77results about How to "Improve fault detection accuracy" patented technology

The invention discloses a relay utilizing fault transient state current component protection, comprising a modal hybrid circuit, a transient state filtering unit, a counter, a transient state time tracing unit, a transient state polarity detection unit, a multipath time and polarity comparison unit, a decision unit, a logic trapping unit, a first communication interface (6) and a second communication interface (7). An application method comprises the following steps: 1) supposing a fault occurred in Point F1; 2) generating high frequency signals by a fault phase and a non-fault phase; 3) sending data to an adjacent relay by a relay; 4) comparing the polarity and transient state time of a first wave with information recorded in other relays by each relay; 5) determining the tripping breaker, if a time difference of the transient state current reaching the two ends of an electricity transmission circuit is less than the ratio of the length of the electricity transmission circuit to the wave speed of the transient state current, and the polarities of the transient state current signals detected at the two ends of the electricity transmission circuit are the same; 6) determining the fault position by a time difference of a traveling wave reaching the two ends of the fault circuit; and 7) preventing the breaker from trapping by the relay, if the time difference of the transient state current reaching the two ends of the electricity transmission circuit is equal to the ratio of the length of the electricity transmission circuit to the wave speed of the transient state current andthe polarities of the transient state current signals detected at the two ends of the electricity transmission circuit are different. The invention has the advantages of high detection precision, quick response and low cost.

An apparatus for detecting a failure of an exhaust gas sensor disposed downstream of a catalyst converter in an exhaust manifold is provided. The apparatus comprises a control unit. The control unit determines a ratio between an amplitude value of a first output of the exhaust gas sensor and an amplitude value of a second output of an air-fuel ratio sensor. The air fuel ratio sensor disposed upstream of the catalyst converter. The control unit detects a failure of the exhaust gas sensor based on the ratio. In one embodiment, a statistical process using a successive least squares method is applied to the ratio. The control unit detects a failure of the exhaust gas sensor based on the statistically processed ratio. In another embodiment, the statistical process is applied to both the output of the exhaust gas sensor and the output of the air-fuel ratio sensor. The control unit detects a failure of the exhaust gas sensor based on a ratio between the statistically processed outputs of the exhaust gas sensor and the air-fuel ratio sensor.

An abnormality diagnostic device for a vehicle is provided with a first temperature sensor that detects the temperature of a rear-wheel drive motor, and a HV control computer that monitors the temperature of the rear-wheel drive motor by using the first temperature sensor and controls the rear-wheel drive motor. When a vehicle state satisfies a provisional determination condition indicating a connection abnormality of the first temperature sensor, the HV control computer performs verification processing of raising the temperature of the rear-wheel drive motor and verifying whether a detection value of the first temperature sensor demonstrates a predetermined variation, and establishes diagnosis of the connection abnormality on the basis of a result of the verification processing.

The invention relates to an improved DFD wireless sensor network code failure detecting method. The current detecting method has a low detecting precision. On the basis of obtaining the detecting result and initial detecting state of the neighbor nodes, the inventive method judges the node state normal if detected nodes, whose detecting result is zero, is more than the nodes whose detecting result is one in the nodes whose initial detecting result is possibly normal in the neighbor nodes to any node; contrarily, it is failed. The method detects the failure code by the data exchange and inter-detection between the neighbor nodes. The technology scheme is suitable for the sensor network with a few network nodes and the neighbor codes to be detected, and high failure rate, which largely improves failure detecting precision.

A thermostat malfunction detection device that detects a stuck open state of a thermostat includes: an estimated water temperature calculation module that calculates an estimated water temperature of a cooling water based on an operation state of an engine; an actual water temperature detection unit that detects an actual water temperature of the cooling water; a first determination module that establishes preliminary determination when an amount of change of a difference between the estimated water temperature and the actual water temperature within a determined period is equal to or larger than a first threshold value; a passing air amount control module that increases a passing air amount, when the preliminary determination is established; and a second determination module that establishes malfunction determination, when the difference is equal to or larger than a second threshold value, after the passing air amount has been increased.

The invention relates to a fault detection method of an unmanned aerial vehicle flight control system. Online detection of the fault of the actuator and the sensor of the fixed-ring unmanned aerial vehicle flight control system can be realized by the method. An unmanned aerial vehicle flight control system continuous nonlinear fault model is established on the basis of the unmanned aerial vehiclekinetic equation and the fault type; and then the unmanned aerial vehicle flight control system continuous nonlinear fault model is converted into an unmanned aerial vehicle flight control discrete time-varying fault model with the help of a nonlinear observer, and unmanned aerial vehicle flight control system fault detection is realized by using an equivalent space method. The robustness indicator is designed by aiming at the problem of poor robustness of the conventional equivalent space method under unknown interference so as to enhance the robustness of system fault detection. The extendedKalman filtering equation is utilized in the Krein space to realize recursive computation of the residual evaluation function to reduce the computational burden by aiming at the problem of high computational burden of online fault detection of the conventional equivalent space method. According to the method, quick alarm of the fault of the sensor and the actuator of the unmanned aerial vehicle can be realized so as to provide an effective basis for fault detection of the unmanned aerial vehicle flight control system.

A fault on the generator can be detected with the use of a simple arrangement. The output of the generator 12 which has multi-phase winding and is driven by an engine 11 is rectified and then converted by an inverter 133 into an alternating current at the frequency of a system before interconnected to the source of the system. After the engine 11 is started, the direct current voltage Vdc is monitored with a first fault monitor 40. When the direct current voltage Vdc rises up to a predetermined level, a connector relay 135 is closed. As the output of the inverter 133 is increased, the interconnection with the system source is enabled. After the interconnection, the direct current voltage and the output of the inverter are monitored with a second fault monitor 43. If the direct current voltage drops down to below the predetermined level before the output of the inverter reaches a rated level, the canceling and re-interconnection is repeated. Then, when the direct current voltage remains below the predetermined level after the re-interconnection, it is judged that the generator 12 has a fault such as a line breakage in the windings disconnection.

The invention discloses a pipeline robot detection device and a pipeline fault detection method. The pipeline robot detection device comprises a machine body, at least one rotatable support, detectioncomponents and angle sensors, wherein the rotatable supports are installed on the machine body and can rotate to first preset angles. The detection components are arranged on the rotatable supports and are used for detecting whether a pipeline fails or not, and the angle sensors are arranged in the rotatable supports and are used for detecting the current rotation angles of the rotatable supports. The rotatable supports can rotate, and the detection range can be expanded by utilizing the detection components arranged on the rotatable supports, so that the detection components can accurately detect detailed faults in the pipeline, the fault detection precision is improved, the pipeline can be repaired in time by manpower, and safe operation of the pipeline is ensured.

The invention discloses a fault warning method, a computer readable storage medium and a refrigeration device. The fault warning method applied to the refrigeration device. The refrigeration device comprises a box body and a number of accommodation chambers arranged on the box body. At least one microphone is arranged in each accommodation chamber. The fault warning method comprises the steps thata sound signal acquired by at least one microphone is determined; a sound parameter range corresponding to the position of each microphone is determined; according to the relationship between the sound parameters of each sound signal and the sound parameter range, whether the position of the microphone is abnormal is determined to generate a first determination result; and corresponding warning information is transmitted to a target terminal according to the first determination result. According to the technical scheme of the invention, maintenance personnel or users can locate a fault according to the warning information and timely process the refrigeration device; and the problem that stored food are damaged due to the failed and unusable refrigeration device is reduced.

The present invention relates to an air conditioner fault detection device, method and system. The air conditioner fault detection device is directly connected with a live line, a null line and a signal line between an indoor unit and an outdoor unit, voltage signals of the signal line are collected, the voltage signals transmitted on the signal line are seperated through comparison circuits thus to obtain communication signals transmitted by the indoor unit and the outdoor unit, the communication signals are transmitted to a microprocessor, the microprocessor determines fault and status information sent by the indoor unit and the outdoor unit, and fault points can be rapidly found, thereby bringing convenience for operation by the after-sale personnel. Meanwhile, a second threshold voltage of a second comparison circuit changes along with a power voltage, upper part waveforms transmitted on the signal line can thus be accurately separated without being influenced by changes of the power voltage, and thus the fault detection precision is high.

The embodiment of the invention provides a fault detection method, a fault detection system, fault detection equipment and a storage medium. In the embodiment, on the basis of a fault detection modelcorresponding to at least one component, input parameters of the at least one component can be combined to calculate an estimated output result corresponding to at least one component; the fault stateof the at least one component is determined according to the difference of the estimated output result and the practical output result; further, whether the component in the equipment to be detectedgenerates a fault or not can be fast determined under the condition of not influencing the normal production of the equipment to be detected; the efficiency is higher; and the fault detection accuracyis higher.

The invention discloses a method for detecting industrial process faults basing on a multi-sampling rate factor analysis model. The method comprises the following steps of: collecting data of different sampling rates in a normal working state; establishing a multi-sampling rate factor analysis model; constructing two detection statistic values T<2> and SPE and the corresponding statistical limitsthereof (T<lim><2>) and SPE<lim> as shown in the specification using latent variables and prediction errors of the model; detecting an online industrial process to obtain a test sample; and estimatingthe latent variables and the prediction errors of the test sample using a existing model structure, calculating corresponding statistic values, and obtaining a final fault detection result. Accordingto the industrial process fault detection method based on multi-sampling rate factor analysis model, the multi-sampling rate information processing is achieved, data information can be fully utilized, and the variance differences of data noise matrices can be fully considered, so that a few latent variables after dimension reduction are better explained and described for the original variables, thereby improving the fault detection precision.

The invention discloses a line fault detecting system and method capable of achieving real-time interaction of three-phase data. The system comprises a plurality of groups of fault indicators mounted on three-phase lines and a master monitor station, and every group of fault indicators comprise three fault indicators which are mounted on the three phases of the three-phase lines respectively and communicated with one other synchronously; by means of the synchronous communication, the fault indicator on any phase of the three-phase lines can obtain the synchronous data of the corresponding two fault indicators on the other two phases at the same time and comprehensively determines whether the corresponding phase gets into fault through the synchronous data of the three-phase lines; the three-phase fault indicators are communicated with the master monitor station. The line fault detecting system and method capable of achieving the real-time interaction of the three-phase data has the advantages of improving the fault detecting accuracy, avoiding data transmission losses and being also applicable to the condition other expanding projects requiring the three-phase interaction data need performing on overhead lines.

The invention discloses a method and a device for detecting distribution line faults. A current transformer is sleeved on a distribution line B-phase so as to acquire a line current signal; a signal acquisition end of an electronic controller receives the line current signal from the current transformer; when a normal line current passes through the electronic controller for the first time or a line circuit is of a fault current and reaches the counting times set by the electronic controller, a control instruction output end of the electronic controller transmits corresponding control signals respectively; a GPRS (general packet radio service) communication module receives the control signals from the electronic controller; the line installing position and the information of the line state are transmitted to a cell phone terminal with an appointed receiving cell phone number through a GSM (global system for mobile) global digital mobile communication system, so as to realize the state monitoring for the distribution line by the cell phone terminal. With the adoption of the method and the device, a fault point can be found as early as possible, so as to find out the reason of the fault and further eliminate the fault; and the device and the method are high in detection precision and reliable in performance, and the detecting device is low in installation and maintenance costs under the condition that the safe and reliable operation of a power grid is ensured.

The invention discloses a smart home control system and method. The smart home control system comprises a monitoring host, a display screen is arranged on the monitoring host, a plurality of alarm indicating lamps are arranged on the top of the monitoring host, a signal transmission interface is formed in one side of the monitoring host, a control circuit board is arranged in an inner cavity of the monitoring host, and a microprocessor, a display module, an alarm module, an execution module, a signal acquisition and amplification module and a wireless transmission module are arranged on the control circuit board. The system is simple in structure principle and high in intelligent degree, intelligent monitoring and control over homes can be achieved, and an owner can know electricity utilization information, temperature and humidity information and air quality information in the family in real time.

The invention relates to a detecting method and device for electrical equipment fault, comprising the steps of performing interference detection for discrete data (i.e. detecting whether the default interference conditions are satisfied) to know whether the discrete data are interfered,updating the interfered discrete data in case of being interfered to ensure the accuracy of data, then undertaking the Fourier transform for discrete data to eliminate the interference component and obtain the fundamental wave component corresponded by the electrical parameter analog quantity, accurately calculating the effective value corresponded by electrical parameters according to the amplitude of fundamental wave component and obtaining the precise fault detection result according to accurate effective value, so as to improve the accuracy of fault detection,namely accurately judging whether the electrical equipment has faults and abnormalities. In case of faults, maintenance can be undertaken, so as to improve the safety of power grid operation.

The invention relates to the technical field of multi-modal industrial process fault detection, and discloses a multi-modal industrial process fault detection method of a weighted k-nearest neighbor standardized method. The detection method comprises a modelling stage and a detection stage; the modelling stage comprises the following steps: collecting normal data of different modals in the process, and serving the normal data as the integrity to form a training set X belonging to Rnxm. Through the multi-modal industrial process fault detection method of the weighted k-nearest neighbor standardized method, the information from the same modal can be intensified and the different modal information can be weakened in the application process of the WKNS method through the importing of a weightof the distance; and meanwhile, an operation of determining the nearest neighbor parameter k value according to the experience is avoided in the computation process, and the modal effect between different modals and stages is effectively eliminated; and the single-modal independent modelling and the model attributive division for the new testing sample are avoided by combining the WKNS-PCA method;and the traditional single-modal fault detection method is applied, a certain generalization capacity is provided, and the fault detection precision is improved.

The application discloses a high voltage interlock circuit and a detection method thereof. The circuit comprises: a first switching module; a second switching module, comprising a first driving unit and a first switching unit arranged in isolation, the first switching unit is arranged between a second power supply and a second power ground; a third switching module, comprising a second driving unit and a second switching unit arranged in isolation; a fourth switching module, arranged between the fourth power supply and the first power ground; a controller. The embodiments of the application improve the accuracy of fault detection.

The invention discloses an intelligent transformer station fault diagnosing method under the IEC61850 standard. The implementation steps of the invention comprise: obtaining the static state information of the intelligent transformer station through the function configuration model for the intelligent transformer station; obtaining the dynamic information of the intelligent transformer station through the messages of the intelligent transformer station; inputting the obtained static state information and the dynamic information to a well-trained fault diagnosing model based on a deep-learning network; outputting the fault diagnosing result for the intelligent transformer station; detecting the fault diagnosing result; if the fault diagnosing result shows that faults occur to the intelligent transformer station, then, according to the fault type classification, carrying out fault wave recording; and outputting control information to restore the fault state of the intelligent transformer station. The method of the invention has a strong learning ability, can achieve high and accurate fault detection, has a good anti-noise performance and can detect fault at a high pace, therefore, making it especially suitable for solving non-linear problems and greatly advantageous in mode identification and classification.

The invention discloses a fault detection method and device for a pressure wave sensor in a train, electronic equipment and a computer readable storage medium. The method comprises the steps: acquiring the speed of the train; judging whether the vehicle speed is less than a preset vehicle speed threshold; if yes, whether the vehicle speed is less than a preset shielding threshold value or not is judged; if the vehicle speed is less than the preset shielding threshold value, obtaining a pressure difference detection value of the pressure wave sensor, judging whether the pressure difference detection value or the change rate exceeds a preset range or not, and if yes, judging that the pressure wave sensor breaks down; if the train speed is not less than the preset shielding threshold value, judging whether the activation accumulated duration of the pressure wave train line activation signal of the train exceeds the preset duration or not: if yes, judging that the pressure wave sensor breaks down. The fault detection problem of the pressure wave sensor under the condition that the differential pressure detection value does not exceed the measuring range is effectively solved, the faultdetection accuracy of the pressure wave sensor is improved, and the train running safety is guaranteed.

A method to achieve the continuity check (CC), it is: sets the answer information that the maintenance end receiving the CC information needs to return CC, the maintenance end that processes the CC information bases on the network condition of the CC answer information. The invention can check out the connection fault in the network before or after that the maintenance end startup CC function; improve the veracity of the fault check, perfect the continuity check.

The failure detection device includes an accumulated data storage unit 30, a unit space generating module 13, a signal space generating module 14 and a determining module 16, wherein the unit space generating module 13 and the signal space generating module 14 use values as they are for condition sensor values defined as sensor values that affect other sensor values and sensor values that are not affected by the condition sensor values, and use values nondimensionalized by the condition sensor values or values adjusted by the condition sensor values for the other sensor values affected by the condition sensor values, and the determining module 16 compares a distance between the unit space and the signal space and determines presence / absence of a possibility of a failure.

The invention discloses a fault detection method and device, terminal equipment and a storage medium. The method is used for detecting a fault in a semiconductor wafer manufacturing process, and comprises the steps: obtaining monitoring signal data in a semiconductor wafer manufacturing process; performing feature extraction on the monitoring signal data to obtain a target general signal in the semiconductor wafer manufacturing process; and detecting whether a fault exists in the semiconductor wafer manufacturing process according to the target general signal. According to the method, full-automatic feature extraction of signal data collected in the semiconductor wafer manufacturing process can be achieved, dependence on expert experience in fault detection is reduced, key features of monitoring signal data in the semiconductor manufacturing process can be reserved through the extracted target summarized signal, and feature information is prevented from being lost, so that the fault detection precision in the semiconductor manufacturing process is improved.

The invention discloses a combine harvester operation state online monitoring system, comprising an upper computer with LabVIEW system, a torsion detection system, a speed detection system and a fault monitoring system; the upper computer comprises a central control unit connected respectively to a mobile communication module, an interrupt controller and a touch display screen; the interrupt controller is connected to a wireless router; the torsion detection system comprises a plurality of wireless torsion sensors and a first wireless data collector; the speed detection system comprises a plurality of angular displacement sensors and a second wireless data collector; the first and second wireless data collectors are in wireless communication respectively to the wireless router; the fault monitoring system comprises a plurality of cameras in wireless communication with the wireless router. The combine harvester operation state online monitoring system has the advantages of good wiring simplicity, good mounting convenience, high fault detection accuracy, good extensibility and the like.

The invention relates to a business data processing method and device, computer equipment and a storage medium. The business data processing method comprises the steps of obtaining business data of ato-be-detected service node, wherein the business data comprises first business data and second business data; performing fault detection on the to-be-detected service node according to the first business data and a database; when the to-be-detected service node is a fault node, determining a fault type corresponding to the fault node; identifying a corresponding standard service threshold in a database according to the second service data; comparing the second service data with a corresponding standard service threshold to obtain a comparison result; extracting historical fault nodes corresponding to the fault types from a database, and counting the number of the historical fault nodes; calculating according to the comparison result and the number of historical fault nodes to obtain updated data; and updating the corresponding standard service threshold in the database according to the updating data. By adopting the business data processing method, the fault detection accuracy of theservice node can be improved.

The invention provides a capacitive AC conducting and DC blocking-based DC bias isolation grounding device, which comprises a DC bias isolation system and a fault detection system, wherein the DC bias isolation system comprises a capacitor connected with a neutral point of an AC power transmission transformer in series, a high-speed vacuum circuit breaker, a zinc oxide nonlinear resistor voltage limiting protector assembly and an intelligent monitoring device for controlling the high-speed vacuum circuit breaker to run, wherein the high-speed vacuum circuit breaker and the zinc oxide nonlinear resistor voltage limiting protector assembly are connected with the capacitor in parallel; and the fault detection system is connected with the DC bias isolation system and is used for carrying out real-time fault monitoring on the DC bias isolation system. A DC bias function is achieved through the DC bias isolation system; and the corresponding fault detection system is arranged, so that health information of various devices in the DC bias isolation grounding device can be monitored in real time to be processed in real time when one device is broken down; the safety performance is high; and the construction cost is low.

A method for detecting a server fault includes: collecting sample monitoring data of a plurality of servers, the sample monitoring data signifying operating states of the plurality of servers; performing training, based on the sample monitoring data, to obtain a fault detection model for the plurality of servers; and collecting current monitoring data of a target server, and inputting the current monitoring data into the fault detection model to determine an operating fault corresponding to the current monitoring data.

The invention discloses a multi-redundancy inertial measurement data management method and system. The method comprises the following steps: acquiring multi-path IMU (Inertial Measurement Unit) data acquired by a plurality of IMU units; performing multi-dimensional fault evaluation on the multi-path IMU data to generate detection data; extracting optimal IMU data contained in the detection data; and taking the IMU unit corresponding to the optimal IMU data as a first IMU unit to be applied at the next moment. According to the method, combined voting scoring of the IMU data is performed through multi-dimensional fault assessment, so that the fault detection accuracy is effectively improved, and meanwhile, the trend of the IMU data with the highest combined voting score at the current moment is simulated; and the IMU data applied at the current moment is gradually corrected to be the same as the IMU data collected by the simulated first IMU unit at the next moment according to the linear or nonlinear adjustment rate, so that the problem that the motion stability of the device is seriously influenced due to the large switching amplitude of the IMU data to be applied is avoided.

The invention discloses a pipeline robot detecting device. The pipeline robot detecting device is characterized by structurally comprising a pipeline detecting regulating device, a camera, travellingdrivers, a detecting controller, a guide wire, and an electrifier, wherein the camera is embedded into the pipeline detecting regulating device; the two travelling drivers are mounted at the two sidesof the pipeline detecting regulating device; the detecting controller is electrically connected with the camera through the guide wire; the detecting controller is mounted on the inner part of the pipeline detecting regulating device; and the electrifier is mounted on the inner part of the pipeline detecting regulating device and is electrically connected with the pipeline detecting regulating device. Height of a camera mechanism is regulated, so that the camera mechanism is suitable for camera environment of pipelines with different pipe diameters, and a camera dead corner is avoided, and therefore, detection is more comprehensive; and moreover, the camera mechanism is expanded to expand the camera range, detail faults in the pipeline are precisely detected within the detection range, and fault detecting precision is improved.