319results about How to "Realize intelligent detection" patented technology

The invention relates to a method and a system for detection of a verticality of CCD installation of a laser cutting machine with an automatically edge searching performance. The method comprises the following steps that: a laser head of a laser cutting machine is directly utilized; a circle and a center of circle mark patterns that are formed by laser light spots are typed on calibration papers,which are paved fixedly at five different areas at a working plane of a cutting bed; marked images at the five different areas are shot through a CCD; an image processing technology is utilized and circumference point coordinates and center point coordinates of the marked images are respectively extracted; and an extreme values of distance of from the center point to all the circumference points are calculated and a verticality between a CCD shaft and the cutting bed is calculated by a calculation model. In addition, the invention also relates to a detection system for a verticality of CCD installation of a laser cutting machine with an automatical edge searching performance. And the detection system mainly comprises three software modules: a control module, an image processing module, and a data processing module. According to the invention, problems on slow detection speed, low efficiency and poor precision and the like during detection on a verticality of CCD installation of a laser cutting machine with an automatically edge searching performance are solved and an automatic capability of the system is also improved.

The invention relates to a highway illegal parking detection method, belonging to the technical field of image processing. According to the method, firstly, a highway in an area is subjected to video sequence extraction and code identification, and a high speed road video sequence information base is established; secondly, the road video sequence image processing is carried out, a moving vehicle license plate is extracted and the center of mass of a vehicle is calibrated, the distance from the center of mass of the vehicle to a highway initial position in the area is recorded, and a vehicle real-time position information base is established and stored; then a driving vehicle is subjected to tracking calibration, the change rate of the vehicle to the initial position in the video sequence is judged, a vehicle driving state is judged, and the illegal parking time of the vehicle is calculated; and finally an illegal parking warning is emitted according to the illegal parking time length of the vehicle at the highway. According to the method, a designated road can be subjected to real-time monitoring, vehicle illegal parking can be timely found, potential traffic accidents can be avoided, the accuracy of illegal parking early warning is greatly raised, and the consumption of manpower resources is reduced.

The invention relates to a personnel behavior identification and detection implementation system and method based on image segmentation and semantic characteristic extraction. The system comprises an image acquisition unit, a personnel behavior detection host computer, a user inquiry unit and an output interface unit. The method comprises the following steps: the personnel behavior detection host computer identifies personnel behaviors in the image data acquired by the image acquisition unit through image segmentation and image semantic characteristic extraction so as to generate personnel behavior presentation information. In the method, the personnel behavior detection host computer maps low-level features of an image into high-level semantics through a support vector machine so as to establish a mapping relation between the image and the image description, so that the content in the picture can be comprehended through digital image processing and analysis, the behaviors of personnel in the scene can be intelligently detected, and the identification accuracy of personnel behaviors in the image can be greatly improved. The system provided by the invention has a simple structure, and the method provided by the invention is simple and convenient to implement, low in application cost and wider in application range.

The invention relates to an intelligent method for testing cardiograms by basing on quanta a simple recursion neural network, which comprises the steps that: the cardiac electric signals are sent to a self-adaptation power frequency disturbance-restriction module for restricting the disturbance of the power frequency; the two output cardiac electric signals in the previous step are sent to a blind baseline drift disturbance-restriction module so as to remove the breath baseline drift disturbance; the output cardiac electric signals in the second step are sent to the quanta simple recursion neural network for carrying out cardiac electric intellectual test and output. The self-adaptation power frequency disturbance-restriction module comprises two same groups of self-adaptation power frequency disturbance-restriction units, and carries out power frequency disturbance-restriction on the two collected groups of cardiac electric signals simultaneously and respectively. The self-adaptation power frequency disturbance-restriction module can automatically restrict power frequency disturbance by adopting the cardiac electric power frequency disturbance-restriction method basing on QR decomposing recursive least squares (RLS) algorithm self-adaptation trap technology. The invention can not only realize cardiac electric intellectualization test, but also remove the power frequency and the breath baseline drift disturbance in the effective frequency band of cardiac electric signals, and solve the difficulty that digital filtration method eliminates the disturbance of aliasing in spectrum.

The invention relates to the electroplating production field, and particularly relates to an intelligent sensing method and system for electroplating line current abnormity. The method comprises the following steps: obtaining a current value required for electroplating according to inputted electroplating current density, and electroplating parameters of a production panel; carrying out electroplating work according to the current value; detecting an electroplating voltage signal during the electroplating; calculating a theoretical voltage corresponding to the inputted electroplating current density according to the linear relation between the voltage and the electroplating current density; sampling and comparing the detected electroplating voltage signal with the theoretical voltage signal, and determining electroplating deviation when the detected electroplating voltage signal is larger than a certain set threshold of the theoretical voltage. According to the invention, by using the linear relation between the electroplating voltage and the current density, the electroplating voltage of an electroplating line is monitored during electroplating in a manner of electroplating current controlling; whether electroplating abnormity occurs is determined by comparing the real voltage with the set current density; and thus intelligent detection of electroplating current abnormity is realized.

The invention provides an in-orbit spacecraft surface abnormity status intelligent detection system comprising a two-dimensional imaging sensing device, a three-dimensional imaging sensing device, anintelligent lighting device and a laser range finding machine; the two-dimensional imaging sensing device and the three-dimensional imaging sensing device are respectively arranged on an end performerof a space robot; the intelligent lighting device comprises a lighting light source, a multi-freedom motion mechanism and a data processing unit; the lighting light source can emit lights of different colors according to needs, and is arranged on the multi-freedom motion mechanism; the multi-freedom motion mechanism is arranged on the end performer of the space robot; the data processing unit comprises a digital signal processing circuit; the laser range finding machine is used for controlling the distance of the end performer of the space robot and an observed object. The method and system are complete in function designs, thus satisfying related application demands of spaceflight in-orbit services, effectively improving environment adaptability of each data processing algorithm, and providing a higher intelligent level.

The invention discloses a high-speed train bottom foreign matter recognition method based on deep learning. The method is carried out according to the following steps: shooting bottom images of high-speed train, screening out images containing foreign matters; expanding the number of images by using a data enhancement method; aiming at the defects of YOLO-V3 network precision design, designing a DenseNet-based network as a feature extraction network, and inserting a spatial pyramid network into a multi-scale prediction layer, so that the precision of a YOLO network framework is improved, and meanwhile, the defect of low small object detection precision is improved; and training the improved YOLO-V3 model by using a stochastic gradient descent method to obtain a vehicle bottom foreign matter detection model, inputting a vehicle bottom foreign matter picture into the model, and outputting the recognition result of the picture. The method can achieve the intelligent detection of the foreign matters at the bottom of the high-speed train, is high in recognition rate, high in detection speed, high in detection efficiency and high in practicality, is obvious in advantages compared with aconventional detection method, and has the potential of being applied to other fields.

The invention relates to an application system, and especially relates to the mobile phone application system monitoring plant growth. The mobile phone application system monitoring plant growth, which is provided by the invention, comprises a WiFi sensor detection device, an intelligent mobile phone APP application module and a background server system. The intelligent mobile phone APP application module respectively communicates with the WiFi sensor detection device and the background server system. According to the invention, through the sensor detection device which integrates a temperature and humidity sensor, a light intensity sensor and a WiFi communication module into a whole body, intelligent detection is carried out on the temperature, the humidity and the light intensity of a flower growth environment; when the temperature, the humidity and the light intensity exceed standards, a sound and light alarm signal is sent out to remind a people who raises a flower, and information is sent to a mobile phone of the people who raises the flower for further reminding; and the system has the advantages of reasonable design and complete functions.

The invention relates to the technical field of poultry farming, and discloses a poultry body temperature detection method based on image fusion and a poultry house inspection system. The poultry bodytemperature detection method comprises the following steps: acquiring a thermal imaging image and a visible light image of poultry; performing image fusion on the thermal imaging image and the visible light image to obtain a fused image; establishing a deep neural network model, performing feature recognition on the key parts of the poultry in the fusion image, obtaining temperature information of the key parts of the poultry in the fusion image, and performing conversion according to the temperature information of the key parts of the poultry to obtain body temperature information of the poultry. Based on image fusion of thermal imaging and visible light, and thrugh the feature recognition of the deep neural network model and the corresponding temperature conversion, the intelligent detection of the poultry body temperature is realized, the accuracy of the detection result is ensured, the inspection requirements of the poultry house in various breeding environments are met, the inspection efficiency of the poultry house is greatly improved, and the poultry breeding cost is saved.

The invention provides an intelligent detection system for blade surface detects of a wind turbine generator system. The intelligent detection system comprises an image pickup system, a programmable software detection system and a communication system, wherein the image pickup system comprises a support and an image pickup apparatus, an adjusting apparatus comprises a pitch angle adjuster and a horizontal adjuster, and the programmable software detection system comprises an image acquisition module, an image analysis and screening module, an image classification module, an image filter module,an image processing module, a defect identification module, a calculation defect position and geometric characteristic information module, a defect analysis suggestion module and a defect detection report output module which are successively connected with one another. The intelligent detection system has a digital image processing function, analyzes and processes an acquired image, extracts a defect image and automatically generates a defect report, so that the intelligent defection for the blade surface defects of the wind power generator system can be realized; and compared with the existing defection means, the intelligent detection system has the advantages of convenience and flexibility in detection, less time, remote detection, accurate detection result and no safety potential hazard.

The invention relates to a large-scale farm sign abnormal bird detection method, which comprises the following steps: pre-processing the collected thermographic images for data annotation, then adopting an instance-based segmentation general framework (Mask RCNN) target detection and instance separation method for feature extraction, pixel alignment, target positioning, classification and mask separation for thermal imaging images, by controlling the target detection number of a single image, improving the detection accuracy rate in each image. The method is an attempt in the field of target detection of current thermal imaging images, breaks the limitations brought by the traditional methods, and uses the superior performance of deep learning in image feature processing to improve the robustness and accuracy of a model. The feasibility of the deep learning method in the field of thermal imaging image detection is verified. At the same time, the method can also be extended to the livestock and other fields, thus improving the level of intelligence in the breeding industry in China.

The preset invention discloses a three-dimensional scanning laser radar based on one-dimensional optical phased array, the radar comprises a transmitting end, a coherent receiving end, and a non-coherent receiving end, all of which are one-dimensional arrays. The radar reduces phase control complexity of a three-dimensional scanning phased array and avoids using costly tunable lasers and grating array antennas with large crosstalk. The radar still has significant advantages in speed and integration level of a pure solid state three-dimensional scanning scheme, and has very high practical value.

The invention discloses a method for detecting the roundness and straightness of a large deep hole part in a boring process. Firstly, a system for detecting the roundness and straightness of the largedeep hole part is established; laser light emitted by a laser displacement sensor is divided into two beams of light through a reflection prism; one beam of light is returned to the laser displacement sensor along an original light path, and the other beam of light is irradiated on a position sensitive detector through a spectroscope; the laser displacement sensor and the position sensitive detector transmits collected information to a data acquisition card in real time, and the information is processed through a data storage module and a pre-machining module; and finally measured roundness and straightness errors are evaluated in an error evaluation module. According to the detection method disclosed by the invention, machining parameters can be adjusted according to a detected error signal, and feedback closed-loop control is carried out on boring machining, so that the machining quality is improved, and the machining efficiency is improved.

The invention discloses a secondary phase detecting instrument and method. The secondary phase detecting instrument comprises a low-voltage PT (Potential Transformer) module set, an A / D module, a master control MCU (Microprogrammed Control Unit) module, a human-computer interaction module and a power module; when in use, six lines of which the voltages are to be checked are connected to corresponding interfaces, the phase is started to be checked after powering until successfully checking the phase, any artificial interference is not needed during phase checking, and therefore, the phase checking operation is simple; in addition, the phase checking can be accurately carried out by acquiring the voltage within 20m under a cycle, so that time for waiting in the whole phase checking process is short, and as a result, the phase checking efficiency is greatly raised; finally the intelligent detection of a three-phase electrical phase sequence at any voltage grade can be performed under the existing artificial phase checking hardware condition, and therefore, the applicable scope is wide.

The invention relates to the technical field of the welding line defect nondestructive detection, and especially relates to an actively-motivated welding line defect infrared intelligent detection system and method. The infrared intelligent detection system for welding defect detection is composed of a driving device, a regulating device, a high-definition camera, an upper computer, a signal generator, a laser pulse gauge, an infrared thermal imager and a code-spraying mark device, different types of welding slot defect can be detected, the infrared intelligent detection system of the welding slot defect can acquire a welding slot trend through the high-definition camera, the laser pulse gauge is used for emitting active laser pulse to perform thermal excitation on the welding slot region, the infrared thermal imager acquires an infrared thermal image, an upper computer system performs image processing on the infrared thermal image, and distinguishes the welding slot defect in real time, and the code-spraying mark device is controlled to automatic identify the welding slot defect location. The intelligent continuous detection of the welding slot defect can be realized, all welding slot defects can be effectively distinguished, and the system has the features of being energy-saving and environment-friendly, efficient and accurate, intelligent and continuous and safe and reliable.

The invention relates to the technology of plastic pipe electric melting joint detection and aims at providing an ultrasonic detection method for a defect automatic identification auxiliary electric melting joint smart phased array. The ultrasonic detection method comprises the steps of carrying out joint defect detection preparation, carrying out joint defect detection imaging and carrying out joint defect detection identification. Welding defect identification is realized through utilization of a defect automatic identification module based on a neural network algorithm. The welding defect identification comprises the content of preprocessing welding defect detection image data, carrying out classification identification on feature areas based on the neural network algorithm and carryingout safety assessment on typical defects. According to the method, typical defect automatic identification, real-time display and alarm prompt in a detection process are realized, dependence of a traditional phased array ultrasonic detection method on a qualification of a detector is overcome, and defect missing detection can be effectively avoided. According to a defect automatic identificationtechnology based on the neural network algorithm, operation speed is fast, complex defect identification accuracy is high, computing load of an ultrasonic detecting instrument can be reduced, and defect detection and identification are guaranteed to be displayed synchronously in real time.

The invention relates to an intelligent home system based on a wireless remote control technology. The intelligent home system comprises an IOT platform, an intelligent home controller, an intelligent home control centre, a mobile intelligent terminal and parameter detection equipment; the mobile intelligent terminal and the intelligent home controller are controlled through wireless communication; the mobile intelligent terminal and the intelligent home control centre are connected through a wireless network; the parameter detection equipment is used for detecting a parameter to be sampled of a house in real time and generating a corresponding parameter signal; and the intelligent home control centre sends the parameter signal detected by the parameter detection equipment to the IOT platform, such that control is carried out. According to the invention, the advanced technologies, such as an intelligent home technology, an indoor positioning technology, a sensor technology and a wireless transmission technology, are integrated; multiple functions, such as voice control, intelligent service discovery control, intelligent environmental adjustment, intelligent safety protection and intelligent energy-saving, can be realized; intelligent control and automatic control are realized; and thus, relatively high intelligent living requirements of people can be satisfied.

The invention discloses a novel electrostatic cooking fume purification integral machine which comprises a shell, wherein a cooking fume collection cover is mounted on one side of the shell; a water tank is arranged at the bottom of the shell; an exhaust fan is mounted inside the shell; cooking fume purification cavities are formed in two sides of the exhaust fan; an air outlet and an air inlet communicated with the cooking fume purification cavities are formed in the shell; an electric field purification device, a first cyclone baffle filter, a self-sucking baffle purifier and a second cyclone baffle filter are sequentially mounted from the air outlet to the air inlet inside the cooking fume purification cavities; and a detergent replenishing device is connected with the water tank. Due to a five-stage efficient oil removal purification system, the integral machine has ideal oil removal effect, a detergent can be automatically replenished, filters of the cooking fume purification cavities can be automatically cleaned to ensure optimal performance, the maintenance cost is greatly reduced, waste oil is automatically collected and recycled, and thus pollution is reduced.

The embodiment of the invention provides a method and system for identifying an empty parking space and a vehicle, and belongs to the technical field of parking space monitoring. The method comprisesthe steps of determining position information of a parking space corner point by adopting a visual detection method based on a parking space picture collected by a vehicle; Based on the position information of the parking space corner points and a preset calibration model, obtaining world coordinates of the parking space corner points; Comparing the world coordinates of the parking space corner points with the actual coordinates of the preset parking space corner points, and under the condition that the world coordinates of the parking space corner points are consistent with the actual coordinates of the preset parking space corner points, identifying the parking space corresponding to the parking space corner points as a preset parking space; And identifying the preset parking space as anempty parking space based on the change relationship between the ultrasonic data and the driving distance and the actual coordinates of the corner point of the preset parking space. According to themethod, the empty parking space in the preset parking space can be accurately and effectively detected in automatic parking or passenger-replacing parking, intelligent detection of the empty parking space is achieved, and therefore a vehicle can be accurately parked on the preset parking space.

The invention discloses a non-motor vehicle traffic behavior monitoring method and an illegal behavior detection system. The non-motor vehicle traffic behavior monitoring system comprises an active RFID tag, a detection area, a low-frequency exciter, an RFID base station, a camera and the like, wherein the active RFID tag is installed on a non-motor vehicle and preset with unique identity information corresponding to the non-motor vehicle; the detection area, the low-frequency exciter, the RFID base station, the camera are arranged in an area where illegal behavior monitoring is planned to beperformed; an antenna of the low-frequency exciter is arranged around the detection area along the edge of the detection area, when the non-motor vehicle enters the detection area, the active RFID tagis awakened by an awakening signal, and begins to broadcast identity information of the non-motor vehicle and antenna position information received from the antenna, and the RFID base station collects broadcast signals. Monitoring of non-motor vehicle traffic behaviors is realized based on information capable of identifying non-motor vehicle identities obtained from active RFID label broadcast signals by an RFID base station and visual evidences taken by a camera at the same time. According to the invention, identification and judgment can be carried out on variable and irregular driving routes of non-motor vehicles, and the identification rate of non-motor vehicle illegal behavior detection is higher.

The invention discloses a mechanical property testing device of a material testing machine. The mechanical property testing device comprises a vertical support seat and a base, wherein the base is fixedly arranged at the bottom of the vertical support seat; vertically arranged support posts are arranged at two sides of the top end of the base; a horizontally arranged support plate is arranged at the top end of each support post; an opening is formed in each support plate; the inner walls of two sides of each opening communicate with sliding rails; a plurality of fixing clamps for clamping test materials are connected to the inside of each sliding rail in a sliding manner; a transfer frame is arranged between the base and the support plates and is fixed at the top end of the base; a transfer mechanism is arranged on the transfer frame; a fixed seat is arranged at one side, close to the support plates, of the vertical support seat; a push rod motor is arranged at the top end of the fixed seat; an infrared sensor, a vertically arranged pressure lever and a first air cylinder are arranged at the bottom end of the fixed seat separately; the pressure lever is connected with an output shaft of the push rod motor; and a pressure head is arranged at one end, far away from the fixed seat, of the pressure lever via a thread. The mechanical property testing device is reasonable in design, the testing method is simple and convenient, the testing efficiency is improved, and the testing accuracy is high.

The invention discloses a product defect automatic detection platform and belongs to the field of product defect detection. The structure of the product defect automatic detection platform comprises apedestal, a rotary workbench, a fixed workbench, a loading mechanical arm, an unloading mechanical arm, a middle mechanical arm, camera combination and a camera adjusting device; the camera combination is arranged on the camera adjusting device; the camera combination comprises three sets; two sets are arranged on the left side of the camera adjusting device; one set is arranged on the right sideof the camera adjusting device; the rotary workbench and the fixed workbench are arranged on the left side and the right side of the pedestal correspondingly; the loading mechanical arm is arranged on the left side of the rotary workbench; the unloading mechanical arm is arranged on the right side of the fixed workbench; the middle mechanical arm is arranged on the front side of the rotary workbench and the fixed workbench; the camera adjusting device is arranged on the back side of the rotary workbench and the fixed workbench; and the rotary workbench, the loading mechanical arm, the unloading mechanical arm, the middle mechanical arm and the camera combination are electrically connected with a controller. The product defect automatic detection platform completely replaces manual detection, obviously improves the detection efficiency of the products and obviously increases the detection accurate rate of the products.

The invention discloses rail transit tunnel geological radar mobile intelligent detection equipment and an operation method. The working state of each rotary telescopic device is controlled by a console, the tail end of each rotary telescopic device is provided with a radar antenna detection device through a telescopic slideway device, the rotary telescopic device rotates under the control of theconsole, the working angle and the working pose of the radar antenna detection device installed on the telescopic slideway device are adjusted, and the fixed distance, which is required by detection,between the radar antenna and the tunnel lining wall is kept; each rotary telescopic device is further provided with a laser detection device, and obstacles on the surface of the tunnel lining are monitored in real time in the moving process of an engineering vehicle so as to avoid the obstacles and adjust the detection route. According to the invention, the laser detection result can be received,the detection path can be set, the working posture of the detection system can be intelligently adjusted, and intelligent detection is achieved.

The invention discloses a bearing defect detection device and a bearing defect detection method. The bearing defect detection device comprises a detection part, a loading part, an unloading part, a programmable controller and a PC host, wherein a detected bearing is conveyed to a specified position by the loading part, and then grabbed onto a detection position by a clamping jaw of the detection part; a CCD camera carries out picture acquisition, and then the clamping jaw grabs the detected bearing, overturns the detected bearing by 180 degrees, and places the detected bearing on the detectionposition; the CCD camera carries out picture acquisition again, and after the acquisition is completed, the clamping jaw places the detected bearing onto the unloading part; and the PC host processespictures shot by the CCD camera, and judges whether the detected bearing has defects or not. The bearing defect detection device detects the defects of the bearing on the basis of a visual identification system, is high in efficiency, facilitates to realizing automatic detection, and is capable of detecting the upper surface, the lower surface and the outer ring of the bearing at one detection station, and therefore is compact in structure and low in cost.

The invention discloses a bridge swivel construction intelligent control system which comprises a lifting swivel mechanism, a PLC control module and a remote control module. The lifting swivel mechanism is provided with a pier column and a beam body pouring platform, and the beam body pouring platform is used for pouring a rotary beam body. The pier column is used for supporting the rotary beam body in the lifting swivel process. The PLC control module is provided with a PLC and a touch screen, the PLC is connected with the touch screen, and the touch screen is provided with a data setting module, a display module, an automatic module and a manual module. The PLC is used for controlling the lifting swivel process of the rotary beam body. The remote control module is provided with an intelligent terminal and a database connected with the intelligent terminal, the intelligent terminal is wirelessly connected with the PLC control module, and all data and lifting swivel simulation data inthe lifting swivel process are stored in the database. The system has the beneficial effects that a new bridge installation mode is adopted, transport is convenient, a lifting rotary device can be recycled, and cost is saved.

The invention provides a transformer substation auxiliary facility detection control method and device. The method comprises the following steps of collecting environment information of a surroundingenvironment of a transformer substation through detection equipment, and converting the environment information into a data quantity collection value; comparing the data collection value with a presetwarning threshold value, and judging whether the data collection value is larger than the preset warning threshold value or not; if yes, judging that the current surrounding environment is in an abnormal state, and generating an abnormal state processing instruction; and starting an alarm, and starting auxiliary equipment. According to the detection control method and device, the real-time or regular computer-based intelligent detection of the surrounding environment of the transformer substation is realized, and the corresponding auxiliary equipment is controlled to adjust the surrounding environment for enabling the surrounding environment to be restored to be in a normal state, so that the normal operation of equipment in the transformer substation is guaranteed; the detection method is high in efficiency and high in speed; the detection data calculation is accurate; and the unattended control method greatly reduces the labor management cost.

The invention relates to a detection device, in particular to an intelligent tearing detection device for belt conveyors. The intelligent detection device comprises two belt conveyors and a blanking cabin mounted between the two belt conveyors, wherein a high definition camera is mounted above the blanking cabin; the monitoring range of the high definition camera is from the blanking position of the belt conveyor and the top of the blanking cabin; the high definition camera is connected with a computer through an intelligent video analyzer and an optical transmitter and receiver; an infrared detection light curtain is mounted on a rack between the upper belt and the lower belt in the belt conveyors below the blanking cabin; the infrared detection light curtain is connected with the computer through an electric control device; a warning device is mounted in the computer. Through the technical scheme, the intelligent tearing detection device has the characteristics of simple structure, convenience in mounting, high sensitivity, high response speed and the like, and after the intelligent tearing detection device is connected with the electric control device of the belt conveyor, the control of beforehand prevention and post-warning, parking and the like can be realized, so that the workloads of underground tour inspection personnel and ground monitoring personnel are alleviated, and intelligent detection is realized.

The invention belongs to the technical field of architectural decoration and discloses an intelligent automatic storing and taking wardrobe system with air replacement and treatment functions. The intelligent automatic storing and taking wardrobe system comprises a cabinet body, a storing and taking area arranged on one side of an inner cavity of the cabinet body, a clothes placement area arrangedon the other side of the inner cavity of the cabinet body, a heating and air supplying module arranged at the bottom of the cabinet body as well as a filtering exhaust module and an internal and external air replacement module which are arranged at the top of the cabinet body, wherein an automatic clothes hanging and taking structure is arranged in the storing and taking area; a rotating hoist chain conveying system is arranged in the clothes placement area; the modules are electrically connected with a master control module. The intelligent automatic storing and taking wardrobe system aims to realize intelligent automatic clothes storing and taking and air replacement of a wardrobe, can save much time for selecting and finding clothes, automatically replace humid and stale air in the wardrobe and automatically replace and treat harmful air in the wardrobe and the room where the wardrobe is located, is convenient and firm to mount and simple in structure, and meets the demands of people for intelligent products.

The invention relates to the technical field of ultrasonic nondestructive test, in particular to an automatic ultrasonic nondestructive test apparatus for dies and a control system and test control method thereof. The automatic ultrasonic nondestructive test apparatus for dies comprises a frame, an X-axis transmission device, a Y-axis transmission device and a test manipulator; the test manipulator comprises a connection seat connected with the Y-axis transmission device, a Z-axis transmission device, and a testing device; the testing device comprises a connection bar, a fixing plate and an ultrasonic test probe, as well as a probe clamp plate for fixing the ultrasonic test probe; a buffer spring is arranged between the probe clamp plate and the fixing plate; the part of the probe clamp plate close to the ultrasonic test probe is provided with a plurality of first proximity switches. The automatic ultrasonic nondestructive test apparatus for dies can test a material at high speed and is beyond traditional handheld ultrasonic single-point scanning in terms of reliability, automation level, testing operation stability and other technical indexes; benefits of the apparatus to the society involve both material testing and major social aspects, such as aviation, national defense and economy.

The invention provides a garbage throwing behavior detection method based on an urban management monitoring video. The method comprises the steps of firstly carrying out the pavement garbage detectionof the urban management monitoring video at intervals, rechecking the monitoring video in the former time if the pavement garbage is found, and analyzing the monitoring video to find a pedestrian whothrows garbage; and if no pedestrian throws the garbage, searching the pedestrian throwing the garbage in the video in the front of the surrounding camera, so as to detect the behavior of throwing the garbage in the monitoring video.