor runs, enabling the current i to be zero; step 3, measuring voltage ud and uq of a shaft d and a shaft q of a motor stator; step 4, calculating according to a triangular function relation between ud and uq to acquire initial position angle deviation theta err of the motor rotor. The initial position angle deviation of the motor rotor is calculated by directly using the voltage of the d shaft and the q shaft of the motor stator, and corresponding relation between voltage at the motor end in a motor controller and the initial rotor position angle is made clear; the method is simple and suitable for engineering site operation; online fault diagnosis and error correction control can be realized, and system function safety can be improved.

An automatic fault diagnosis system triggered by a fault model disclosed in the present invention includes: a sensor for obtaining vibration acceleration signals of each component of the equipment to be detected; a fault model for storing the corresponding component type, component fault characteristic frequency and corresponding component type and the component fault code of the component fault characteristic frequency, when there is a frequency component matching the component fault characteristic frequency in the vibration acceleration signal, the component fault code is sent to the fault classifier and the start signal is sent to the fault level evaluation module; the fault classifier, for the component The fault code is classified and the corresponding fault type information is searched, and the fault type information is output as the fault type diagnosis result; the fault level evaluation module calculates the vibration intensity according to the vibration acceleration signal after receiving the start signal, and evaluates the fault level to obtain the fault level diagnosis result . The invention can improve the fault diagnosis efficiency of wind turbines and other equipment.

The invention provides a power plant induced draft fan vibration fault diagnosis method, which comprises the following steps: representing the state of an induced draft fan through different characteristic values, setting characteristic value measuring points on the induced draft fan, and obtaining the detection data of each characteristic value through the characteristic value measuring points. According to the method, historical data and online data are combined, an artificial intelligence technology is utilized, the vibration fault coding value of the induced draft fan is calculated in realtime according to the online characteristic value data, the vibration fault of the induced draft fan is obtained, and maintenance guidance is conducted. According to the power plant induced draft fanvibration fault diagnosis method, the correlation between the vibration characteristic value data is considered, online fault diagnosis of the state of the induced draft fan is achieved, and a basisis provided for state maintenance of the induced draft fan.

The invention relates to a magnetic levitation train speed and distance measuring system. The magnetic levitation train speed and distance measuring system comprises a plurality of induction proximityswitch sets arranged at the bottom of a train, speed and distance measuring control boxes arranged in train-mounted equipment cabinets at the activated end and the non-activated of the train, digitalservo acceleration sensors arranged at the bottoms of the speed and distance measuring control boxes for detecting the acceleration of the train, induction proximity switch detection objects, and speed and distance measuring control units arranged in the speed and distance measuring control boxes at the two ends of the train; and the speed and distance measuring control units are connected with the digital servo acceleration sensors and the induction proximity switch sets correspondingly, and metal sleepers parallelly distributed on a rail serve as the induction proximity switch detection objects. Compared with the prior art, the magnetic levitation train speed and distance measuring system has the advantages of low cost, accurate measuring, high environmental adaptability, small measuring error, high anti-jamming ability, high usability, reliability, safety and the like.

The invention relates to a rotary mechanical equipment fault diagnosing method based on diagnosing evidence smooth updating and belongs to the technical field of rotary mechanical equipment fault monitoring and diagnosing. The diagnosing evidence during equipment operation is obtained through an evidence acquiring method, a conditioning linear weighting evidence fusion rule is recursively used to update the diagnosing evidence updated at the previous moment with the current-moment diagnosing evidence, and the updated current-moment diagnosing evidence is obtained. Under a certain decision making rule, the updated diagnosing evidence is used for fault decision making. On the basis of the reliability of the current-moment, historical-moment and future-moment diagnosing evidences, the smooth weighting in linear fusion evidence updating is determined, the updated current-moment diagnosing evidence is enabled to have useful diagnosing information of historical and future moments, and the decision made on the basis of the updated diagnosing evidence is more accurate and reliable than the decision made on the basis of diagnosing evidence not updated.

The invention discloses rotor ground on-line monitoring device and method based on adaptive frequency square-wave voltage. The device comprises a rotor ground real-time on-line monitoring processing unit, an adaptive frequency regulation square-wave power panel, a coupling resistance board and first and second measuring transducers. In the method, the coupling resistance board is adopted to prevent excitation high voltage from striking back the monitoring device; the adaptive frequency square-wave power panel adaptively regulates control voltage frequency corresponding to the power panel according to a fault mode of a motor rotor; the measuring transducers acquire control voltage and measuring voltage which are output by the adaptive frequency square-wave power panel; and the rotor ground real-time on-line monitoring processing unit judges a generator fault according to the control voltage and the measuring voltage. The invention has high monitoring precision and can simply find the fault point, thereby shortening repair time and reducing economic loss brought by power failure.

The intention discloses a converter transformer fault online diagnosis method based on three-sensor reasoning, and belongs to the technical field of ultra-high voltage direct-current power transmission device fault diagnosis. The method includes the steps of obtaining online data of a converter transformer by using online detection instruments, including the ultra-high frequency detection instrument, the broadband pulse detection instrument and the transient earth voltage (TEV) detection instrument, which can be obtained on projects at present as three sensors; calling the actually-measured online data of the converter transformer to achieve fault diagnosis, wherein effective discharging information is extracted from the actually-measured online data of the converter transformer, three types of sensor characteristic space are established, the fault diagnosis results of the three types of sensor characteristic space are obtained, the differences and similarities of the fault diagnosis results are judged, the diagnosis results are finally output, reasoning is conducted on data of the three sensors, and the final diagnosis results under the condition are obtained. By means of the method, the converter transformer fault diagnosis accuracy is effectively improved, and the online diagnosis of the transformer converter fault is achieved.

The present invention discloses an industrial process fault diagnosis method based on a switching supervised LDSM (Linear Dynamic System Model), which is used for fault diagnosis on the condition that a key quality variable is obtainable in an industrial process. According to the fault diagnosis method, a supervised LDSM is expanded to a multi-modal form, and a switching supervised LDSM is established, thus dynamic characteristics and random characteristics of process data are considered, and important process operation information included in quality variables is also fully utilized. In comparison with the conventional method, the fault diagnosis method improves the capability of describing industrial process operation states by the model, improves a fault diagnosis effect, shortens delay time of diagnosis, enables fault processing to be more timely and effective, and is more beneficial to automatic enforcement of industrial process.

The invention discloses a fault diagnosis method and application of an electric vehicle driving motor, and belongs to the technical field of vehicle monitoring. In order to solve the problem that prediction maintenance, online health detection and the like cannot be realized in the conventional electric vehicle motor driving, the invention provides a fault diagnosis method, which comprises the following steps: firstly, analyzing a fault formation mechanism of an electric vehicle driving motor; secondly, establishing a mathematical model and a fault mechanism theory, and establishing a relationship between the electric vehicle driving motor fault and a measurable signal and a calculation method; and then measuring the magnetic field and port parameters of the electric automobile in real time. And carrying out data analysis, and dynamically updating the built part health model to realize the detection of the state of the motor so as to provide a decision. Giant magnetoresistance and the long-period fiber grating sensing technology are combined for the first time and applied to fault diagnosis of the electric vehicle, full-life-cycle motor state monitoring is achieved, the operation and maintenance cost of the vehicle can be reduced, and the reliability and intelligence of an electric drive system of the electric vehicle are improved.

The invention discloses an online comprehensive service system for electric automobiles. The online comprehensive service system comprises a clustered repair control center, a plurality of repair control terminals and a plurality of electric automobile part manufacturing factory terminals. The repair control terminals and the electric automobile part manufacturing factory terminals are connected to the clustered repair control center through a communication network to exchange information. When electric automobiles need repairing at the repair control terminals, the clustered repair control center, based on the fault detection result of the electric automobiles, connects the repair control terminal to the electric automobile part manufacturing factory terminal with problem parts. Finally, the technicians at the electric automobile part manufacturing factory terminals guide the working staff at the repair control terminals to complete the repair work to the electric automobiles. The service system of the invention is capable of online detecting faults and remotely controlling repair robots and capable of integrating online repair guidance and skill training into one. Further, with such a service system, the problem of shortage of technicians can be overcome and online teaching can be given to electric automobile repairmen.

The invention discloses a regional integrated energy system evaluation method based on an energy Internet layered architecture, and the method comprises the steps: taking the geographic position of equipment in an energy station system as an Internet system node, and marking a connection port address of the corresponding equipment at the Internet system node; using a power transmission line connected with equipment in an energy station system as an Internet system link, marking the power transmission line on the Internet system link as information, and it can be understood that a string of nodes and links between a signal sending node and a signal receiving node establish a power grid topological structure for a path of an Internet system; power analysis of power grid equipment is facilitated, the power analysis and application requirements of an energy station system are met, and online fault diagnosis and early warning of a power system are achieved.