135 results about "Fault grading" patented technology

In the present invention, after fault information analysis, fault cause judgement, giving treating opinion and predicting stop time, the fault cause and treating opinino are transmitted to single-machine controller to direct the operator's job while the influence of the fault on the machine group engineering is judged based on the weight value of the fault part in the machine, the weight value ofthe fault machine in the machine group and fault grade and the fault information is transmitted to the group dispatching system. Each single machine is equipped with intelligent monitoring and diagnosis subsystem connected to movable communication module; the machine group is equipped with high-level monitoring and diagnosis system connected to movable communication module.

The invention discloses a finished vehicle control method and a finished vehicle control system suitable for a pure electric vehicle. The state of a finished vehicle is subjected to fault grading through software, a special processing mode is set for each grade, and the pure electric vehicle is integrally controlled, so that the finished vehicle can be scientifically and sequentially controlled and managed, and the conservation and control of resources are facilitated; according to hardware, three mutually-independent controller area network (CAN) buses are connected with a motor controller, an energy storage controller and an instrument panel respectively, so that data transmission cannot be influenced mutually; and a transmission speed is increased, so that the control response of the finished vehicle is quick and accurate.

The invention discloses a train bogie bearing service process monitoring and fault diagnosis system and method. The system comprises vibration sensors, a collecting board card, an AD chip, a digital signal processing board card and a diagnosis service mainframe, the digital signal processing board card is of a double-processor architecture with a DSP (digital signal processor) and an FPGA (field programmable gate array), the vibration sensors are arranged on an axle end cap of a train, and each bogie is provided with four vibration sensors. The vibration sensors collect vibration signals of a bogie bearing, analog signals are acquired through the collecting board card integrating amplifying and filtering functions, digital signals are acquired after the AD chip samples the analog signals and then input into the FPGA of the digital signal processing board card, and the FPGA primarily preprocesses the collected digital signals, inputs the same into the DSP to complete preprocessing and sends results to the diagnosis service mainframe for analyzing, fault diagnosis and fault grading. The train bogie bearing service process monitoring and fault diagnosis system and method has the advantages of low cost, high engineering implementation performance and capability of realizing online realtime monitoring.

The invention provides a wind power generator blade edge breakage monitoring device. Conductive medium is filled in wind power generator blades or adhered to the surfaces of the same according to different blade edge breakage grade spacing; the conductive medium forms a conductive loop between an entrance end A and an exit end B; and the conductive medium is connected with an on-off detector. According to the on and the off states of the conductive medium of different blade edge breakage grade lines, the potential fault grading alarm is realized. Compared with the prior device for artificially monitoring the wind power generator blade edge breakage, the wind power generator blade edge breakage monitoring device has high reliability and relatively lower monitoring cost, is simple and practical, can ensure that a wind power station proprietor can accurately know the breakage of all the edges of a wind power generator in time due to the installation of a blade monitoring system, provides a reliable basis for designing a truthful strong wind and typhoon resistance scheme and reduces the generated power energy loss resulted from wind power generator blade edge breakage.

The invention relates to a precaution and alarming hardware device for combined harvester plugging fault when in harvesting, belonging to the technical field of the agricultural machinery electronic equipment and comprising the following components: a sensor module, an analog signal processing module, a signal converting module, a power supply module, a singlechip central information processing unit module, a liquid crystal display (LCD) module, a tri-color LED fault grading display, and an upper computer communication module. The device provided in the invention can be assembled into the cab of the combined harvester, so when in harvesting, the device can perform real-time precaution and alarming on a threshing cylinder and a grain-delivering auger parts, and promptly provide state information of the harvester for the driver to prevent plugging fault from occurring.

The invention discloses an automatic fault protection method for a bulldozer, which comprises the followings: acquiring operational parameters of the bulldozer in real time; making a comparison between the operational parameters and a pre-set value, judging whether the operational parameters meet the pre-set value or not, if not, making a comparison between the operational parameters and date stored in a fault database, and determining corresponding fault grades and fault codes; generating corresponding control signals to control an engine according to fault grades. The invention further discloses an automatic fault protection system for the bulldozer. According to the invention, in the case of faults on the bulldozer, the fault grades can be determined according to the data stored in the fault database, and corresponding control to the engine can be performed according to corresponding fault grades. Therefore, automatic protection to the bulldozer can be achieved.

The invention provides a health state diagnosis early-warning circuit and method of an electric automobile high-voltage system. The circuit comprises an insulation resistance detection module, a connecting resistance detection module, a battery management module, a motor control module, a pre-charging monitoring module, a relay monitoring module and a control computing module. The modules are used for detecting an insulation resistance value between a serial-connection battery pack of an electric automobile and an automobile body, a connecting resistance value of a high-voltage circuit, the health state, voltage and current of the serial-connection battery pack, a fault grade of a driving motor system, voltage and current of the direct-current input end of the driving motor system, a fault grade of a pre-charging circuit and a fault grade of a relay on line. Quantified comprehensive representation and on-line recognition are achieved for the health state of the high-voltage system, and therefore high-voltage safe management is performed on the safety state of the electric automobile high-voltage system more scientifically and reasonably.

The invention provides a vehicle fault processing method and device and an electric vehicle. The vehicle fault processing method comprises the steps of determining a fault grade of the vehicle and a fault processing strategy corresponding to the fault grade according to a target fault of the vehicle, wherein different fault grades correspond to different fault processing strategies; and transmitting first indication information to a user, wherein the first indication information is used for indicating the fault processing strategy corresponding to the fault grade of the vehicle. According to the embodiment of the invention, the different fault processing strategies are indicated for the user according to different fault grades so that the fault processing efficiency is enhanced; and furthermore, a function of intelligently prompting the fault processing strategies is increased for the vehicle, market problem treatment is made more convenient, the user satisfaction degree is increased,and the occurrence probability of traffic accidents is reduced.

The invention discloses a fault diagnosis method of a motor bearing based on a time-frequency domain statistical characteristic. The fault diagnosis method comprises the following steps that: speed pulse signals and vibration signals of the motor bearing in T time interval are collected simultaneously, and a frequency conversion curve f is calculated according to the speed pulse signals; the vibration signals at a stationary speed are intercepted according to the frequency conversion curve and are sectioned; health indicators of the vibration signals in all segments are calculated according toa formula of the health indicators, a fault degree grade of each segment is obtained by comparing the health indicators with a fault threshold table, and the fault grade with the highest fault degreegrades counted is the fault grade of the motor bearing; Hilbert envelope spectrums of the vibration signals in all segments are calculated, effective frequencies of all envelope spectrums are determined according to a calculation method of the effective frequencies, the most frequent occurrence frequency of the effective frequencies counted is a fault frequency, and then a fault position of the bearing is determined. The overall fault degree and the fault position of the motor bearing are accurately obtained by counting the fault grade of the vibration signals and the effective frequencies ofthe envelope spectrums in a plurality of time intervals.

An electric automobile fault handling method comprises the steps of enabling a motor system monitor to monitor running of a motor system according to preset frequency, obtain a running state of the motor system, and send corresponding running state signals to a full automobile controller according to the running state of the motor system; enabling an energy storage system monitor to monitor running of an energy storage system according to preset frequency, obtain a running state of the energy storage system and send corresponding running state signals to the full automobile controller according to the running state of the energy storage system; enabling the full automobile controller to receive the running state signals of both the motor system and the energy storage system, analyze the received running state signals, search fault grades corresponding to the running state signals and send running instructions to the motor system according to the fault grades; and enabling the motor system to run according to the running instructions. In addition, an electric automobile fault handling system is further provided. According to the electric automobile fault handling method and system, the faults of the motor system and the energy storage system can be detected timely, and the electric automobile is controlled to run according to the fault grades.

The invention provides an abnormality management system of an autonomous vehicle and an abnormality handling method of the autonomous vehicle and belongs to the field of automatic driving. By the adoption of an existing automatic driving technology, the abnormality handling capacity is poor. An abnormality detecting module conducts statistics and collection of fault information generated by each subsystem in an automatic driving system and stores the fault information; a fault triggering module conducts concentrated judgment on the fault information collected by the abnormality detecting module, obtains fault grades of the fault information and sends the fault grades to the fault processing module; the fault processing module sorts the received fault grade information according to the fault grades from low to high and then processes the faults according to the fault grades from high to low, and whether the current fault is bypassed or not is judged; a data management module backups data after fault is triggered when abnormality happens. The abnormality management system of the autonomous vehicle and the abnormality handling method of the autonomous vehicle can rapidly find surrounding abnormal conditions and rapidly handle the abnormal conditions.

The invention provides a multi-source data fusion-based automatic identification method of a power network fault grade, and belongs to the technical field of power distribution automation systems. A main-network model and main-network fault monitoring and loss load quantity calculation results provided by an EMS system, a basic distribution network model provided by a GIS system and SCADA data anddistribution network fault monitoring and diagnosis results provided by a power distribution automation system are fully applied, load attribute information inserted by a marketing and distribution integration platform and the like and measurement data are combined, corresponding rules of an accident grading library are matched on the basis of provision of basic data through analyzing a loss loadquantity and user impact situations of a fault event, automatic identification on the power network fault grade and process tracking and early-warning are realized, and a reference basis is providedfor starting emergency response or a predetermined scheme of the corresponding grade by an emergency-response command institution.

The embodiment of the invention discloses a real-time fault diagnosis method and device. The method comprises the steps that an operating signal of a controller of a terminal to be diagnosed is acquired in an A / D acquisition mode, and a fault signal of a motor control system of the terminal to be diagnosed and a fault signal of a battery control system of the terminal to be diagnosed are acquired through a CAN bus; the adjusted operating signal, the fault signal of the motor control system and the fault signal of the battery control system are subjected to fault grading processing; the fault state of each diagnosis event is updated according to the fault grading processing result, fault information of the diagnosis events is stored in a fault storage module after the terminal to be diagnosed is powered off, and the fault information of the diagnosis events comprises fault codes and fault state information. Therefore, a self-diagnosis function, namely, a car-mounted diagnosis function, is set in an automobile control system; real-time diagnosis is carried out through diagnosis equipment in a car, and the diagnosis information is stored in a memorizer in the form of the fault codes.

A double-motor torque distribution control method for a rubber wheel low-floor intelligent rail train comprises the steps that firstly, a program starts to run after a power-on self-test is carried out; secondly, pedal and gear information of a driver at a driving end is collected, information of a double-motor controller, management of batteries and an auxiliary system is collected through a CAN, the state and the working mode of the current train are subjected to logical judgment, and whether a fault exists or not is judged according to states of all system components, and the fault grade of the fault is judged; thirdly, according to features of two motors, features of the batteries, and the state of a pedal, the target torque and a working mode of the given motor are calculated through a motor control module, and limit torque is output according to the fault grade of the train; fourthly, the limit torque is output to the two motors to carry out torque output, in other words, a whole-train controller finally outputs the motor target torque to the double-motor controller, and the motor torque output is subjected to average distribution. The double-motor torque distribution control method has the advantages that the principle is simple, reliability is high, and the whole-train control performance can be optimized.

The invention relates to an elevator lift car illumination diagnosis device, which comprises a camera (106), a detecting device (108), a storage device (112), a control device (110) and a communication device (114), wherein the camera (106) shoots the inside of a lift car (102) provided with an illuminating device (104), the detecting device (108) detects the brightness of an image shot by the camera, the storage device (112) stores detecting conditions and an initial brightness value, the control device (10) is used for comparing the brightness value detected by the detecting device with the initial brightness value, carrying out diagnosis on the illumination of the lift car on the basis of a comparison result and uploading the image shot by the camera into the control device (110) arranged in a server (120) connected with a network, and the communication device (114) is communicated with an external terminal. When the brightness difference is greater than a designated value, the control device determines the illumination fault grade on the basis of phenomenon occurrence frequency, and the communication device notifies a portable terminal of maintenance personnel of the fault grade and points to the interlinkage of the server. Therefore maintenance personnel can observe the condition inside the lift car on line in time and can take corresponding measures.

The invention provides a method for recording and selecting fault information of rail transit vehicle air conditioning equipment, and relates to the technical field of the rail transit vehicle air conditioning equipment, in particular to a method for recording operating information generated before and after air conditioning faults. An air conditioning controller records the air conditioning operating information, a computer is connected with the air conditioning controller, information interaction and data transmission are achieved, and the air conditioning controller is provided with a memorizer for storing the air conditioning operating information. The method for recording and selecting the fault information includes the following steps that after the air conditioning equipment is started, the air conditioning controller acquires air conditioning operating states at a time every N seconds and records the air conditioning operating states in the memorizer; when an air conditioner breaks down, the air conditioning controller records the fault information in the memorizer, and the fault information comprises fault names, occurrence time and fault grades; when the computer is connected with the air conditioning controller, the computer reads the information in the memorizer, the position of the fault information is found, the fault information is preserved, and the M air conditioning operating states generated before and after the fault information are selected and preserved.

The invention discloses an infrared monitoring early warning system for a belt conveyer key part. According to the system, an infrared thermal imaging instrument is utilized to acquire infrared images of a motor, a carrying roller and a roller of a belt conveyer, through pretreatment, image segmentation, characteristic extraction and classification of the infrared images, automatic identification of the motor, the carrying roller and the roller is realized, according to the identified part types, a temperature rising fault grade is determined, and fault early warning is carried out. The system integrates the infrared thermal imaging technology and the computer image identification technology, monitoring and early warning of the key part of the belt conveyer based on infrared thermal imaging are realized, and great importance on safe operation of the belt conveyer is realized. The system has advantages of excellent interactivity and operability, strong practicality and high popularization and application values.

The invention relates to a large-scale carrying belt tearing fault intelligent detection method based on dynamic images, which comprises the following steps: step 1, determining a mounting position ofan intelligent high-speed industrial camera for a large-scale carrying belt transportation system; step 2, preprocessing a belt operation image collected by the camera; step 3, segmenting the belt tearing image; step 4, extracting characteristic parameters of the belt tearing image; step 5, calculating the connected domain area of the belt tearing image, performing fault grade division accordingto the belt tearing area of the industrial site, obtaining the belt tearing threshold value, and when the corresponding actual tearing area of the carrying belt is yes, judging a second-level fault; and when the actual tearing area of the corresponding carrying belt is greater than the actual tearing area, judging as a first-stage fault; and determining the tearing area and the tearing fault levelof the belt. Compared with the prior art, the method has the advantages of high detection precision, high real-time performance, no need of manual intervention and the like.

The invention discloses an airplane autonomous guarantee system and method based on the internet of things. The system comprises a PHM subsystem, an airplane information integrated management subsystem and an airplane ground comprehensive health management subsystem. The method includes the following steps that 1, by means of information interaction of the PHM subsystem and the airplane information integrated management subsystem, airplane parameters and fault diagnosis results are transmitted; 2, the airplane ground comprehensive health management subsystem conducts performance degradation trend analysis on key equipment of an airplane, and early prediction and diagnosis of potential faults are achieved; 3, the airplane information integrated management subsystem analyzes transmission data information, a fault grade and a fault solution are determined, corresponding army maintenance staff, other guarantee staff and maintenance equipment are reasonably scheduled and allocated, and maintenance conditions of the airplane are monitored in the whole process. Conversion from planned maintenance to condition maintenance in airplane maintenance guarantee is achieved, and the system and method play an important role in guaranteeing safe flight of the airplane, improving maintainability, increasing the task success rate, improving use efficiency and the like.

The invention relates to a system and a method for offline secondary detection and checking of machine detected data of a large-piece checker. The system comprises a central database, an image server, a secondary checking working station, a small-piece checking manual waste determination system, a display master station and a detection slave station, wherein the detection slave station comprises a front-face detection slave station and a back-face detection slave station; the secondary checking working station is used for receiving defect information and a defect image which are sent by the display master station, performing fault grading on the defect information and the defect image and sending a fault grading result into the display master station; the display master station is used for uploading the received information and the fault grading result; and the small-piece checking manual waste determination system is used for downloading the fault grading result and the defect image,performing comparative analysis to output a manual waste determination result and uploading the manual waste determination result to the central database for export and use. By the system and the method, the technical problem of a large number of mistakenly wasted pieces of the conventional Renminbi large-piece product quality detection system is solved; and the system and the method have the advantages of simplifying production processes, increasing checking speed and saving production resources.

The invention discloses a power distribution network fault prediction method. The method comprises: 1, data acquisition and preprocessing; 2, characteristic variable selection; 3, building of a powerdistribution network fault prediction model based on fault grading; according to the invention, the optimized data acts on the establishment of the accurate power distribution network fault predictionmodel; accurate prediction of the power distribution network fault is achieved, the problems that in power distribution network fault prediction, data is difficult to refine and extract, and prediction model parameters are difficult to select are solved, a basis is provided for power grid workers to respond to the power distribution network fault in time, and the stability and reliability of a whole power system are improved.

The present invention discloses a fault grading-based fault warning method and device and equipment. The method includes: obtaining a current to-be-checked parameter of to-be-checked equipment; determining a fault early warning level corresponding to the current to-be-checked parameter according to a grading early warning rule; and outputting the early warning information corresponding to the fault early warning level. According to the present invention, different fault early warning levels are divided based on the grading early warning rule, the fault early warning level corresponding to theequipment is determined by a specific parameter of the equipment and corresponding early warning information is output. Therefore, the fault early warning can be issued in advance, so that the user understands the operation state of the equipment or the system, thereby remedial measures can be taken in time before a fault occurs or when a serious fault does not occur, to prevent greater losses andimprove system stability.

The invention discloses a takeover method and a takeover device for intelligent automobile, and a storage medium, and belongs to the technical field of intelligent automobiles. The method comprises the steps of: detecting a driving domain of an intelligent automobile and the state of an automatic driving system; when the driving domain of the intelligent automobile is detected to be in the operation domain of the automatic driving system, and when the automatic driving system fails, controlling the intelligent automobile to drive according to a first deceleration speed if the automatic drivingsystem fault grade is a first fault grade; controlling the intelligent automobile to enter a degraded operation mode if the automatic driving system fault grade is a second fault grade; when the driving domain of the intelligent automobile is detected to exceed the operation domain of the automatic driving system, and when the automatic driving system fails, controlling the intelligent automobileto stop in a first parking duration if the automatic driving system fault grade is the first fault grade; and controlling the intelligent automobile to drive according to the second deceleration speed if the automatic driving system fault grade is the second fault grade.

The invention discloses a fault-tolerant method aiming at TSV (Through Silicon Via) fault grading in 3D NoC (Network on Chip). According to the method, TSVs and data bits are respectively divided into four groups; if a TSV fault state value is within 6, the serial transmission among the groups and among data bits in the groups can be realized by using rest available TSVs; and otherwise, a localized fault-tolerant routing algorithm is used, and the address of the optimum TSV is found out from a locally stored TSV state table and is used as a temporary target address to be added to a data packet header for completing interlayer communication. According to the scheme of the method provided by the invention, the corresponding fault-tolerant method is selected through judging the fault grade of TSV links; higher reliability of the system is ensured; and meanwhile, the waste of available resources is reduced.

The invention provides a server error diagnosis method based on supervised learning, comprising the following steps of collecting server fault information and classifying the fault information; digitalizing the fault information of each type according to the fault condition and fault grade; dividing the digitized information into training set and test set; training a training model constructed bya plurality of algorithms based on the training set, and testing the trained model based on the test set to select the model with the highest precision; and predicting a failure level corresponding tothe new server failure information through the selected model. The invention realizes the complete automatic analysis and fault grade prediction, and reduces the time cost of manually monitoring theserver fault.

The invention discloses an infrared image-based photovoltaic array fault grading method. According to the infrared image-based photovoltaic array fault grading method, infrared image information of a photovoltaic array system is collected; the infrared image information comprises a plurality of infrared images of a photovoltaic module; each image is divided into a plurality of image units; R, G and B values of each unit form an image information database tensor; fault coding is carried out on the infrared images according to obtained temperature information of the photovoltaic module; a fault grade vector is predicted through the image information database tensor by a Tensor-V hybrid partial least square method, so that a tensor-vector fault grading model is built, and has high predictive ability; rapid and effective fault grade coding on the infrared images of the photovoltaic module can be achieved; and the rapid and effective fault grade coding is supplied to photovoltaic power station operation and maintenance workers to arrange maintenance and replacement for the faulty photovoltaic module, so that an operation of the photovoltaic module in a constant optimum state is achieved; and economic benefits of a photovoltaic power plant are ensured.

The invention discloses a frequency conversion equipment operation fault monitoring system based on big data, which belongs to the field of electromechanical equipment, and is used for solving the problems that a fault during operation of frequency conversion equipment cannot be known in time and the frequency conversion equipment cannot judge whether the fault occurs or not by autonomously depending on operation data. The system comprises a fault division module, a fault judgment module and a data analysis module, wherein the data analysis module is used for carrying out data analysis on real-time operation data of the frequency conversion equipment, and the fault judgment module receives a stress value and a relaxation value of the frequency conversion equipment sent by the data analysis module and is then used for carrying out fault judgment on the operation information of the frequency conversion equipment in unit time, and the fault division module is used for carrying out fault grade division on the fault condition of the frequency conversion equipment after receiving a fault signal sent by the server. The failure condition of the frequency conversion equipment is known in time, and whether the frequency conversion equipment breaks down or not is intelligently judged through the real-time operation data.

The invention provides a mower, which comprises a battery system, a walking system and a cutter system. The mower also comprises a fault detection module, wherein the fault detection module is used for respectively detecting whether the battery system, the walking system and the cutter system of the mower have faults or not; a fault judging module used for judging the grade of a detected fault; acontrol module used for controlling the current limit or power-off of the corresponding battery system, the speed reducing or stopping of the walking system and the speed reducing or stopping of the cutter system according to the fault grade; compared with the prior art, the mower has the advantages that the fault detection is more intelligent, the working state of the mower can be adjusted in real time according to the fault grade, and the working efficiency is improved.

The invention provides a representation method for describing an old fault top surface structure diagram. The representation method for describing the old fault top surface structure diagram comprises the steps that 1, the top surface of an eroded and lifted stratum is interpreted according to logging information of a drilled well; 2, fault interpretation is performed in a seismic section, and fault combination is performed on a plane after the interpretation on the seismic section is completed; 3, fault classification is performed according to the fault displacement existing situations of faults on a top interface, and fault grading is conducted on the faults according to the fault displacement amounts and the lengths of the faults. By means of the representation method for describing the old fault top surface structure diagram, the problem of representation of blind faults on the top surface structure diagram is effectively solved. The representation method has the great significance on oil-gas exploration work of a front tertiary stratum, is simple, clear and good in operability and has very good practicability in structure diagram drawing.

The invention discloses an intelligent air-conditioner fault reminding system and a reminding method for automobiles, and belongs to the technical field of automobile manufacturing. The system comprises a fault information acquisition module, wherein the fault information acquisition module is connected with a plurality of sensors and a plurality of executors, the fault information acquisition module is connected with a fault grade classification module through a fault code storage module, and the fault grade classification module is connected with a meter; a CAN bus connected with the fault code storage module is provided with the diagnosis interface which is connected with a diagnosis instrument in an insertion manner. The method comprises the following steps: acquiring voltage signals of the sensors and the executors by the fault information acquisition module in real time; analyzing and judging the voltage signals and distributing the voltage signals to the fault grade classification module through the fault code storage module and then performing classification and displaying on the meter; reading and displaying fault information on the fault code storage module through the diagnosis instrument for car repairing. According to the intelligent air-conditioner fault reminding system and the reminding method for automobiles disclosed by the invention, the problem that minor faults of an existing automotive intelligent air-conditioner are difficult to be found out, severe faults cannot be found out in time and fault sources are difficult to search can be solved.