198results about How to "Timely investigation" patented technology

The invention relates to the technical field of fire safety, and provides a public fire warning indicating terminal comprising a sensor module, a camera, a sound pick-up, a processor and a communication module. The sensor module is used for detecting environment parameter data, and comprises a temperature sensor and a smoke detector. The camera is used for acquiring environment images. The sound pick-up is used for acquiring environment sound. The processor is used for acquiring the environment parameter data detected by the sensor module, transmitting the environment parameter data and data acquired by the sound pick-up to a fire warning system server through the communication module, determining whether an exception occurs or not according to the environment parameter data acquired by the temperature sensor and the smoke detector, and if so, sending warning signals through the communication module. The communication module is used for interacting data between the processor and the fire warning system server. The public fire warning indicating terminal has the advantages that structure is simple, configuration is reasonable, data are pre-processed by the built-in processor of the public fire warning indicating terminal, when exception is determined to occur, warning signals are sent to the fire warning system server, speed of warning is increased, and accuracy of warning is improved.

The invention discloses a distributed cluster performance monitoring system. The system comprises a monitoring module and a plurality of middleware modules, wherein the monitoring module is deployed in a distributed cluster; each middleware module is deployed in each service component of each node of the distributed cluster; each middleware module is used for generating tracking information of a business request when the business request passes through a corresponding service component, and storing the tracking information of the business request into a log file on the basis of a global identifier carried by the business request; and the monitoring module is used for generating a calling link of each business request on the basis of the tracking information of the business requests in thelog files. By applying the system provided by the invention, calling links of the business request are generated and analyzed, so that performance of the distributed cluster can be effectively monitored and troubleshooting or system optimization can be carried out in time. The invention furthermore discloses a distributed cluster performance monitoring method which has corresponding technical effects.

The invention discloses a full-process three-dimensional dynamic safety management method of a building enterprise. According to the method, a bidirectional closed-loop operation mode is utilized. Through performing classification and identification processing on engineering projects which enter a safety risk evaluation database, an engineering project safety evaluation report is generated. An engineering project three-dimensional dynamic safety hazard monitoring model is established in a second-level enterprise layer and potential hazard early-warning information is issued. Real-time monitoring for sensor and video, and artificial regular checking and modification are performed at a project part. A safety accident is handled immediately. The three-dimensional dynamic safety hazard monitoring model is instantly updated. After the engineering project is finished, updating learning is performed on a safety risk evaluation database. According to the full-process three-dimensional dynamic safety management method, learning and reutilization are performed on safety management historical data of the building enterprise. Advanced forecasting, early warning and prevention are performed on the potential safety hazard. The safety event is reasonably handled immediately after occurrence. Safety of persons, fund and property in the engineering project of the building enterprise can be effectively ensured. Furthermore loss is reduced.

A vehicle-mounted fault detection and early warning system disclosed by the present invention mainly comprises a vehicle-mounted MCU, an on-board diagnostics (OBD) system interface, an ABS signal acquisition module, an automatic transmission connection module, a car light data acquisition module, a voice communication module and a 4S store detection, maintenance and service platform. The vehicle-mounted fault detection and early warning system of the present invention can accurately detect the vehicle faults and the concrete faulted parts and positions, alarms the faults, does not need to the professional instruments, does not require the technology levels for overhauling personnel, is convenient to carry, and can timely troubleshoot the faults which are not observed by the operators easily, but possibly cause the serious consequences.

The invention provides a fire disaster treating robot and system. The fire disaster treating robot is arranged in a building, and compared with manual fire disaster risk check in the prior art, the fire disaster treating robot and system have the beneficial effects that fire disasters in the building can be checked all the time, the fire disaster detection efficiency is improved, fire extinguishment treatment can be carried out when a fire disaster occurs, treatment is in time, and the damage to the building from the fire disaster is reduced as much as possible.

The invention discloses a transformer state prediction method, which comprises the following steps: (1) respectively training a long-term and short-term memory neural network and a deep belief neuralnetwork; (2) inputting the current concentration value of the characteristic gas in the transformer oil chromatographic data to be identified into the trained long-short-term memory neural network toobtain the future concentration value of the characteristic gas outputted from the trained long-short-term memory neural network; Obtaining a future concentration ratio of the selected gas based on the future concentration value of the characteristic gas; feeding The selected gas future concentration ratio into the trained deep belief neural network to obtain the transformer state prediction results. In addition, the invention also discloses a transformer state prediction system, which comprises a long-term and short-term memory neural network module and a deep belief neural network module. The transformer state prediction method can predict the transformer state efficiently and accurately, and has guiding significance for the operation and maintenance of the transformer.

The invention discloses a stope micro-earthquake continuous monitoring intelligent early-warning instrument, which is characterized in that a micro-earthquake sensor sensing and collecting device is arranged at a stope access or in an adjacent drift roadway so as to monitor stope rock mass micro-fracture signals and collect the micro-earthquake time, the micro-earthquake frequency, the micro-earthquake energy, the micro-earthquake magnitude and the micro-earthquake location; a micro-earthquake signal processing system analyzes the collected data so as to carry out judgment on the stability state of stope rock mass and carry out recognition on a potential rock mass collapse hidden danger location of the stope; and an early-warning device carries out sound-light signal early warning on the stability of the stope rock mass. The stope micro-earthquake continuous monitoring intelligent early-warning instrument can perform monitoring on the stope rock mass stability, and carries out early warning on potential safety hazards such as roof collapse, wall caving and rock burst in a stope personnel operation area. Workers are enabled to check and process rock mass collapse hidden dangers in the stope personnel operating area timely, and safety accidents such as roof collapse, wall caving and rock burst can be effectively controlled and reduced.

The invention discloses an intelligentized sewage treatment expert system, and belongs to the technical field of environmental engineering .The expert system comprises a data storage device and a display device; input data and a data analysis result can be displayed in the display device; the display device can display two first-stage modules including the operating management problem query module and the effluent quality standard exceeding reason reasoning module; the effluent quality standard exceeding reason reasoning module is provided with five second-stage modules including the effluent TN quality standard exceeding reason judging module, the effluent NH3-N quality standard exceeding reason judging module, the effluent COD quality standard exceeding reason judging module, the effluent SS quality standard exceeding reason judging module and the effluent TP quality standard exceeding reason judging module .According to the expert system, sewage treatment field expert-level experience and knowledge are integrated into the same system platform, a more convenient way capable of effectively solving the practical problems is supplied to technicians in the sewage treatment field, checking can be conducted in time, an effective solution can be presented in time, and the operating management level of a sewage treatment plant is increased.

The invention relates to the technical field of 3D (Three-dimensional) printing, concretely relates to a 3D printer waste recovery system, and discloses a recovery method utilizing the recovery system. The recovery system comprises a waste storage device, a waste recovery device, a waste cooling device, a waste smashing device, a smashed waste conveying device and a re-injection molding device; and the recovery method comprises a waste storage process, a waste recovery process, a waste cooling process, a waste smashing process, a waste conveying process and an injection molding process. According to the 3D printer waste recovery system and the recovery method thereof provided by the invention, through the reasonable setting and the coordination and distribution of responsibilities of the processes, the 3D wastes are recovered through the system, and the cyclic utilization of the 3D printer wastes is realized.

The invention provides a brushless DC electronic water pump fault diagnosis system, which comprises an observer and a fault analysis module, wherein the observer inputs a motor angular velocity and control voltage, and a load torque observation value is obtained; the motor angular velocity is actually measured through a sensor, and the control voltage is obtained through an original brushless DC electronic water pump control system; the fault analysis module comprises a water pump operation fault analysis module; the water pump operation fault analysis module is used for comparing the load torque observation value obtained by the observer and a set load torque range, when the obtained load torque observation value is not in the load torque range, fault is judged to happen to operation of the water pump, and a plurality of load torque observation values are acquired in the case of normal water pump operation, an arithmetic mean value and a standard deviation are calculated, appropriate multiples are selected, and thus the load torque range is obtained. Detection output of the sensor is only used for data calibration, an observer model is built, and fault diagnosis is carried out on the water pump.

The invention relates to partial discharge detection of three-phase power cable insulation in a metal sheath crossing interconnection mode, and provides a power cable partial discharge detection system based on ultrahigh-frequency and high-frequency current combination for diagnosing and recognizing the insulation partial discharge defect of the power cable. Therefore, the technical scheme adoptedby the invention is that the power cable partial discharge detection system based on the combination of UHF and HFCT comprises an ultra-high frequency signal acquisition unit, and a data acquisitionand transmission unit, which are sequentially in series connection; a high-frequency signal acquisition unit, a data acquisition and transmission unit, which are sequentially in series connection; a host computer and a wireless synchronization module. The method is mainly applied to partial discharge detection of phase power cable insulation.

The invention provides a detecting method, device and system for vehicle abnormal wakeup. The detecting method for vehicle wakeup comprises the steps that a fault signal sent by a vehicle is received,wherein the fault signal is sent when the output voltage of the vehicle is lower than a preset voltage threshold value; a plurality of groups of pre-stored vehicle data are obtained according to thefault signal, wherein the groups of the vehicle data are reported every time the vehicle is waken up; and if at least two groups of the vehicle data are lower than the preset threshold value, abnormalwakeup reminding messages are generated. According to the detecting method, device and system for vehicle abnormal wakeup, whether abnormal wakeup occurs to the vehicle or not is determined through the vehicle data, when abnormal wakeup occurs to the vehicle, users are reminded, and multiple times of feeding of a low-pressure storage battery is avoided.

The invention relates to the technical field of unmanned vending, in particular to an unmanned vending cabinet anti-theft method and system, and an unmanned vending cabinet with an anti-theft function. The unmanned vending cabinet anti-theft method comprises the steps that a change angle of a cabinet door is judged through a visual door opening and closing detection algorithm, the change angle ofthe cabinet door is compared with a preset angle to obtain a comparison result, and an opening or closing state of the cabinet door is judged based on the comparison result; a producing state of an unmanned vending cabinet order is detected; the opening or closing state of the cabinet door is combined with the producing state of the order to determine an operating state of the unmanned vending cabinet; when the operating state is abnormal, the unmanned vending cabinet sends an alarm message, and the visual door opening and closing detection algorithm determines the opening or closing state ofthe cabinet door, thus the method for judging the opening or closing state of the cabinet door is faster and more accurate, and the behavior of fraudulent locking is avoided; and the opening or closing state of the cabinet door is combined with the producing state of the order to determine an operating state of the unmanned vending cabinet, thus the real-time sales situation of the unmanned vending cabinet can be accurately determined, and theft of goods caused by human interference is avoided.

The invention provides a NB-IoT valve controlled dry reed tube Internet of Things water meter. The NB-IoT valve controlled dry reed tube Internet of Things water meter comprises a NB-IoT module and aWIFI unit; through a general asynchronous serial communication bus, the NB-IoT module and the WIFI unit are respectively connected with a central processing unit in a communication mode, a communication control unit first selects the NB-IoT module for communication, in the absence of the NB-IoT coverage, the NB-IoT module is automatically transfered to the WIFI for communication; a dry reed tube core unit is added, and connected with the central processing unit, measured pulse value can be received in real time; through a display unit, the working state information of the water meter is displayed dynamically; through a wake-up switch unit, water meter state can be awakened manually or regularly awaken. According to the NB-IoT valve controlled dry reed tube Internet of Things water meter, the water consumption situation can be controlled through the user's water meter, manpower, material and financial resources are saved, and the efficiency of production is improved. The adopted operator led wide-area low-power NB-IoT technology has the advantages of wide coverage, large capacity and high reliability, is especially suitable for water terminal connections in urban areas. Intelligentmeter reading management is truly realized, and substantial industry promotion is brought to the smart meter industry.

The invention discloses a body temperature detection method and device and a thermal infrared image processor. The method comprises the steps of detecting the body surface temperature of a preset partof a target object; determining the body temperature of the target object according to the detected body surface temperature; determining whether the body temperature of the target object is abnormalor not according to the body temperature of the target object and a temperature threshold value, wherein the temperature threshold value is determined through the following operations that a body temperature information set, detected within a previous preset time range, of a historical detection object is obtained; and the temperature threshold is determined according to the body temperature information in the body temperature information set. And the temperature threshold value can be dynamically updated and adjusted continuously according to the change of the environment temperature. In this way, in the process of determining whether the body temperature of the target object is abnormal or not according to the temperature threshold value, individuals who have the body surface temperature lower than the conventional fever temperature but are actually in the fever state can be timely and accurately checked out, and the possibility of large-range infection is greatly reduced.

The invention discloses an image processing system, apparatus and method for a displacement sensor. The system comprises a linear array light-sensitive chip and an FPGA processing chip, wherein the linear array light-sensitive chip is connected with an FPGA processing chip; and the FPGA processing chip comprises a receiving module and an image processing module, wherein the receiving module is used for receiving image signals from the linear array light-sensitive chip, and the image processing module is used for filtering the image signals received by the receiving module, determining the position of the center point of an image contour according to the filtered image signals and determining a relative displacement value. According to the system provided by the invention, real-time image processing is completely realized by the FPGA; the relative displacement value is determined based on the center point of the image contour; and therefore, the use of large-sized equipment can be avoided, and installation and use can be facilitated, and the method used in image processing can be effectively applicable to the linear array sensing chip, and thus, the precision of displacement sensing can be ensured, the complexity, cost and energy consumption of the system can be reduced, the hardware requirement of the system can be lowered, and real-time performance can be ensured.

The invention provides a copy plate identification method and system, an intelligent license plate, a scanning device thereof and a copy plate determining device. The copy plate identification methodexecuted by the scanning device of the intelligent license plate comprises that an electronic label unit of the intelligent license plate is scanned; vehicle information stored in the electronic labelunit is obtained; and the obtained vehicle information is sent to the copy plate determining device. The copy plate identification method executed by the copy plate determining device comprises thatthe vehicle information of the intelligent license plate is received from the scanning device of the intelligent license plate; the received vehicle information is compared with stored vehicle information; and if the received vehicle information does not match any of the stored information of multiple vehicles, it is determined that the intelligent license plate is a copy plate. Thus, a vehicle using the copy plate can be identified effectively, and a vehicle using a fake plate can be also identified.

The invention provides a router state monitoring method, device and system. The method includes the steps: S100 acquiring network state information of a router; S200 transmitting the network state information to a target terminal, and accordingly receiving and displaying the network state information by the target terminal. The network state information comprises network normality information andnetwork anomaly information. The device comprises an acquisition module and a transmitting module, wherein the acquisition device acquires the network state information of the router, and the transmitting module transmits the network state information to the target terminal, so that the target terminal can receive and display the network state information. A user can be timely reminded of networkinterruption of the router, and the router is timely repaired and troubleshot.

The invention discloses an on-line security monitoring method for freight, which includes the following steps: SA1, setting up a database, storing driver identity information which includes a photograph and a title; SA2, arranging a camera device in a vehicle and carrying out camera shooting on the driver; SA3, obtaining the right to use the vehicle after the name of the driver is verified; SA4, collecting the driver real-name verification information, and taking corresponding driver photograph from the database; SA5, comparing the image shot by the camera device with the driver photograph; and S6, calling the police if the shot image and the driver photograph are inconsistent. The on-line security monitoring method for freight pre-stores the driver identity information, compares the driver real-name verification information with the pre-stored identity information, and allows the driver to obtain the right to use the vehicle only when the real-name verification information matches some pre-stored driver identity information. The on-line security monitoring method for freight prevents lawless persons from stealing and using the vehicle and controls the vehicle use condition.

The invention provides a street lamp intelligent detection and night state judgment method which comprises the following steps: step 1, collecting street lamp pictures in a daytime environment, and manually marking position coordinates of street lamps in the pictures; step 2, training a street lamp detection model by adopting a deep convolutional neural network; step 3, initializing the system inthe daytime environment, and initializing the position and angle relationship of the street lamp in the camera by using the street lamp detection model obtained in the step 2; step 4, judging the state of the street lamp at night, and obtaining a street lamp position interval according to the camera and the street lamp position model obtained in the step 3; step 5, judging the light and shade state of the street lamp according to the street lamp position obtained in the step 4; and step 6, if the street lamp is continuously found to be in a non-bright state, sending alarm information to streetlamp managers. According to the invention, the light and shade state of the street lamp in the night environment can be obtained without transforming the existing street lamp and the road surface environment and transmitting the image of the camera installed in the road administration department to the background for analysis.

The invention provides a wafer defect analysis system. The wafer defect analysis system comprises a wafer defect scanning library, a defect position obtaining unit, a defect position matching unit, a defect set analysis unit, a defect set correlation analysis unit and a defect marking unit, wherein the wafer defect scanning library is used for storing defect scanning graphs of a wafer scanned by a wafer scanning drilling crew in pre-set time; the defect position obtaining unit for sorting position information; the defect position matching unit is used for matching the position information of one defect in the defect scanning graph of one wafer with the position information of one defect in the defect scanning graph of the other wafer, and marking a matched set; the defect set analysis unit is used for obtaining position information of a defect set; the defect set correlation analysis unit is used for carrying out a correlation analysis on the position information of the defect set between the two wafers; and the defect marking unit is used for displaying the defects with the correlation in the defect scanning graphs by highlight. The wafer defect analysis system can be used for analyzing the defect scanning graphs and can mark the defects with the correlation by the highlight so that in-time troubleshooting of the same defect condition of the specific positions of the wafer is convenient to carry out and the manpower and the time are saved.

The invention provides a traffic light fault detection system based on machine learning. The system comprises detection terminals, a remote detection center and communication modules, wherein the detection terminals are integrated in traffic lights, and each detection terminal comprises a current detection unit, a voltage detection unit and a time detection unit; the remote detection center transmits data with the detection terminals through the communication modules and comprises a detection data processing unit, a display unit and a compensation unit; the detection data processing unit receives and processes detection data from the detection terminal and comprises a learning type chip, and the display unit and the compensation unit are connected with the detection data processing unit. The system can detect running conditions of traffic lights in a covered area in real time, send detection data to the detection center for processing and display, and faulted traffic lights can be timely checked. Besides, the system can actively compensate errors for the detection data and has higher learning performance and intelligence.