20results about How to "Realize intelligent detection" patented technology

The invention discloses a test method for a high-load heating tube for a mold, and belongs to the technical field of single-head electric heating tube detection. The method specifically comprises the following steps: S1, historical data acquisition: acquiring cold-state electrical performance data of single-head electric heating tubes with different specifications and under different working conditions; s2, historical data preprocessing: performing preprocessing including data cleaning, data normalization and data standardization on historical data to obtain a standardized data set; the test process design covers a full-period closed loop of cold state detection, hot state leakage current test, reliability test, secondary hot state leakage current test and secondary cold state detection, the electrical safety (leakage current control) under a high-load working condition is verified through the hot state test, and the reliability of an actual use scene is simulated through a rapid on-off test. Meanwhile, the appearance, temperature, gas release and other states of the heating pipe are monitored in real time, abnormal testing is terminated in time, safety risks are avoided, and it is ensured that the detection result can comprehensively reflect the actual use performance of the heating pipe.

The application discloses a contact line hard bending state detection method and device based on deep learning and a medium. The method comprises the following steps: acquiring a detection image containing a pantograph and a contact line which is shot in real time during train operation; locating a pantograph region from the detection image, and determining a contact line extraction region according to the pantograph region; extracting the contact line from the contact line extraction region to obtain a contact line image; inputting the extracted contact line image into a pre-trained hard bending state detection model to obtain a detection result output of whether the contact line exists hard bending, wherein the hard bending state detection model is obtained by training a deep learning model using an image data set, and each image data in the image data set contains the pantograph, the contact line and the labeling information of a hard bending region of the contact line with hard bending. The application has the advantages of simple implementation method, low cost, high detection precision and efficiency, strong flexibility and the like.

This invention belongs to the field of automotive assembly technology and discloses an automated production line and control method for double-sided machining of workpieces with dual spindles. It includes a flipping mechanism, a dual-spindle machining mechanism, a raw material conveying mechanism, a finished product conveying mechanism, a robot, and a workstation conveying mechanism. The machining devices of the dual-spindle machining mechanism are spaced apart on the chassis. The lifting platform of the flipping mechanism is located next to the chassis. A flipping gripper is fixedly mounted on the chassis and positioned above the lifting platform. The rotating mechanism of the flipping gripper drives the clamping mechanism to rotate horizontally by 180 degrees. Two spindle boxes are slidably connected to the upper part of the chassis. The spindle is located inside the spindle box, with its lower end extending out of the lower end of the spindle box and fixedly connected to a spherical positioning chuck. The robot is positioned between the raw material conveying mechanism, the finished product conveying mechanism, and the workstation conveying mechanism. This invention achieves automatic workpiece flipping, avoids positioning errors and clamping eccentricity, uses air blowing to clean foreign objects from the chuck, detects the airtightness of the positioning surface, prevents workpiece deformation, and extends the service life of the equipment.

The present application relates to the technical field of laser welding, and provides a visual detection method and device based on laser welding and a readable storage medium, the method comprising: controlling a galvanometer welding head to weld according to a preset standard welding image to obtain a plurality of welding image samples; comparing and analyzing each welding image sample with the standard welding image to obtain welding data of the welding image sample, and labeling unqualified welding sections in the welding data to obtain labeled welding data; obtaining welding process parameters of the unqualified welding sections in the welding image sample, and associating the welding process parameters with the welding data of the welding image sample to obtain training data; constructing and training a visual detection model; inputting a collected welding image to be detected into the trained visual detection model, and the visual detection model judging whether the welding image to be detected has unqualified welding sections. The technical scheme provided in the present application embodiment can effectively improve the detection efficiency of visual detection welding effect.

The present invention relates to the field of water content detection technology, and discloses a device and method for measuring the sensitive area of ​​a multi-section tubular water content sensor. The device for measuring the sensitive area of ​​a multi-section tubular water content sensor comprises: a measuring barrel, a lifting mechanism and a data collector; the interior of the measuring barrel is divided into a first space for placing the soil to be tested, a second space for placing a material with a fixed dielectric constant, and a third space for the soil water content sensor to move up and down; the first space is located in the second space, and the third space is located in the first space; the lifting mechanism is used to drive the soil water content sensor to move up and down, and the data collector is connected to the soil water content sensor signal. The device for measuring the sensitive area of ​​a multi-section tubular water content sensor directly observes the sensitive area of ​​the section tubular soil water content sensor through an experimental method, realizes the automatic and intelligent detection of the soil water content sensor, improves the detection work efficiency, and ensures the sensor is tested in a real soil sample environment.

The present application relates to a kind of vehicle speed detection methods based on outer pole face image, belong to the field of automatic driving.The method includes: S1: periodically capture the image of the road in front of vehicle, obtain time-space distance image;S2: the curve cluster surface of the time-space distance image obtained is divided into several parts;S3: the curve corresponding to each part obtained;S4: by its analytic differential, the speed curve of each part is obtained;S5: the generation of full interval speed curve, according to the displacement of feature point, the speed of vehicle is calculated.The present application is based on the principle of visual kinematics, using the image obtained by vehicle-mounted camera and distance sensor, the speed of vehicle is calculated by observing the motion of feature point in image.Compared with the existing speed detection method based on physical sensor, the method is lower in cost, but the principle is simple, and the accuracy is also higher.The method can be used alone, can also be combined with the data of other sensors, improve detection accuracy and stability.

The invention provides an intelligent household electrical appliance control method, electronic equipment, a storage medium and a program product, and belongs to the technical field of intelligent household electrical appliance control. The intelligent household electrical appliance control method is applied to the intelligent household electrical appliance, and the intelligent household electrical appliance comprises a panel, a burner assembly, a first temperature sensor and a second temperature sensor. The method comprises the following steps: in response to the fact that the current temperature of the cooker is detected to be within a first temperature range, judging the current state of the cooker according to the temperature variation detected by the first temperature sensor and the second temperature sensor; in response to the fact that the current state of the cookware is the preset cooking state, the overflow state of the cookware is further judged, and the power of the burner assembly for heating the cookware is controlled according to the overflow state of the cookware. Therefore, the overflowing state can be accurately determined, the accuracy of judging the overflowing state is improved, and then the pot heating power of the burner assembly can be controlled according to the overflowing state of the pot.

The invention provides an unmanned aerial vehicle attitude angle measurement method based on horizon line detection. The method comprises the following steps: defining horizon line key points; constructing an end-to-end horizon line key point detection neural network, wherein the end-to-end horizon line key point detection neural network comprises a backbone network, a transposed convolutional network and a self-attention module; predicting horizon line key point coordinates according to the end-to-end horizon line key point coordinate feature map; acquiring a horizon line according to the predicted horizon line key point coordinates; and the roll angle and the pitch angle of the unmanned aerial vehicle are obtained according to the imaging relation of the horizon line in the camera. The technical problem of low air alignment precision caused by difficulty in accurately acquiring the attitude of the micro inertial navigation system in an air flight scene in the prior art can be solved.

The invention discloses an acoustic detection system for non-disassembly of a railway wheel set bearing in a warehouse. The invention further discloses an acoustic detection method for the non-disassembly of the railway wheel set bearing in the warehouse. According to the invention, the wheel set operation sound is picked up; and a detection result is analyzed and output for a worker to judge whether the wheel set has defects or not (the wheel set is accelerated by means of a wheel set running-in machine, a proper distance is kept for the wheel set to be detected through a high-precision microphone sensor to collect sound signals, a wheel set bearing acoustic comparison oscillogram is generated, and the detector can judge whether bearing defects exist or not through the oscillogram). According to the invention, automation and intellectualization of the railway wheel set bearing maintenance process are realized, the operation safety is improved, the upgrading transformation process is accelerated, and the problems of misjudgment and missed judgment caused by strong subjectivity of existing manual detection are solved.

This invention relates to the field of motor operating status detection technology, and discloses a detection method, system, electronic device, and storage medium that combines motor feedback and torque threshold analysis. The method collects multi-dimensional operating data such as torque, current, speed, and temperature during motor operation, performs time-synchronized processing on the multi-source data, and extracts related characteristic parameters such as torque-current correlation coefficient, torque change rate, speed response delay, and phase difference. A dynamic torque threshold model is constructed based on sliding window statistics, and an adaptive detection threshold is generated by combining environmental correction and wear compensation mechanisms. A multi-source data fusion algorithm is used to calculate the comprehensive anomaly probability, enabling abnormal motor operating status determination and graded early warning. Simultaneously, an adaptive model update mechanism is introduced to continuously optimize the threshold model. This solution can improve the accuracy and stability of motor anomaly detection, reduce false alarm and false negative rates, and is suitable for motor condition monitoring and predictive maintenance in industrial scenarios such as industrial robots, new energy vehicles, and CNC equipment.

The present application relates to the field of intelligent management, and specifically to an intelligent management system for chemical production based on data analysis. It uses artificial intelligence technology based on deep learning to analyze the time-frequency characteristics of the operating vibration signal of the production equipment, mines the waveform semantic characteristics of the vibration signal, and performs dynamic clustering analysis on it through the attention mechanism to identify the abnormal vibration mode of the production equipment, thereby realizing intelligent detection of the operating status of the production equipment. In this way, the accuracy and robustness of abnormality detection can be effectively improved, and the complex changes in the operating status of equipment in the chemical production process can be better adapted, thereby improving production safety and efficiency.

The application discloses a fluid pipeline leak detection robot and relates to the technical field of pipeline leak detection.The robot comprises a whole-circle clamping ring arranged outside a pipeline, a detection sensor arranged on the whole-circle clamping ring, a driving mechanism arranged on the whole-circle clamping ring and used for driving the detection sensor to rotate circularly with the center of the whole-circle clamping ring as the center, a self-propelled power device used for moving the whole-circle clamping ring on the pipeline, a sliding mechanism used for moving the whole-circle clamping ring on the fluid pipeline and an automatic clamping device.The robot can realize automatic flaw detection on the circumferential outside of the pipeline, so that an operator can judge the damaged position outside the pipeline in time and accurately, and the whole-circle clamping ring can automatically clamp and separate the pipeline, intelligent recognition is realized, and the intelligent automation degree of the robot is greatly improved.

The embodiment of the invention provides an addition transformer, and relates to the technical field of electronic power. The addition transformer comprises a plurality of annular conductors; the multiple groups of input windings are in one-to-one correspondence with the annular conductors, and the annular conductors penetrate through the first axial cavities of the input windings; and the plurality of annular conductors all penetrate through the second axial cavity of the output winding, and the plurality of annular conductors are not intersected with one another. According to the adder provided by the embodiment of the invention, the performance of the adder transformer is improved from multiple dimensions such as capacity expansion, multi-stage voltage output providing, current / voltage ratio flexible adjustment, waveform optimization, voltage harmonic reduction and the like, the power supply requirements under multiple working conditions are met, and reliable electric energy conversion is provided for various high-power alternating-current transmission devices.

The invention relates to the technical field of machine vision, and discloses a pre-packaged sauced beef vacuum degree detection method based on machine vision, and the method comprises the steps: carrying out the effective region extraction of an original image of pre-packaged sauced beef, and obtaining a to-be-analyzed image; performing high-frequency detail enhancement on the to-be-analyzed image to obtain an enhanced grayscale image, and performing adaptive division to obtain a vacuum defect sensitive area; traversing the vacuum defect sensitive area, extracting image surface local texture features of the pre-packaged sauced beef, and determining vacuum degree distribution features; performing texture morphological analysis on the vacuum degree distribution characteristics to obtain vacuum degree morphological characteristic description; performing structural similarity comparison on the vacuum degree morphological feature description and a preset reference feature description to obtain morphological similarity, and judging whether the morphological similarity meets a qualification standard or not to output a vacuum degree detection result; the efficiency of the pre-packaged sauced beef vacuum degree detection method based on machine vision can be improved.

The present invention discloses a magnetic resonance detection system and method for bile and pancreatic duct imaging, which belongs to the technical field of bile and pancreatic duct imaging, and comprises an image analysis module and an image detection module; the image analysis module is used to analyze a target image, determine various doubtful problems corresponding to the target image, and calculate problem evaluation values ​​corresponding to the doubtful problems; determine detection interference problems according to the problem evaluation values; the image detection module is used to perform bile and pancreatic duct disease detection on the target image, and determine various target analysis images; perform bile and pancreatic duct disease recognition on the target image and various target analysis images respectively, obtain various disease recognition results, mark the disease recognition result corresponding to the target image as a baseline disease result, and mark the disease recognition result corresponding to the target analysis image as an auxiliary disease result; perform consistency evaluation on the baseline disease result of the target image according to the auxiliary disease results of each target analysis image, and obtain corresponding consistent evaluation values; and mark the consistent evaluation values ​​on the target image.

The invention relates to a steam quality online detection system. The steam quality online detection system comprises a non-condensable gas content detection unit, a superheat degree detection unit, a dryness detection unit and a gas inlet pipe used for outputting steam to be detected, the non-condensable gas content detection unit comprises a first condenser and a non-condensable gas detector which are communicated with each other, and the first condenser is communicated with the gas inlet pipe and used for condensing the steam to be detected; the non-condensable gas detector is used for detecting the content of non-condensable gas in the input material conveyed by the first condenser; the superheat degree detection unit comprises a first branch channel communicated with the air inlet pipe, and the first branch channel is provided with a first temperature detector for detecting the superheated steam temperature value of the steam to be detected; the dryness detection unit comprises a gas-liquid mixer output end and a second condenser input end which are communicated with each other, a first input pipe which is communicated with the first branch channel and the gas-liquid mixer, and a circulating pipeline which is communicated with the output end of the second condenser and the input end of the gas-liquid mixer. Through the arrangement, the intelligent detection of the steam quality is realized.

This invention relates to a method and system for detecting the condition of engine ground test benches, specifically to a method and system for intelligent detection of the condition of pneumatic valves on test benches. To address the shortcomings of existing valve internal leakage detection technologies, such as sensitivity to temperature interference, high failure rate for minor leaks, limited correlation analysis, and high deployment costs, this invention provides an intelligent detection method for the condition of pneumatic valves on test benches. This method includes data acquisition and preprocessing; graded assessment of cylinder health status based on preprocessed data; detection of valve internal sealing status based on preprocessed data; and output of cylinder health status and valve internal sealing status to obtain intelligent detection results for the pneumatic valve condition. Furthermore, a test bench intelligent detection system for implementing the above method is also provided.

The present invention provides a sand spreading device and a sand position detection method thereof, the sand spreading device comprises a sand box and a sand position detection component; a sand injection port connected to a sand injection pipe is provided on the sand box, an exhaust port is provided on the top of the sand box, and a sand outlet connected to a sand spreader is provided at the bottom; the sand position detection component comprises a controller and a first capacitance sensor and a second capacitance sensor arranged up and down; the controller is arranged on the sand box, and is respectively connected to the first capacitance sensor, the second capacitance sensor and the sand spreader; the first capacitance sensor and the second capacitance sensor are both arranged in the sand box, and one end of both is connected to the box body of the sand box, and the other end is a sand position detection end, and both are located on the central axis of the sand outlet. The sand position detection method comprises sand injection and sand spreading. The present invention can solve the problems that the sand injection pipe cannot be assembled on the sand box, the sand particles are compacted, and the sand position detection has false alarms.

The present invention provides a fluid transport mechanism and device based on a self-driven cavity, including a telescopic chamber, wherein the telescopic chamber is provided with a fluid inlet and a fluid outlet, and when the fluid enters the telescopic chamber through the fluid inlet, the volume of the telescopic chamber increases, thereby generating a driving force for driving the telescopic chamber to retract, wherein the driving force comes from the telescopic chamber itself; and / or the driving force comes from a force-applying mechanism connected to the telescopic chamber. In the present invention, the telescopic chamber adopts a bellows or a deformable material embedded with an elastic medium, so that the bearing pressure is large during the expansion of the telescopic chamber, which greatly reduces the risk of the telescopic chamber bursting, improves product quality, and prolongs the service life of the equipment. In addition, elastic parts can be added inside or outside the telescopic chamber to increase the self-ejection pressure of the fluid inside the telescopic chamber, thereby improving the practicality of the equipment.

The utility model discloses a gait analysis accessory which comprises a shell, a gait detection module, a first wireless transmission module and an energy storage module are arranged in the shell, the gait detection module is used for detecting gait information, and the first wireless transmission module is connected with the gait detection module to wirelessly send the gait information. The energy storage module supplies power to the gait detection module and the first wireless transmission module; the statistical system comprises a main control box terminal and a plurality of gait analysis accessories, the main control box terminal comprises a box body, a second wireless transmission module, a power module, an electric connecting piece and an identity recognition module are arranged in the box body, and the second wireless transmission module is in wireless signal connection with the first wireless transmission module. According to the gait analysis accessory and the statistical system, intelligent detection and gait information statistics can be realized, the personnel demand is reduced, and the training effect is optimized.