52results about How to "Realize online diagnosis" patented technology

The invention provides a fault on-line diagnosis and early warning method of a flameproof dry-type transformer for mine in order to raise the accuracy and rapidity of fault diagnosis. The method comprises the following steps: determining monitoring quantity; extracting characteristic values: extracting a three-dimensional spectra parameter and two-dimensional statistical parameter in a partial discharge signal as characteristic quantities, with regard to operation voltage, current and iron core leakage current, extracting effective values of the operation voltage, the current and the iron core leakage current as characteristic values, and taking real-time values of a temperature parameter as characteristic quantities; using a normalization method to calculate a corresponding value of each characteristic quantity and taking the corresponding value as an input parameter of an intelligent diagnosis system; collecting values of each monitoring quantity under different environment, and obtaining training and testing samples of a nerve network under corresponding environment; establishing a nerve network: selecting a generalized RBF nerve network intelligent diagnosis method to establish a nerve network; utilizing a sample data training nerve network and forming a fault diagnosis tool; establishing a database; storing collected real time data and the above diagnosis result into a ground server real-time database and a real-time early warning information table, and carrying out diagnosis and early warning through an expert system.

The invention provides a pressure monitoring system marking instrument of an automobile tyre and a marking method thereof. The marking instrument includes two parts; one is a tyre pressure sensor and the other is a diagnosing marking device; the tyre sensor includes a central control module 2, a sensor 1, a RF transmitting circuit and a lower frequency receiving circuit; the tyre sensor is connected with the lower frequency receiving circuit and the central control module 2; the central control module 2 is connected with the RF transmitting circuit and the sensor 1; the marking instrument consists of an SCM, the lower frequency transmitting circuit, the RF receiving circuit, a human-computer interface and a communication interface; the SCM is connected with the lower frequency transmitting circuit; the tyre sensor is connected with the RF receiving circuit which is connected with the SCM; the SCM is connected with the human-computer interface and the communication interface. The invention can simply realize the diagnosing and the marking of the pressure monitoring system sensor of the tyre, is suitable for the automobile types of any collocation, is not interfered by the tyre pressure monitoring system on other automobiles and can not affect other automobiles.

The invention discloses a CAN (Controller Area Network) communication control device used in a control system of a converter. The CAN communication control device comprises a CAN bus interface unit and a microcontrol unit, wherein the CAN bus interface unit is connected with a field bus to receive or transmit messages to be delivered between the communication control device and other converter control devices on a bus network, and the messages are corresponding to a CAN standard protocol or user-defined field bus protocols; the microcontrol unit is connected with a CAN bus interface circuit to receive the messages sent by other remote converter control devices through the bus network, the messages are corresponding to the CAN standard protocol or user-defined field bus protocols, the messages are analyzed and treated according to inhouse configuration files and converted into parallel data information, and the configuration files are written on-line through a serial bus network through a serial bus interface unit connected with the microcontrol unit. The device can configurate different communication message IDs (identities) for the CAN communication control devices of different converters in a convenient and real-time mode, so that basic applications are unified.

The invention discloses a medical examination report cloud storage management system, comprising: an information collection module for collecting diagnosis and treatment information; a diagnosis and treatment information identification code generation module for generating a unique diagnosis and treatment information identification code for identifying patient diagnosis and treatment information; The storage module is used to store the collected diagnosis and treatment information and the corresponding diagnosis and treatment information identification code; the condition query module is used to query the corresponding diagnosis and treatment information according to the diagnosis and treatment information identification code; the payment module is used to generate the payment function. Two-dimensional code; download display module, used to download and display the diagnosis and treatment information of successful payment; secondary storage module, used to establish patients' personal health information files for patients to download and query. The invention also discloses a medical examination report cloud storage management method.

The invention discloses an on-line winding deformation diagnosis method, system and device of a transformer. The method comprises the following steps: analyzing vibration characteristics of a transformer; drawing a relation curve of transformer vibration and load currents according to an analysis result of the vibration characteristics; and determining whether the winding deforms or not accordingto the linear degree of the relation curve of the transformer vibration and the load current. According to the embodiment of the invention, vibration characteristics before and after a transformer fault condition are detected and the characteristic change of the vibration frequency of the transformer can be extracted; on-line diagnosis of deformation of the transformer winding is realized throughthe relation curve of transformer vibration and load current. According to the invention, power failure operation does not need to be conducted on the transformer in the diagnosis process of the transformer, the deformation condition of the transformer winding can be detected in real time, and the stability of a power supply network of a power system is guaranteed.

The invention relates to a PMSM drive system inverter open-circuit fault online diagnosis method, which can carry out online fault diagnosis and positioning on various inverter open-circuit faults. The method comprises the steps: introducing a Luenberger observer to track a PMSM three-phase current so as to obtain a three-phase current observation residual error as a fault diagnosis basis; designing a sampling strategy, and obtaining an original sample set for training; in offline training, introducing a principal component analysis method to preprocess an original sample set to obtain a datadimension reduction model, and then acquiring a classification model by training a support vector machine; finally, operating the dimension reduction model and the classification model in a driving system, and achieving the online diagnosis and positioning of faults. According to the method, hardware equipment is not added, and driving control is not affected; meanwhile, the method is not affectedby load and model parameter changes; through machine learning of actual working conditions, the method does not depend on a diagnosis basis set manually, and the possibility of misdiagnosis is reduced.

The invention provides a GIS insulation state diagnosis method based on gas component analysis. The GIS insulation state diagnosis method based on gas component analysis comprises the steps that the moisture content inside a GIS gas chamber is measured through a precision mirror plane dew point method; when the moisture content inside the GIS gas chamber meets requirements, varieties and contents of gas decomposition components inside the GIS gas chamber are determined through measurement, and whether electric discharge exists inside GIS equipment or not is judged; if electric discharge exists in the GIS equipment, whether electric discharge in the GIS equipment relates to an organic insulating medium or an inorganic insulating medium is judged according to whether carbonaceous electric-discharge-related gas decomposition components exist inside the GIS equipment. Compared with GIS insulation state diagnosis methods in the past, the GIS insulation state diagnosis method based on gas component analysis has the advantages that the anti-electromagnetic interference performance is better, on-line GIS equipment insulation state diagnosis can be realized, detect type judgment is simpler, and the GIS insulation state diagnosis method is easier to apply and popularize.

The invention, which relates to the field of mechanical fault diagnosis, discloses a mechanical fault diagnosis method based on a dual-tree complex wavelet packet sub-band average kurtosis graph, thereby improving the robustness and accuracy of mechanical fault feature extraction and fault type identification. According to the invention, with utilization of non-stationary and instantaneous impactcharacteristics of a mechanical fault vibration signal, a sub-band average kurtosis graph method based on a dual-tree complex wavelet packet is provided, wherein the efficiency and the accuracy are both considered in dual-tree complex wavelet packet transformation; the sub-band average spectral kurtosis can eliminate the influence of random impact interference on the kurtosis graph, can find the frequency band where the fault characteristic signal is located more accurately; the filtered signal is analyzed through a square envelope spectrum and thus the accurate extraction of the bearing faultcharacteristics and the precise recognition of the fault type are realized. The method is suitable for mechanical fault diagnosis.

The embodiment of the invention provides an online positioning method for distribution network single-phase fault, which relates to the field of power system fault positioning and can judge a fault circuit without depending on zero-sequence current and realize quick online positioning on the distribution network single-phase grounding fault. The method of the specific scheme comprises steps: when SCADA (Supervisory Control And Data Acquisition) determines a single-phase fault judgment condition is met, a phase current recording command is sent to K RTUs (Remote Terminal Unit), wherein the phase current recording command comprises the fault happening time determined by the SCADA and the fault phase information; the K RTUs sample fault phase current signals in M cycles before and after the fault happening time, effective energy is obtained through wavelet transformation, and the effective energy is transmitted to the SCADA; and according to the effective energy returned by the K RTUs, the SCADA judges a single-phase fault line from lines monitored by the K RTUs. The method of the invention is used for judging the single-phase fault line.

The invention discloses a method for examining loosing of iron tower bolts. The method combines the iron tower vision measurement technology with theoretical calculation to predict loosing of bolts, and adopts the vision measurement method to measure vibration of iron towers. By adopting the non-contact method, potential safety hazard caused by iron tower climbing measurement is avoided, natural wind is utilized as the power source, and the method is time-saving and labor-saving as compared with artificial iron tower climbing cable-lanyard measurement.

The invention belongs to the field of biological process diagnosis, and in particular relates to a compound sensor and a method for biological process diagnosis and material characteristic analysis. The invention provides a modular compound sensor for online biological process diagnosis and analysis of characteristic analysis. The sensor mainly consists of a packed bed bio-membrane reactor, a microbial fuel cell (MFC), a gas flowmeter and a pH meter, wherein the packed bed bio-membrane reactor performs a quick biochemical reaction for a liquid phase organic matter in a target biological process, and the working state of the target biological process is diagnosed by means of online-detecting the gas flow, the pH of a fermenting liquid and electric signals of the MFC and comparing the signals among the three. The modular compound sensor is mainly characterized in that various sensors comprehensively diagnose and work stably; the sensor is in modular design and strong in mobility; the sensor can realize online diagnosis of industrial biological processes (such as biogas fermentation and hydrogen fermentation).

The invention provides an energy storage battery unsupervised fault diagnosis algorithm based on similarity measurement, and belongs to the field of energy storage battery fault diagnosis. The problem that high-efficiency series battery pack fault detection and positioning cannot be realized autonomously in the prior art is solved. The method comprises the following steps: monitoring, collecting and summarizing signals in the charging and discharging processes of the energy storage battery, and constructing an unsupervised fault diagnosis data set; the collected signals are cleaned, abnormal points are removed, and meanwhile, a filter is constructed to suppress noise mixed in sampling; constructing a key point sequence of each single battery according to the signal characteristics of the charging and discharging process; extracting segmentation trend term characteristics of the monitoring signal, segmenting the complete monitoring signal into time slices, and performing segmentation linearization; constructing a single battery outlier calculation module; information fusion of multiple standards is realized, the outlier degree is obtained and serves as an important measurement index of fault occurrence, and then a fault battery is judged. The method has the advantages of quickly checking faulty batteries and providing maintenance suggestions.

The invention discloses a dynamic diagnosis method of a throttle valve. The method includes the steps that the target opening value of the throttle valve is acquired; the static deviation range valueof the throttle valve is acquired according to the target opening value; the actual dynamic deviation limiting value of the throttle valve is acquired; the position deviation range value of the throttle valve is acquired according to the actual dynamic deviation limiting value and the static deviation range value; the opening error of the throttle valve is acquired; whether the opening error of the throttle valve is within the position deviation range value or not is judged; if not, it is determined that the throttle valve breaks down. By means of the dynamic diagnosis method of the throttle valve, the throttle valve is dynamically diagnosed under the condition without dependent on a direct current motor and other equipment, the working state of the throttle valve is detected in real time,and timely feedback generated when the fault occurs is achieved.

The invention discloses a power transformer defect on-line diagnosis method using operation information, which comprises the following steps of: acquiring voltage and current data of each phase of a high-voltage side and a low-voltage side of a transformer within a period of time, and performing parameter identification on equivalent circuit parameters of the transformer by adopting a parameter identification algorithm; the method comprises the following steps: acquiring voltage and current data and temperature data of each phase of the high-voltage side and the low-voltage side of a transformer, automatically modeling, automatically learning, automatically training, generating a proper heat accumulation model, inputting voltage and current effective values of the high-voltage side and the low-voltage side of each phase and starting moment temperature in a period of time to the heat accumulation model, and outputting ending moment temperature by the heat accumulation model; according to the deviation between the actually measured temperature of the transformer and the temperature output by the heat accumulation model and the equivalent circuit parameter identification result of the transformer, the defect and fault type and degree of the transformer can be effectively judged, transformer defect online diagnosis based on comprehensive electric and non-electric operation parameters is realized, and the accuracy of defect and fault diagnosis is improved.