10results about How to "Improve inspection effect" patented technology

This invention discloses an auxiliary hoisting device for a power line inspection drone, relating to the field of power line inspection technology. The invention includes a hoisting mechanism composed of hoisting arms symmetrically arranged on both sides of a platform. Fixed rods are symmetrically arranged on both sides of the hoisting arms. A fixed seat is fixedly connected to the end of the hoisting arm away from the platform. A connecting plate is fixedly connected to the inner wall of the fixed seat. A placement mechanism is arranged on the side of the connecting plate away from the fixed seat. The placement mechanism includes a housing, which is cone-shaped. A camera used for power line inspection is placed inside the housing. The housing has a streamlined outer surface, which reduces air resistance when the drone carries the housing, thus avoiding affecting the drone's flight efficiency. The fixed rods symmetrically arranged on both sides of the hoisting arms improve the connection strength between the hoisting arms and the platform, preventing the hoisting arms from bending due to air resistance, and thus preventing the housing from swaying and affecting the inspection effect.

The application relates to an unmanned aerial vehicle intelligent flight method and system based on energy data analysis, and relates to the field of energy management technology.The method comprises the following steps: acquiring a required inspection position; constructing a monitoring time window and acquiring a monitoring wind receiving vector of a wind measuring point in the monitoring time window; determining a standard wind receiving vector according to the monitoring wind receiving vector; constructing a simulated inspection path according to a starting point and the required inspection position, and constructing a historical time window; determining a path single-point vector of each point on the simulated inspection path according to the standard wind receiving vector in the historical time window, and determining a required charging position according to the path single-point vector, and constructing a simulated inspection task according to the required charging position and the simulated inspection path; determining a task suitability coefficient according to the simulated inspection task, and defining the simulated inspection task with the largest task suitability coefficient as a use inspection task, and controlling the unmanned aerial vehicle to fly according to the use inspection task. The application has the function of improving the unmanned aerial vehicle inspection effect.

This utility model discloses a single-track liftable coal conveyor belt inspection system, relating to the field of coal conveyor belt inspection technology. It includes an inspection box and a traveling track. The inspection box is equipped with a traveling mechanism, and an electric telescopic rod is fixedly installed inside the inspection box. An inspection camera body is fixedly installed at the bottom of the electric telescopic rod. This single-track liftable coal conveyor belt inspection system, through the combined use of cleaning components and a cleaning structure, sprays cleaning fluid in a ring onto the inspection camera body, covering it with the cleaning fluid. Simultaneously, a drive motor drives a rotating rod to rotate, which in turn drives an external gear ring to rotate, causing a rubber scraper to rotate around the outside of the inspection camera body. The rubber scraper cleans away coal dust from the outside of the inspection camera body, ensuring clear images captured by the camera and improving inspection effectiveness.

The utility model discloses an inspection device for a steel bar truss, and belongs to the field of steel bar truss inspection. The inspection device for the steel bar truss comprises a base, a first sliding block is arranged in the middle of one end of the base, a second sliding block is arranged on one side of the outside of the first sliding block, and a laser head is arranged at the front end of the second sliding block. According to the utility model, the problem that a gap exists between the lowermost end of the truss and the placing position of the existing truss height measuring device, so that the measurement accuracy is influenced is solved, and the highest point and the lowest point of the steel bar truss can be detected through the supporting of the supporting sheet and the detection of the laser head; in the detection process, the pointer can be in contact with the sliding frame to identify the highest position of the steel bar truss, the pointer can identify the lowest position of the steel bar truss along with longitudinal movement of the laser head, a user can directly know the highest point and the distance between the lowest points through the scale, and the detection accuracy is improved.

The invention discloses a CT (Computed Tomography) nuclear magnetic resonance head fixing device, which belongs to the technical field of inspection auxiliary equipment, and comprises a CT nuclear magnetic resonance machine body, the fixing mechanism comprises a supporting frame fixedly connected to the detection table, a fixing box slidably connected to the interior of the supporting frame and two adjusting clamping plates slidably connected to the top of the fixing box, and an inner adjusting piece capable of driving the fixing box to move front and back is installed on the inner left side of the supporting frame; an outer adjusting part matched with the inner adjusting part is installed on the outer left side of the supporting frame, the outer adjusting part can drive the two adjusting clamping plates to move synchronously, the fixing box moves front and back to achieve fine adjustment of the head, and the adjusting clamping plates move synchronously to achieve clamping and fixing of the two sides of the head. The device has the technical effects that the head can be finely adjusted front and back, accurate positioning can be achieved without moving the body of a patient, and clamping and fixing are convenient and fast.

The invention belongs to the technical field of detection, and particularly relates to a power transformer no-load current detection device, which comprises a detection box, a box cover, a fixed seat, a control panel and a lock catch mechanism, and is characterized in that one side of the box cover is provided with a bunching mechanism; the detection box is movably connected with the box cover, the detection box and the box cover are closed through a lock catch mechanism, a detection opening is formed in one side of the box cover in a penetrating mode, the fixed seat is arranged in the detection box, a notch is formed in the top of the fixed seat, the control panel is arranged in the notch, and the control panel is arranged in the notch. A detection switch and a control button are arranged at the two ends of one side of the control panel respectively. According to the invention, the plurality of detection lines can be independently fixed and constrained, so that the detection effect of the equipment on the power transformer is improved, and the influence on the detection of the no-load current of the power transformer due to mutual interference of the plurality of detection lines during detection is prevented.

The invention relates to the technical field of fault identification, and provides a wind power plant unmanned aerial vehicle inspection data fault identification system based on artificial intelligence, which comprises an unmanned aerial vehicle, a server, a data acquisition module, an interaction module, an analysis module, a decision module and an inspection control module, the data acquisition module acquires appearance image data of a wind driven generator in a wind power plant, the interaction module interactively transmits the appearance image data acquired by the data acquisition module and ground data receiving equipment, and the inspection control module acquires the position of the wind driven generator and real-time position data of an unmanned aerial vehicle. The data acquisition module acquires the position of the wind driven generator, evaluates the inspection route of the unmanned aerial vehicle according to the position of the wind driven generator and the real-time position data of the unmanned aerial vehicle, adjusts the acquisition posture of the data acquisition module according to the evaluation result, and analyzes the wind driven generator according to the appearance image data acquired by the data acquisition module to form an analysis result. And the decision module evaluates the state decision of the wind driven generator according to the analysis result.

The application relates to the technical field of electric digital data processing, and discloses a power inspection task unloading state coding method and system, which comprises the following steps: acquiring multi-modal original observation data collected by an inspection terminal in a power inspection task, and identifying key components and state information of a target power equipment based on an image analysis model; performing defect analysis on the key components to generate an evaluation result containing defect types and quantitative severity; fusing task calculation attributes, communication environment parameters and equipment resource states to construct a multi-dimensional state vector; performing normalization and vectorization processing on the dimensional features of the multi-dimensional state vector to output a state space representation for task unloading decision-making of a reinforcement learning intelligent agent. The application solves the problems of disconnection of general state coding, inaccurate decision-making and untimely response in the prior art, and achieves the purposes of precise decision-making, targeted response and energy efficiency improvement.

The utility model relates to photovoltaic module inspection device field, concretely relates to a kind of for perovskite photovoltaic module's inspection device, for the flatness inspection of perovskite photovoltaic module, including bottom plate, bottom plate top rear side vertical fixed with support plate, support plate top end is vertically fixed with top plate, the lower plate is fixed with on the top plate by lifting assembly, the inspection assembly is fixed with on the lower plate by adjusting assembly, the clamping assembly for positioning perovskite photovoltaic module is fixed in the bottom plate top, the utility model has the beneficial effect that: perovskite photovoltaic module four end top can be pressed simultaneously, the difference range of pressure sensor is used to judge whether the flatness of perovskite photovoltaic module is qualified, without operating personnel manual operation, effectively reduce operating personnel workload, and greatly improve inspection effect, subtle edge lifting can also be normally inspected, it is favorable to control product quality, suitable for use widely.

The application discloses a kind of based on embodiment intelligent large model driving's inspection autonomous learning method, device, equipment and medium, it is related to artificial intelligence technical field, method includes: control multi-sensor acquisition current inspection scene original data and extract feature data, original data includes scene data and / or equipment state data;Feature data and the priori knowledge matching of energy inspection association of light model;When similarity is less than preset threshold, trigger autonomous learning, generate new inspection operation rule for unknown scene, or generate new fault judgment basis for unknown fault;Based on matching result or autonomous learning result, output action instruction;Inspection robot executes instruction and collects entity interaction feedback data;Calibrate action according to feedback data, simultaneously feedback data, new rule or new criterion are uploaded to cloud, and incremental update is carried out to large model, and learning closed loop is formed.The application improves the flexibility and intelligent level of inspection.