344results about How to "Monitor running status" patented technology

The invention belong to the technical fields of low-voltage power distribution and power electronics, and relates to a battery charging and replacing station for electric vehicles. In the battery charging and replacing station for the electric vehicles, battery replacement and separated-box charging take the priority and entire vehicle charging takes the secondary. The battery charging and replacing station can satisfy the requirement of replenishing electric energy for large-size commercial vehicles and small-size passenger vehicles. In addition, a warehousing type automatic battery replacing system is adopted so that the functions of automatic battery replacement and automatic warehousing in/out management are achieved, and a separated-box charging system can be used for charging the batteries.

The invention provides a rotating machinery fault diagnosis and state monitoring system and method based on deep learning. The system includes a shell, a loudspeaker, a display, a storage, central processing unit (CPU) and a data acquisition device, an integrated deep learning device, a historical signal database, a fault category expert system library and the data acquisition device are arrangedinside the shell, a middle position of an upper end part of the shell is provided with a signal transceiver, the right side is provided with the loudspeaker, the display is arranged under the signal transceiver, a USB interface is arranged under the display at the left side, the storage is arranged under the USB interface, the CPU is arranged under the storage, a graphics processing unit (GPU) isarranged under the CPU, a data interface is arranged under the GPU, and all components in the shell are connected together through leads to form an access. The rotating machinery fault diagnosis and state monitoring system based on deep learning is more accurate and convenient in fault diagnosis and state online monitoring of rotating machinery.

The invention discloses an abnormal vibration analysis-based GIS (gas insulated switchgear) mechanical fault diagnosis method and system. The GIS (gas insulated switchgear) mechanical fault diagnosis method includes the following steps that: vibration signals on a GIS are acquired; de-noising processing is performed on the acquired signals through using a threshold de-noising method; various kinds of feature information contained in the signals are extracted by using a narrowband noise aided multivariate empirical mode decomposition (EMD) method; the power feature of the signals is extracted by using a power density function, and the maximal amplitudes of the power spectra of all IMF of each channel are calculated so as to form power feature matrixes under measured conditions; and a power feature matrix under a normal condition and/or power feature matrixes under various kinds of fault conditions which are obtained through tests are adopted as judgment criteria of faults. Compared with a traditional method, the method and system of the invention have no influence on the normal operation of a whole power system, and can monitor the running state of the GIS safely and reliably, and are suitable for being applied to GIS substations of various voltage levels.

The invention discloses a chain state monitoring and protecting system for a scraper conveyor. The system is characterized by comprising a micro controller unit, a wireless measuring unit, an AC (Alternating Current) sampling unit, an analog quantity conditioning unit, a display unit, a communication unit, a keying unit, a switching value unit and a driving unit. According to the invention, a modularized system structure is adopted; all the units are combined into one organic integral body; a wireless measuring technology is adopted to more directly and accurately monitor an operating state of a chain; the state of the chain is dynamically regulated according to the load condition; after chain clamping and breaking accidents occur, fault protection is carried out by sending an alarm signal to an integral switch, and fault alarm is carried out; safety and stability of operation of the scraper conveyor are improved; and production safety of an underground coal mine is ensured.

The invention discloses a system and method for realizing vehicle state monitoring. The system comprises a vehicle-mounted terminal and a vehicle networking cloud service center in communication connection with the vehicle-mounted terminal, wherein the vehicle-mounted terminal comprises a positioning module, a vehicle self-diagnosis module, a three-axle acceleration sensor module, an oil-level linear sensor module and a communication module; vehicle-mounted data comprises positioning information, contamination discharging parameters, running state parameters of vehicle parts, acceleration and deceleration information, and liquid-level data of oil mass; the vehicle networking cloud service center is used for receiving the vehicle-mounted data transmitted by the communication module, performing unpacking calculation and treatment on the vehicle-mounted data, and storing calculation and treatment results to a vehicle networking service platform. Through the adoption of the multifunctional system and method for realizing vehicle state monitoring, disclosed by the invention, the running state of a vehicle is monitored, the position of the vehicle, the journey of the vehicle, the speed of the vehicle, the oil consumption of the vehicle, and the like are monitored in real time, so that a driver can discover the problems of the vehicle in time, modifying or optimizing measures are provided in time, and the driving safety is provided.

The invention belongs to the technical field of monitoring, and in particular discloses a multi-channel real-time monitoring and management system. The system comprises at least one front-end audio-video capture device, an intermediate transport network, at least one video decoder, a television wall and a central management platform, wherein a duplex communication manner is adopted between the central management platform and other equipment; and the central management platform issues instructions to the other equipment so as to manage and control operation of the other equipment; meanwhile, the central management platform collects the running status data of the other equipment so as to facilitate monitoring and management of the equipment. The system provided by the invention has the advantages that any one front-end supervising device and back-end display device can be instructed randomly so as to realize more flexible application; meanwhile the system also has the advantage of more rapid fault management and maintenance.

The invention discloses an intelligent hydraulic suspension unit and a control method thereof. The intelligent hydraulic suspension unit comprises a hydraulic cylinder, a digital throttling valve, an energy accumulator, a detection module, a controller, a hydraulic pump and an oil tank, wherein the hydraulic cylinder adopts a three-cavity dual-piston single-piston-rod structure, a cylinder body of the hydraulic cylinder is connected with a frame through a frame support, a piston rod of the hydraulic cylinder is connected with wheels through a wheel support, the digital throttling valve and the energy accumulator are configured to realize semi-active control, and a digital directional valve, the hydraulic pump and the oil tank are configured to realize active control. The controller realizes semi-active control through damping control and realizes active control through force and displacement compound control. The intelligent hydraulic suspension unit and the control method thereof have the advantages that the semi-active control and the active control on the suspension unit are realized through intelligent control, a hydraulic medium, wear-out and creeping phenomena of a sealing ring of the hydraulic cylinder, failure of a buffer mechanism as well as fatigue failure and wear-out failure of the piston and the cylinder body are effectively monitored, the operation state of the hydraulic cylinder is judged actively, the service life of the hydraulic cylinder is prolonged, the reliability of the hydraulic cylinder is improved, and the intellectualization of a hydraulic suspension is realized.

The invention discloses a farm data display platform based on a blockchain traceability system. The whole system architecture is composed of four parts: a blockchain back-end server, a production management acquisition mobile phone front end, a sensor farm acquisition network and a data visualization webpage. The production management collection mobile phone front end and the sensor farm collection network are responsible for collecting mature agricultural product packaging data and immature agricultural product production process data respectively, and the data is directly uploaded to the block chain rear end server after being collected. And the block chain back-end server classifies and stores the data after receiving the data uploading, and forwards the information data such as the geographic position, the data type and the block chain operation state of the uploaded data to the data visualization webpage. According to the invention, the block chain is used as a main form of agricultural data storage, and meanwhile, a webpage map is introduced, so that data acquisition equipment such as a sensor and a mobile phone can be displayed more visually in the map.

The invention discloses a machine equipment state monitoring system based on deep learning and voice recognition. The system comprises a training data collection module used for collecting voice signals; a manual marking module used for marking the voice signals to form a sound sample library, wherein sound samples are sent to a preset neural network model for training after being subjected to pretreatment and feature extraction; a real-time data collection module used for collecting the voice signals and sending the signals to the trained neural network model; and a state recognition module used for being combined with artificial experience to comprehensively recognize and determine a running state of a machine via the voice signal and feeding back and outputting a result. According to the system, the running state of machine equipment can be monitored in real time, and meanwhile when the machine equipment is faulted or in a dangerous state, an alarm signal is emitted to notice an equipment keeper to maintain in time, so that work efficiency is improved; and meanwhile, a deep learning algorithm is used and combined with the artificial experience to train the neural network model,so that the system has the advantages of high recognition accuracy, good safety, high efficiency and intellectualization.

The invention provides a generator utilizing acoustic energy, and a sound transducer. In the generator, a triboelectric nano power generation part is arranged in the cavity of an acoustic resonator; the cavity of the acoustic resonator can collect extraneous sound waves and allow the sound waves to generate resonance and converge to form standing waves in the cavity; two sides of the elastic membrane structure of the triboelectric nano power generation part form a sound pressure difference; electric signals are outputted to the outside in a contact separation process between a first electrode layer and a frictional layer. The generator does not need to be additionally provided with a vibrating diaphragm, thereby reducing unnecessary acoustic energy loss, and increasing acoustic energy utilization efficiency. The generator can also be used as a sound transducer which does not need a power supply and is a self-driven passive sound transducer.

The invention relates to a method, equipment and a system for monitoring the running status of a server, and particularly discloses the method for monitoring the running status of the server in a network. At least one piece of application runs in the server. The method comprises the following steps of: collecting abnormal information generated by the application from the server; and monitoring the running status of the server on the basis of the collected abnormal information. The invention also discloses corresponding equipment and a corresponding system. According to the embodiment of the invention, the running status of the server can be effectively monitored.

The invention relates to a method and a system for virtualized resources with optimized performance. The method includes that the operating performance of a physical server, the operating performance of a client virtual machine and a system call event of the client virtual machine are monitored on a virtual machine monitor layer at first; data are processed for the monitored system call event in a secure virtual machine according to the monitored operating performance of the physical server, the monitored operating performance of the client virtual machine and priority and security policies; and a control instruction is transmitted after the data are processed so as to control the system call event specific to operation for calling the virtualized resources. The method and the system for monitoring the virtualized resources with the optimized performance have the advantages that integral operating and security states of a system can be effectively monitored, and excellent user experience can be realized.

The invention discloses a characteristic vector extraction method for rolling bearing fault mode identification and state monitoring. The time wavelet energy spectrum fuzzy entropy of rolling bearing vibration signals is used as a characteristic vector so that rolling bearing fault mode identification can be realized, the operation state of a rolling bearing can also be monitored in real time and the early fault in the operation process of rolling bearing can be timely diagnosed. According to the time wavelet energy spectrum fuzzy entropy characteristic vector extraction method, the method can be simultaneously used for mode identification and operation state monitoring of different fault types of the rolling bearing so that the defect of the conventional method of respectively processing the two problems can be overcome, and the range of the similar research method for fault diagnosis of the rolling bearing can be greatly extended. Besides, the time wavelet energy spectrum fuzzy entropy acts as a single characteristic vector so that the method has higher fault mode identification efficiency in comparison with the multi-characteristic vector analysis method. Compared with the conventional rolling bearing operation state monitoring indicators, the method is more timely and accurate in monitoring the operation state of the rolling bearing.

The invention provides a wind power plant equipment state evaluation and maintenance decision support detection method. The method comprises the steps of (1) collecting and analyzing information whichcomprises technical data related to equipment patrol records, fault statistics and equipment running conditions; (2) performing charged detection: effectively monitoring a running state of wind powerplant equipment through the data collected by an instrument, and performing fault detection and prevention; (3) implementing state maintenance of a decision making system: by collecting and analyzingrunning data of the equipment, carrying out state evaluation work on the equipment to determine whether the equipment needs to be maintained or not and maintenance items; and (4) establishing an equipment pre-test maintenance optimization scheme: by implementing the state maintenance of the wind power plant equipment and the charged detection of the equipment, performing state evaluation on the equipment according to wind power plant equipment state evaluation rules, and customizing a maintenance policy. The invention furthermore discloses a corresponding detection system. The maintenance test cycle is prolonged, and maintenance test items are optimized, so that the maintenance test expense is reduced, excessive maintenance and lacking maintenance of the equipment are prevented, and the equipment stability is further improved.

The invention provides the state test method of wind power plant equipment live detection. The method comprises the following steps of (1) carrying out live detection: using an apparatus to collect data, implementing the live detection combining ultrasonic partial discharge detection and ultraviolet imaging detection, monitoring the operation state of wind power plant equipment, and carrying out fault detection and prevention; (2) constructing decision system state overhauling: collecting and analyzing the operation data of the equipment, and carrying out state evaluation work on the equipmentso as to determine whether the equipment needs overhauling and determine overhauling items; (3) establishing an equipment pre-test overhauling optimization scheme: through wind power plant equipmentstate overhauling, combining the implementation of equipment live detection, according to a power plant equipment state evaluation rule, carrying out state evaluation on the equipment, and making a customized overhauling strategy. The invention also discloses a corresponding detection system. A live detection method combining the ultrasonic partial discharge detection and the ultraviolet imaging detection is adopted, a test project is optimized and pre-test overhauling cost is saved.

The invention discloses an electromechanical equipment maintenance and management method based on BIM technology. The method includes steps of step 1 constructing a three-dimensional model; step 2 coding the information of the electromechanical equipment; step 3 realizing the information integration and communication of a monitoring system and a BIM system of the electromechanical equipment via a communication module; step 4 establishing an equipment maintenance and management database; step 5 establishing a fault analysis database; step 6 performing equipment simulation maintenance and repair; and step 7 setting a system management module. According to the electromechanical equipment maintenance and management method based on BIM technology, the electromechanical equipment information model is established and is aided by a real-time monitoring system, the running state of the electromechanical equipment can be timely known, the faults can be timely found and a solution scheme is provided; and meanwhile, the daily maintenance of the electromechanical equipment can be monitored, the periodical maintenance system is established, and the maintenance and management of a large number of complex electromechanical equipment of a building can be efficiently realized.

The invention discloses an air bearing compressor for a fuel cell. The air bearing compressor is characterized by comprising a rotating motor, a driving motor an impeller shell, wherein an impeller is arranged in the impeller shell; an air bearing which is radially coupled with the driving motor is arranged in the driving motor. According to the air bearing compressor disclosed by the invention, a state control system for controlling the physical quantities of motor speed, temperature, flow and pressure is designed, so that the rotating speed of the motor can be fed back and controlled comprehensively in real time. Through integration of a design thought and the state control system for controlling a plurality of physical quantities, the air bearing compressor for the fuel cell has the characteristics of small size, low cost, simple structure, low energy consumption, long service life and the like, the requirements of a new energy electric vehicle, a high-speed fan and the like on the fuel cell can be met, and the application field and application range of the air bearing compressor are further widened.

The invention discloses an intelligent component transporting method and system used for a prefabricated building. Components conveyed to a construction site are numbered according to a code system made according to a construction drawing and correspond to installation positions in a one-to-one mode, and the numbered components are conveyed to be within the hoisting range of a tower crane at the construction site according to the construction sequence; the tower crane hoists the components to a travelling bogie in sequence, the components are transversely conveyed to the workpiece loading position of each intelligent hanging lifting unit through the traveling bogie, the intelligent hanging lifting units convey the components to the installation stations, the unloaded traveling bogie returns to be loaded with the next component, and one working cycle is completed; and a climbable supporting base is controlled by an intelligent control device to climb to the new construction station upwards and automatically every time one or two storeys of the building are completed, and the next round of construction is conducted. The intelligent component transporting system is composed of a component conveying device and an intelligent control system. Building formwork components can be conveyed to the installation positions through crossed arrangement of longitudinal beams and transverse beams, and time and labor are saved.

Equipment for detecting the abnormal sound of equipment device comprises an equipment body, and is characterized in that the equipment body comprises a front-end data collector and an edge computing container; the front-end data collector is a device capable of collecting audio characteristics and compressing, transmitting and storing data signals. The technical point is characterized in that after data slicing processing is carried out in audio data processing, each obtained feature vector matrix of audio features extracted through an MFCC method is straightened and subjected to dimension reduction processing, the extracted audio features are better, and the clustering effect is more remarkable; by adopting the clustering algorithm of the self-organizing feature mapping neural network (PSO-SOM) based on particle swarm optimization, the label of the data does not need to be known; according to the method, the class with large data volume is classified as the normal operation sound by default in a segment of long equipment operation sound data, the SO-SOM algorithm is superior to the SOM basic algorithm in clustering effect evaluation indexes (AVQ, UTE and LWDI), and the obtained network is good in quality and low in misclustering rate.

The invention discloses an alarm linkage video monitoring system and method for a cable terminal tower field. A wireless audio and video encoder is connected with an intelligent control terminal through a serial port; an upper computer respectively communicates with the intelligent control terminal and the wireless audio and video encoder, the intelligent control terminal communicates with an alarm signal input and output device, and the wireless audio and video encoder is respectively connected with an audio collection device and a tripod head controller; and a hybrid power supply apparatus is connected with the intelligent control terminal for supplying power to a cable terminal tower video monitoring system. The alarm linkage video monitoring system and method disclosed by the invention have the beneficial effects of completely solving the problem that single solar power supply is influenced by weather factors, controlling the security of onsite implementation periphery, carrying out linked alarm on abnormal invasion and snap shooting and recording dangerous point images of onsite electrical appliances, and a periodical and automatic image snap shooting and recording function of critical points guarantees the safe and reliable operation of the terminal tower, so as to guarantee the safety and stability of the entire power supply system.

The invention relates to an automatic guide vehicle, an automatic guide system and a navigation method based on an ultrasonic range finder. The automatic guide vehicle comprises a drive chassis, an automatic guide vehicle body, a drive device, a gyroscope, a displacement encoder, a drive controller, an ultrasonic range finder receiving device and a controller, wherein the automatic guide vehicle body and the drive device are arranged on the drive chassis, the gyroscope, the displacement encoder, the drive controller, the ultrasonic range finder receiving device and the controller are arranged on the automatic guide vehicle body, and the gyroscope is used for acquiring a driving course angle of the automatic guide vehicle based on the ultrasonic range finder; the displacement encoder acquires the driving displacement of the automatic guide vehicle based on the ultrasonic range finder; the drive controller controls the drive device; the ultrasonic range finder receiving device which is arranged on the automatic guide vehicle body receives an ultrasonic signal and calculates a transmission distance value of the ultrasonic signal; and the controller is respectively electrically connected with the gyroscope, the encoder, the drive controller and the ultrasonic range finder receiving device and calculates a running route of the automatic guide vehicle based on the ultrasonic range finder according to the acquired course angle, the displacement and the distance value and controls the drive device to run through the drive controller.