65results about How to "Avoid sudden failure" patented technology

The invention discloses a cloud-edge cooperative amusement equipment fault prediction and health management system and method. The system comprises a distributed data acquisition system, edge computing equipment, a cloud computing platform and a management and control center. The data acquisition system distributed on the amusement equipment can acquire various heterogeneous state data including operation parameters, mechanical system parameters, hydraulic and pneumatic system parameters, electrical system parameters and the like in real time; and the edge computing equipment comprises an edgedata management functional module, a prediction service orchestrator functional module, an edge model training functional module, a fault early warning functional module and a communication service functional module, so the data caching capacity, the equipment health diagnosis capacity and the early warning capacity of an edge platform are achieved. The cloud computing platform comprises a data warehouse module, a model training module, a health management module and a communication service module, and achieves the data storage and model training capability of the cloud. The management and control center provides man-machine interaction, and is used for monitoring operation parameters and health conditions of the amusement equipment and receiving a fault prediction message.

The invention provides an analysis method for reliability of numerical control equipment based on a hidden Markov chain. The method particularly comprises the following steps: 1, monitoring dynamic performance signals of the numerical control equipment, and abstracting the performance characteristic parameter values showing the change of the reliability of the numerical control equipment; 2, constructing a predictive model of the performance characteristic parameter values; 3, using the predictive model to predict the performance characteristic parameter values within the time needed for vectorization, and adopting the source coding method to vectorize the predictive values of the performance characteristic parameter values; 4, adopting the discrete hidden Markov chain model to identify the state transition probability of the numerical control equipment; and 5, utilizing the Chapman-Kolmogorov differential equation to establish a relational expression of the operational state and the state transition probability so as to deduce the probability of the numerical control equipment in different operating states, namely obtaining the reliability of the numerical control equipment. The method can accurately analyze, evaluate and predict the change of the reliability of the numerical control equipment before the numerical control equipment goes wrong, thereby avoiding the fault of the numerical control equipment and improving the operational reliability of the numerical control equipment.

The invention relates to a method for detecting the insulation defect of a high-voltage cable accessory. In the method, hardware comprises a local discharge signal sensor, a local discharge signal acquisition unit and an industrial control computer, wherein the local discharge signal acquisition unit conditions and amplifies a signal acquired from a cable joint by the local discharge signal sensor, extracts a power frequency voltage signal and a local discharge signal and transmits the power frequency voltage signal and the local discharge signal to the industrial control computer through a universal serial bus (USB) communication interface; and the industrial control computer forms a local discharge spectrogram with reference to a power frequency voltage phase to obtain a characteristic parameter of the discharge spectrogram, compares the characteristic parameter with an insulation defect database and detects the existence of the insulation defect in the cable joint and the type of the defect. Compared with the prior art, the method has the advantages of preventing faults from occurring, enhancing the power supply reliability of a cable system and the like.

The invention discloses a transformer comprehensive monitoring system, which comprises a plurality of monitoring devices capable of rapid detection and fault positioning, external sensors of the monitoring devices, an outdoor cabinet body, a mobile wireless communication network and transformer internal insulation defect diagnosis system software. The transformer comprehensive monitoring system can improve the coping capability of a large-scale power transformer to more complicated operating conditions of an intelligent power grid in the future, and reduce the probability of occurrence of newhidden dangers, thereby improving the reliability of the entire power grid system; and the power transformer comprehensive monitoring system can perform rapid and effective evaluation on insulating states and service life of a large-scale power transformer, effectively instructs the operation and maintenance, reduces the workload of the operation and maintenance personnel, and decreases the operation and management costs.

The invention discloses a battery pack charge-discharge control circuit and an electrocar power battery system. The control circuit comprises a discharge switch circuit, a charge switch circuit, a first unidirectional control circuit and a second unidirectional control circuit, wherein the discharge switch circuit is conducted when the battery pack is in discharge and is turned off when the battery pack is in charge; the charge switch circuit is conducted when the battery pack is in charge and is turned off when the battery pack is in discharge; the control module is used for controlling the on-off states of the discharge switch circuit and the charge switch circuit; the first unidirectional control circuit is connected to the discharge switch circuit in parallel, and the direction of the electric current passing through the first unidirectional control circuit is reverse to the direction of the electric current passing through the discharge switch circuit; the second unidirectional control circuit is connected to the charge switch circuit in parallel, and the direction of the electric current passing through the second unidirectional control circuit is reverse to the direction of the electric current passing through the charge current circuit. According to the battery pack charge-discharge control circuit and the electrocar power battery system, multiple battery packs are included, the problems of self charge and self discharge of power batteries can be avoided, the decay rate of the power batteries is reduced, and the service life of the whole electrocar is improved.

A method for measuring the resistance component current included in the leakage current is provided. In a monitoring apparatus and system for measurement the signal waveform of at least one AC cycle is sampled. The resistance component leakage current is measured by dividing the average of integrated value of the instantaneous leakage current values and the instantaneous voltage values by the square root of average of squared instantaneous voltage values. In addition, a voltage signal of the target measurement circuit is obtained the waveform of the leakage current signal and the voltage signal for one cycle is sampled and stored; the leakage current signal and the voltage signal are expanded to N-th higher harmonic wave component respectively, and the resistance component that relates to the leakage current is calculated.

The invention discloses an optical power control circuit which comprises an APC (Automatic Power Control) loop and a microcontroller, wherein the APC loop comprises a semiconductor laser and an integral amplifier; the semiconductor laser is connected with a current induction circuit; and the microcontroller is used for monitoring the bias current through the current induction circuit and is used for adjusting the target power of the APC loop. The optical power control circuit has the beneficial effect that through monitoring the bias current and comparing with additional two threshold currents, when an MCU (Microprogrammed Control Unit) is used for adjusting the target power, the situations of overload and sudden shutdown of the laser are prevented, the damage of the semiconductor laser caused by overload and forced shutdown is avoided, and the sudden failure of a data chain using the laser caused by overload and sudden shutdown is also avoided.

The invention discloses a compressible device of a deep foundation pit horizontal inner support. The device is arranged in a deep foundation pit horizontal inner support structure and mainly consists of steel plates (3), vertical plates (2) and a steel pipe (1), wherein two steel plates (3) are provided and connected with the horizontal inner support structure respectively, the steel pipe (1) is arranged between the steel plates (3) and fixedly connected with the steel plates (3), and the vertical plates (2) are arranged at the two ends of the steel plates (3) and fixedly connected with the steel plates (3). When the static soil pressure acting on the support structure is excessively high, the support can generate a certain amount of compression through the compressible device, partial overload can be removed through compression displacement, and then the load acting on the support structure is reduced so as to provide a certain safety guarantee to a deep foundation pit support project, guarantee the stability of the support structure and avoid sudden failure of the support structure after exceeding ultimate bearing capacity. The device is simple in design and manufacturing and convenient to mount, and can realize constant load-compression within a certain range.

The invention discloses a system of processing transformer faults. The system of processing transformer faults includes a plurality of data monitoring nodes, a data acquisition unit, a data analysis unit, a fault diagnosis unit and a fault processing unit, wherein each data monitoring node includes a plurality of monitoring devices; each monitoring device is used for monitoring state parameters related to an operating state of the assigned transformer; the data acquisition unit is used to acquire all the state parameters related to the operating state of the assigned transformer; the data analysis unit is used to perform data analysis on all the state parameters of each transformer, and analyze the performance level of each state parameter; the fault diagnosis unit is used to determine theoperating standard of each state parameter, perform scoring on the performance level of each state parameter according to the operating standard of each state parameter, and determine whether the transformer has a fault and determine the fault type according to the score of at least one state parameter in all the state parameters; and the fault processing unit is used for reporting the identifierand fault type of the transformer to a remote monitoring center in the case of determining that the transformer has a fault.

The invention discloses an elevator safety maintenance method. The elevator safety maintenance method comprises the steps that (1) the initial sliding distance of an elevator is acquired in a self-learning mode; (2) the actual sliding distance of the elevator is detected regularly; (3) corresponding processing is conducted on the elevator according to the relation among the initial sliding distance, the actual sliding distance and the preset critical sliding distance. According to the elevator safety maintenance method, a testing method is simple, and data analysis is conveniently conducted; due to the fact that the working condition of the elevator is detected regularly, the problems of the elevator are discovered in advance, maintenance and repair are timely conducted on the elevator, and the hidden danger is prevented before happening. Compared with the phenomenon that in the prior art, the elevator is processed only when the elevator has a fault, the elevator safety maintenance method has higher safety and operability.

The invention discloses a steam turbine component health state assessment method based on ResNet, which comprises the following steps: carrying out a simulation experiment of a steam turbine component, and carrying out vibration data acquisition through a plurality of measuring points, wherein the vibration data comprises fault signal data and normal working condition data; carrying out label assignment on the fault signal data, wherein the label information comprises a fault type and residual available life; segmenting the fault signal data assigned by each label and carrying out normalization processing to obtain a sample set; dividing the sample set according to a preset proportion to obtain a training set and a verification set; training a pre-constructed ResNet-based multi-task learning neural network model through the training set by adopting a strategy of adaptively updating the network learning rate to reach a preset convergence condition, and obtaining a trained ResNet-based evaluation model; steam turbine part health state assessment is achieved through the assessment model. A multi-task learning mechanism is adopted, the fault type and the health degree of the steam turbine can be judged at the same time, and the accuracy is high.

The invention discloses a system of performing early warning on faults of transformers. The system includes a plurality of data monitoring nodes, a data acquisition unit, a data analysis unit, a faultdiagnosis unit and a fault early warning unit, wherein each data monitoring node includes a plurality of monitors and each monitor is used for monitoring the state parameters related with the operation state of an owned transformer; the data acquisition unit is used for acquiring all the state parameters related with the operation state of the owned transformer; the data analysis unit is used forperforming data analysis on all the state parameters of each transformer to determine the performance level of each state parameter; the fault diagnosis unit is used for determining the operation standard of each state parameter, performing scoring on the performance level of each state parameter according to the operation standard of each state parameter, and determining whether each transformerhas a fault and determining the fault type according to the scores of at least one state parameter of all the state parameters; and the fault early warning unit is used for reporting the identifier and the fault type of each transformer to a remote monitoring center when determining that the transformers have faults.

The invention discloses a fault early warning control method of an air conditioner and the air conditioner, relates to the technical field of the air conditioner, and aims to solve the problem that anair conditioner fault early warning method provided by the prior art cannot repair all faults of the air conditioner. The fault early warning control method comprises the steps of collecting operation parameters, judging whether the operation parameters are in a normal operation range of the air conditioner or not, and if the operation parameters are not in the normal operation range, judging whether a fault type causing a fault by the operation parameters is an I type of fault or a II type of fault; if I type of fault is about to occur, correcting the operation parameters according to a preset correction mode corresponding to the operation parameters which cause the I type of fault to occur, so that the operation parameters are in a normal operation range; and if II type of fault is about to occur, sending out early warning information and controlling a compressor of the air conditioner to operate according to the lowest operating frequency. The fault early warning method is used forair conditioner fault early warning.

The invention provides a high-toughness multiphase ceramic material as well as a preparation method and application thereof. The high-toughness multiphase ceramic material comprises rare earth zirconate and rare earth aluminate with high Curie temperature, the rare earth aluminate is distributed in the rare earth zirconate, and the Curie temperature of the rare earth aluminate is not lower than 1000 DEG C. The rare earth aluminate contains a plurality of randomly oriented ferroelastic domains, when the stress applied by the outside is higher than the coercive force, the C axis of the ferroelastic domains tends to turn to the direction parallel to the external stress or perpendicular to the crack propagation direction, and the ferroelastic domains can effectively consume the crack propagation energy during turning. According to the high-toughness multiphase ceramic material provided by the invention, the rare earth aluminate with high Curie temperature is introduced into the rare earthzirconate matrix as a toughening phase, so that the prepared ceramic material still has high fracture toughness and low thermal conductivity at a high temperature of 1000 DEG C or above, and has a very wide application prospect as a thermal barrier coating.

The invention relates to a walking aid with the function of gravity braking. The walking aid comprises a floor stand and a protective waistcoat with which a human body is wrapped. Idler wheels are installed on the lower portions of foot rods of the floor stand through castor assemblies with the function of braking, and the function of gravity braking is achieved under cooperation of electric control pin devices, a master control chip and the castor assemblies. The walking aid has the advantages of being capable of helping aged people in walking or exercising, will feel descending under gravityto start the function of braking when the body falls down under imbalance, and guarantees the safety of the aged people in walking or movement, and meanwhile the stability and popularization of the walking aid are improved.

The invention relates to an online state monitoring method for an on-load tap changer of a converter transformer. The online state monitoring method comprises the steps of: (1) acquiring vibration signals of a contact and a dialing piece by means of a vibration signal acquisition device during the shifting process of the on-load tap changer of the converter transformer; (2) performing denoising processing on the acquired vibration signals; (3) and comparing the denoised vibration signals of the on-load tap changer with vibration signals in a normal state, judging whether the on-load tap changer operates normally, and giving out anomaly prompting information if the on-load tap changer operates abnormally. The trial proves that, sudden failures can be effectively prevented and reduced after adopting the online state monitoring method provided by the invention, and the safe and reliable operation of the converter transformer can be further ensured.

The invention relates to a method for a testing personnel static grounding device with a near failure prompting function, which comprises the following steps of: inserting a test signal wire into a tester and connecting the test signal wire and a tested object; measuring a voltage of the tested object; performing an operation of the measured voltage and a reference value to obtain an actual voltage; performing an operation to generate a resistance value of the tested object; and comparing the resistance value with the set upper and lower limit resistance values of the tested object. If the resistance value is between the upper and lower limit resistance values of the tested object, a lamp of which the test result passes is on; if the resistance value is more than the upper limit resistancevalue or less than the lower limit resistance value of the tested object, a lamp of which the test result does not pass is on; and if the resistance value is near to the upper and lower limit resistance values of the tested object, within a permeable resistance value range and within a preset value range of the upper limit resistance value or the lower limit resistance value, a lamp of which thetest result is near failure is on. The testing device comprises a tester.

The invention discloses a testing method for on-line monitoring internal insulation incipient fault of electric equipment, wherein a sensing unit is employed for collecting collision high-frequency heavy current signal from power transmission bus wire and earthed sheathed tube port, the correlation between the waveform, amplitude and time of the collected shock transient signal is utilized to select the excitation signal and response signal of the power equipment transfer function and establish the internal transfer function curve of the power equipment.

The invention provides a big data based speed reducer linkage control system and method. A neural network monitoring unit based on big data training automatically identifies the working state of a speed reducer according to collected signals of vibration, noise and temperature change of the speed reducer, quantitative representation is formed, effective linkage control of the speed reducer, lubricating oil circulation equipment of the speed reducer and cooling equipment is achieved according to the quantitative representation of the working state, so that lubricating oil supply and circulationand the internal temperature adjustment of the speed reducer can be fully matched with the working state of the speed reducer.

The invention discloses a method and a device for analyzing the life of expressway electromechanical equipment, and relates to the technical field of computers. One specific implementation way of themethod comprises the following steps that: obtaining sample data, wherein the sample data comprises the operation state of the electromechanical equipment at each historical time point; according to the sample data, constructing the one-step transition probability matrix of the operation state of the electromechanical equipment; according to the one-step transition probability matrix, calculatingthe state limiting probability tendency of the operation state of the electromechanical equipment; according to the state limiting probability tendency, constructing the fault probability graph of theelectromechanical equipment; and analyzing the fault probability graph to obtain the service life of the electromechanical equipment. By use of the implementation way, the prediction accuracy of theactual life and the service life of the expressway electromechanical equipment can be improved, and the functions of preventing accidents, reducing fault losses and prolonging the life of the equipment can be performed for the maintenance and management work of the expressway electromechanical equipment.

The invention discloses a power grid panorama simulation system. A power grid panorama is simulated through a power grid primary simulation device and a power grid secondary simulation device; time setting of the system is realized through a time setting device which is separately connected with the power grid primary simulation device and the power grid secondary simulation device, so that time consistency of all devices is guaranteed; a data processing device which is separately connected with the power grid primary simulation device, the power grid secondary simulation device and the time setting device starts power grid panorama simulation after realizing system time setting; simulation data are processed to obtain a power grid panorama simulation effect. The overall operation condition of a power grid can be effectively analyzed, so that systematic overall prediction of the power grid is achieved, and the effect of preventing sudden faults of the power grid system is achieved. Theinvention also provides a power grid panorama simulation method which has the above beneficial effects.

The invention relates to the field of mechanical equipment after-sale maintenance, in particular to an air compressor fault remote processing method and system based on the internet of things. The aircompressor fault remote processing method mainly comprises the following steps that A, air compressors feed back work states to a server; B, the server stores the data fed back by the air compressorsand compares the date with preset safety numerical values preset in the server; C, a fault early warning signal is generated under the condition that a comparison result of the server shows that thedata exceed the preset safety numerical value, the fault early warning signal is pre-designed warning codes, the warning codes are used for storing and recording, and then the warning signals are converted by the server into character warning information corresponding to the codes; D, under the condition that the comparison result of the server shows that the data exceed the preset safety numerical value, the character warning information is sent to a bound mobile terminal, and if the comparison result of the server show that the data are normal, no character warning information is sent; E. online remote fault removal is conducted, wherein after an engineer is informed of the fault information codes online, the engineer makes a solution and conducts remote guidance or makes full preparation and then goes to the site to conduct maintenance.

The invention discloses an equipment remote predictive maintenance system and method based on an internet mode. The system comprises a data acquisition module, a database management module and a prediction maintenance module, wherein the data acquisition module is connected with the microelectronic manufacturing equipment and is used for acquiring running state information of the microelectronic manufacturing equipment in real time; the database management module is connected with the data acquisition module and is used for receiving and storing the running state information; and the prediction and maintenance module is connected with the database management module and is used for extracting the running state information stored in the database management module and carrying out state trend prediction, residual life prediction and maintenance scheme determination on the microelectronic manufacturing equipment according to the extracted running state information. According to the remote predictive equipment maintenance system and method based on the internet mode, predictive maintenance analysis of the microelectronic manufacturing equipment can be realized, early symptoms of faults can be identified in advance, sudden faults can be avoided, the safety and reliability of the microelectronic manufacturing equipment can be improved, and the maintenance cost can be reduced.

A method of fabricating a semiconductor laser device by forming a semiconductor structure at least part of which is in the form of a mesa structure having a flat top. The steps include depositing a passivation layer over the mesa structure, forming a contact opening in the passivation layer on the flat top of the mesa structure; and depositing a metal contact portion, with the deposited metal contact portion contacting the semiconductor structure via the contact opening. The contact opening formed through the passivation layer has a smaller area than the flat top of the mesa structure to allow for wider tolerances in alignment accuracy. The metal contact portion comprises a platinum layer between one or more gold layers to provide an effective barrier against Au diffusion into the semiconductor material.

The invention belongs to the technical field of locomotive working condition monitoring and fault diagnosis, and particularly relates to a motor train unit transmission system fault prediction and health management device and a use method thereof. The device comprises a bridge processor, a ground fault diagnosis predictor and a train-mounted diagnosis server which are interconnected through a train bus, and a data acquisition preprocessor which is connected to the corresponding vehicle-mounted diagnosis server through a gigabit Ethernet; a data processing unit is arranged in each unit; and particularly, a metabolism grey-particle filtering combined prediction model is adopted for predicting the service life of the motor bearing, so that the residual service life of the motor bearing can be accurately predicted. According to the device, real-time fault monitoring of the motor train unit transmission system is guaranteed, and health management data of the motor train unit transmission system is efficiently provided. According to the method, faults of the motor train unit are alarmed in advance or in time, repair or replacement of the bearing before the maximum use time limit is achieved, unnecessary overhaul is reduced, and cost is saved. The driving safety can be guaranteed, and the use efficiency of key components is improved.

The invention discloses a lanthanum zirconate multiphase ceramic, and a preparation method and applications thereof. The lanthanum zirconate multiphase ceramic comprises lanthanum zirconate and lanthanum aluminate, and lanthanum aluminate is dispersively distributed into lanthanum zirconate. The preparation method comprises the following steps: sintering lanthanum zirconate and lanthanum aluminate mixed powder through discharge plasma, to obtain the lanthanum zirconate multiphase ceramic. The lanthanum zirconate is toughened by lanthanum aluminate in a ferroelastic toughening manner, therefore, the lanthanum zirconate multiphase ceramic has the advantages of being high in fracture toughness, high in density, good in chemical stability and volume stability, and the like, and has wide application prospects in the application field of high-temperature thermal barrier coatings.

The invention relates to a method for measuring the partial discharge of a joint with an insulation defect, which comprises the following steps of: 1) connecting water pipes with the two ends of the joint with the insulation defect and arranging water terminal equipment at the tail end of each water pipe; 2) arranging a signal leading-out wire on the joint with the insulation defect; 3) applying power frequency high voltage to the water terminal equipment on the two sides, and acquiring a partial discharge signal by using a signal sensor; and 4) outputting the partial discharge signal through the signal leading-out wire. Compared with the prior art, the method has the advantages of effectively judging the insulation condition, preventing the sudden failure of cable equipment, and improving the power supply reliability of a cable system.

The monitoring method includes: preparing standard criteria for determining operating condition of mechanical equipment, sampling, making spectra and determining operating condition of equipment. The method tests sampled lubricating oil of mechanical equipment regularly, analyzing indexes of physics and chemistry, analyzing microscopic ferromagnetic grinding dust quantificationally and in qualitative. Based on statistical result, standard criteria for operating condition of equipment are prepared. Whether operating condition of equipment is normal or not is determined by comparing the condition with standard criteria. If there is abnormity, corresponding inspection or repairing can be arranged in order to prevent paroxysmal failure, reducing chain reaction of damaging parts and loss of stopping operation.

The invention discloses a ResNet-based method for assessing the health status of steam turbine components, which includes: performing a simulation experiment on steam turbine components, and collecting vibration data through multiple measuring points; the vibration data includes fault signal data and normal working condition data; the fault signal The data is tagged; the tag information includes the fault type and remaining usable life; the fault signal data after each tag assignment is segmented and normalized to obtain a sample set; the sample set is divided according to a preset ratio to obtain a training set and verification Set; adopt the strategy of adaptively updating the network learning rate, train the pre-built multi-task learning neural network model based on ResNet through the training set, and obtain the trained evaluation model based on ResNet to the preset convergence condition; realize the steam turbine through the evaluation model Component health assessment. The invention adopts a multi-task learning mechanism, can simultaneously judge the fault type and the health degree of the steam turbine, and has high accuracy.

The invention discloses a rolling bearing residual life prediction method based on LSTM and TDNN, and the method comprises the steps: (1) extracting the time domain features of an original vibration signal of a training bearing, forming a time domain feature set, and carrying out the minimum-maximum normalization processing of each feature; (2) constructing a health factor by using at least two nonlinear functions, then constructing a mapping relation between training features and the health factor and a mapping relation between the health factor and the residual life percentage by using LSTM and TDNN in sequence, and constructing an LSTM-TDNN residual life prediction model; and (3) inputting test bearing vibration data, after feature extraction and normalization processing, obtaining a residual life estimation value according to the LSTM-TDNN prediction model, and giving out comprehensive evaluation of prediction accuracy. The rolling bearing residual life prediction result is more accurate, unification of high precision and strong conservative is achieved, the method can be effectively applied to rolling prediction maintenance tasks, and the maintenance cost is reduced.