86results about How to "Achieve convergence" patented technology

A rigid aircraft predetermined time adaptive neural network attitude stabilization method comprises the following steps: establishing kinematics and dynamics models of a rigid aircraft system, introducing a hysteresis quantizer to reduce buffeting in a quantized signal, and estimating and compensating lumped uncertain items of the system by using a neural network; a virtual controller is designed based on an inversion recursion idea, and the problem of controller singularity caused by derivation of the virtual controller is avoided; on the basis, a preset time adaptive neural network attitude controller is designed. According to the method, under the condition that inertia uncertainty, external interference and quantitative input exist, the rigid aircraft attitude is converged to the neighborhood near the original point within the preset time, and the upper bound of the minimum convergence time can be predetermined by adjusting a simple parameter.

The invention discloses a decentralized differential game cooperative guidance method for a missile cluster under a switching communication topological structure, and the method comprises the steps: introducing a virtual leading missile-slave missile architecture, enabling each missile to construct a virtual leading missile from an initial position, enabling nodes in a simplified virtual leading missile group system to interact through the state information of a topological structure, coordinating a virtual state, and achieving the cooperative guidance of the missile cluster under the switching communication topological structure. And generating a virtual consensus state track so as to realize decentration control. Communication topological structure switching is considered, an optimal control scheme for tracking an expected trajectory is solved in combination with a differential game theory and self-adaptive dynamic programming, and a network weight updating mechanism is designed in the process of solving an optimal control strategy for a nonlinear system line. According to the scheme, the average residence time limiting condition of switching signals is put forward, hypotheses and conditions needing to be met by part of parameters and variables are given, under the scheme, the designed multi-Lyapunov function can achieve exponential convergence, and the stability performance of a missile cluster using the guidance scheme under the topology switching condition is guaranteed.

The invention discloses a hydraulic arm safety control method and device based on parallel learning and a high-order CBF, and the method comprises the steps: building a kinetic equation of a hydraulic mechanical arm through a Lagrange method, integrating unmodeled dynamics, structural parameter change and external interference into an uncertain item, and describing the generalized uncertainty of the uncertain item in a linear parameterization form; for the problem of insufficient excitation in a complex environment task, a parallel learning mechanism is introduced, and historical data and real-time data are combined to realize parameter identification. For high relative order safety constraints (such as obstacle distance constraints and joint limiting constraints) in a task space, an obstacle function family is constructed. A dynamic error buffer function is introduced, and a high-order adaptive control barrier function condition is designed. The high-order self-adaptive control obstacle function constraint is embedded into a real-time quadratic programming solving problem, input obtained through optimization solving can keep the track precision, meanwhile, a joint instruction is automatically corrected to prevent constraint failure, and minimum intervention type safety control is achieved.

The invention relates to the technical field of amorphous zirconia corundum bricks, in particular to an amorphous zirconia corundum refractory brick and a preparation method thereof.The amorphous zirconia corundum refractory brick comprises, by weight, 60-70 parts of alumina powder, 25-35 parts of zircon sand, 5 parts of additives and 11-13 parts of binder.The preparation method comprises the steps of mixing, pouring, drying in the shade and baking. The components of the amorphous zirconia corundum refractory brick are adjusted, silica sol is added as a binder, and one or more of a binder additive, a water reducer additive and a dispersant additive is / are selected as an additive, so that alumina powder and zircon sand are dispersed more uniformly and combined more tightly; and in the preparation process, the green bricks are heated and baked by utilizing a transformed and innovated trolley furnace, the heating is uniform, and the formed amorphous zirconia corundum refractory brick is compact in structure, high-temperature-resistant, corrosion-resistant and permeation-resistant.

The invention discloses a specified time control method and device, electronic equipment and a storage medium, and the method comprises the steps: setting a displacement vector, a speed vector, target position information and target speed information of a mechanical arm; the displacement vector, the speed vector, the target position information, the target speed information and preset control time are input into a preset time controller, a control signal is output, the preset time controller is established based on a preset projection strategy and a PD controller, and the preset projection strategy is used for establishing connection between an infinite time domain and a finite time domain; and controlling the mechanical arm to perform dynamic trajectory tracking according to the control signal. Thus, real-time target position information and target speed information are introduced through the PD controller, dynamic trajectory tracking can be achieved, asymptotic stability of the mechanical arm is controlled, meanwhile, time in the infinite time domain is mapped to preset control time in the finite time domain through the preset projection strategy, and convergence in the preset control time is achieved.

The invention relates to a composite adaptive preset time attitude fault-tolerant control method for a rigid aircraft, which comprises the following steps of: constructing a rigid aircraft kinematics and dynamics model based on corrected Rodrigues parameters, and considering an actuator fault problem in the model; a virtual controller in a hyperbolic tangent form is constructed, so that the problem of singularity of the controller caused by derivation of the virtual controller is avoided; a fuzzy logic system is adopted to approach a nonlinear uncertain item of the system, and an adaptive law is designed to estimate the upper bound of composite interference of the system; on the basis, a composite self-adaptive preset time attitude fault-tolerant controller is designed. According to the method, under the conditions of uncertainty of rotational inertia, external interference and actuator faults, the rigid aircraft attitude is converged to the neighborhood near the original point within the preset time, and the upper bound of the minimum convergence time can be predetermined by adjusting a simple parameter.

The invention discloses a design method capable of giving consideration to both toughening and crack path controllability for a brittle material, and belongs to the technical field of fracture mechanics and artificial intelligence crossing, and the method comprises the steps: employing an input coding method based on space-response double-domain fusion to carry out feature extraction; introducing a channel attention mechanism to perform weighted fusion on the extracted double-domain features, and generating prediction results for different key tasks; evaluating the reliability of a prediction result by adopting a phase field verification and closed-loop adaptive optimization mode, and carrying out iterative training and optimization on the neural network; and taking the optimized neural network as a fitness evaluation function of double-target genetic optimization, and performing multi-target optimization on defect generation parameters. According to the invention, through fusion of the spatial domain and the response domain, geometric morphology and dynamic response characteristics are cooperatively extracted, and the prediction precision of complex fracture behaviors is improved; through non-dominated sorting multi-objective optimization under physical constraints, a high-toughness and path-controllable optimal solution is output, and brittle materials are pushed to cross an active controllable fracture design.

The invention requests to protect a reinforcement learning mixing method applied to assembly sequence planning, the assembly sequence planning can be essentially understood as a sorting of product parts, the excellent assembly sequence can shorten the production cycle of products, and the production cost is reduced. In the invention, a reinforcement learning algorithm, i.e., a Greedy-QS algorithm, which combines a Q-learning algorithm and a Sarsa algorithm is provided to solve the problem of assembly sequence planning. In the work of the method, firstly, the to-be-assembled product is reasonably abstracted into a mathematical model expressed by several Boolean matrixes, the complexity of the assembly model is reduced, the operability of the algorithm for the assembly sequence planning problem is improved, and then the optimal solution is solved by using the Greedy-QS algorithm. Experiments prove that compared with a Q-learning algorithm, a Sarsa algorithm and a Q-SARSA algorithm, the Greedy-QS algorithm has a faster convergence speed in the assembly sequence planning problem, the obtained reward value of the optimal assembly sequence is higher, and the advantages of the Q-learning algorithm and the Sarsa algorithm are both achieved.

The embodiment of the invention provides an alarm method and device. The method comprises the steps that alarm information is acquired; in response to the fact that the alarm information exists in an active queue, an end timestamp of the alarm information in the active queue is prolonged, the active queue is used for storing the alarm information in an active state, and the end timestamp is set based on a start timestamp when the alarm information is stored in the active queue; updating the active queue based on a comparison result of an end timestamp and a current timestamp of each piece of alarm information in the active queue; and based on a preset notification condition, notifying the alarm information in the updated active queue. According to the method, the convergence of the alarm information is realized, and the problem of alarm flooding is avoided.

The invention relates to an analytical calculation method for axial magnetic pulling force of an electric propulsion conical permanent magnet motor of an electric aircraft. A segmented equivalent method and an equivalent magnetic network method are combined, a conical motor is equivalent to a multi-segment cylindrical motor, three-dimensional modeling is converted into two-dimensional section modeling, the calculation complexity is reduced, meanwhile, the motor section change, the magnetic circuit saturation influence and the specific distribution of an air gap magnetic field are fully considered, the calculation accuracy is close to that of a finite element method, and the calculation efficiency is improved. The calculation speed is obviously higher than that of a finite element method. According to the method, the magnetic field distribution is prevented from being predicted in advance before modeling, and the modeling thought is simplified. Meanwhile, according to the method, grid subdivision is simplified, a quadrilateral grid in a standard shape is constructed as much as possible, grid direction magnetic conductance and branch magnetic conductance can be calculated through a unified formula, and modeling efficiency is improved.

The invention discloses a multi-source domain rolling bearing fault diagnosis method and system based on a diffusion model. The diagnosis method comprises the steps that rolling bearing vibration signals under different rotating speed working conditions are collected; in the forward process of the diffusion model, converting a source domain label into a one-dimensional vector, and adding noise to destroy original distribution to obtain yT approximate to Gaussian distribution; replacing yT with a Gaussian distribution variable # imgabs0 # in a reverse process, learning noise distribution characteristics added in forward distribution through a noise prediction network, denoising # imgabs1 # step by step to obtain # imgabs2 # in the same distribution as y0, inputting source domain data into the noise prediction network to extract data characteristics, inputting target domain data into the noise prediction network, and outputting the target domain data into the noise prediction network; global noise priori and local noise priori corresponding to the target domain data are obtained; and inputting source domain data and target domain data into a noise prediction network, mapping source domain data features to a target domain by using a multi-source domain adaptive algorithm, learning noise distribution features related to the target domain data, and gradually denoising # imgabs3 # to obtain a fault type of the target domain data.

This application relates to the field of new energy vehicle charging equipment technology, and discloses a multifunctional mobile vehicle-mounted charging device, including a carrier vehicle. A battery pack and charging module are installed inside the vehicle's cargo compartment. A slide rail is fixedly connected to the top of the cargo compartment, and a support frame is slidably connected to the slide rail. An air extraction component is fixedly connected inside the support frame to extract air from inside the cargo compartment to the outside, thereby accelerating the ventilation efficiency between the inside and outside of the cargo compartment. The bottom end of the support frame facing the rear door of the cargo compartment is connected to the rear door of the cargo compartment via a connecting rod, and the top end is hinged to one end of a drive arm. By directly transmitting the opening action of the rear door of the cargo compartment to the support frame via the connecting rod, the support frame and the air extraction component are driven to slide out of the cargo compartment along the slide rail. This transforms the necessary action of opening the door into the driving force for the deployment of the cooling system and wiring components. The device is ready without additional operating steps, and the linkage process is stable and reliable.

The utility model relates to pharmaceutical equipment technical field especially relates to a kind of powder accumulation prevention wall cleaning device of spray drying tower.It is a kind of powder accumulation prevention wall cleaning device of spray drying tower, including main part, limiting screw rod, locking knob, sliding sleeve, first pivot, folding rod, brush and hinged rod, main part bottom fixed connection has limiting screw rod, limiting screw rod is threadedly connected with locking knob, locking knob bottom periphery fixed connection sliding sleeve, limiting screw rod lower end rotationally connects first pivot, first pivot periphery is cross-distributed rotationally connected with folding rod, folding rod outer end is all fixedly connected with brush, and each folding rod outer side top and sliding sleeve lower periphery between rotationally connected with hinged rod.The utility model is moved up and down along limiting screw rod by rotating locking knob and driving sliding sleeve, realizes the unfolding and folding of folding rod, improves the operation convenience and maintenance efficiency of equipment, reaches the effect that it is easy to operate and efficiently to complete drying tower inner wall cleaning.

The present invention discloses a dual-arm operation task learning method and system based on a large model, belonging to the field of neural network learning and robotics technology. The method includes receiving a task environment diagram and task description information for dual-arm operation, inputting the task environment diagram and task description information into a large visual language model, and decomposing them into a plurality of subtasks; determining a reward function according to the task description information, task perception space information and action space information corresponding to each subtask, and training based on a reinforcement learning model to construct a corresponding subtask model, and the subtask model is used to complete each subtask respectively; according to the operation sequence of a plurality of subtasks, calling a plurality of subtask models in sequence to perform dual-arm operation, and collecting a dual-arm trajectory data set, learning the dual-arm trajectory data set through an imitation learning algorithm, and obtaining a dual-arm operation strategy. The present invention realizes the learning of complex dual-arm operation tasks and improves the robustness of the operation strategy.

This invention belongs to the field of sound-generating device technology, specifically a directional sound-generating device and its manufacturing process. It includes a folding mechanism, a height adjustment mechanism located below the folding mechanism, a rotating mechanism located at the top of the folding mechanism, an angle adjustment mechanism located at the top of the rotating mechanism, and a mounting mechanism located above the angle adjustment mechanism. A directional sound-generating body is fixed above the angle adjustment mechanism via the mounting mechanism. The rotating mechanism includes a fixed base, with a second motor fixedly connected to the left side of the top of the fixed base. A first gear is fixedly connected to the output end of the second motor, and a second gear is meshed with the right side of the first gear. This invention achieves lateral adjustment of the sound-generating device by controlling the rotation of the first gear with the second motor, which in turn drives the second gear to rotate the rotating frame. Vertical adjustment of the sound-generating device is achieved by controlling the up-and-down movement of the mounting frame with a telescopic rod. This solves the problem of traditional sound-generating devices requiring manual adjustment to change the direction of the sound source output, which is labor-intensive.

This application relates to a method, apparatus, and measurement system for dynamic measurement of assembly data. The measurement system includes a moving crossbeam and multiple calibration targets, with a 3D scanner and a laser tracker mounted on the moving crossbeam. The method includes: controlling the moving crossbeam to move to a measurement pose; positioning multiple calibration targets using the laser tracker to construct a geodetic coordinate system and tracking and determining the real-time pose of the 3D scanner in the geodetic coordinate system; controlling the 3D scanner to move and scan to obtain reference point cloud data and key area point cloud data of the assembly workpiece, and establishing the point cloud correlation between the two, establishing a workpiece coordinate system based on the reference point cloud data; based on the workpiece coordinate system, real-time pose, and point cloud correlation, mapping the key area point cloud data to the geodetic coordinate system and performing error correction; and generating an assembly deviation map based on the deviation between the corrected actual measurement data and the expected measurement data. This method can improve the cycle time efficiency and assembly accuracy pass rate of a pulsed assembly production line.

The application relates to the technical field of point cloud data processing, and specifically discloses a UAV point cloud original piece data processing system with a grading naming function; the system comprises the following modules: a boundary division module generates a rectangular boundary suitable for a terrain and screens a to-be-graded original piece; a grading identification module constructs geometric constraints based on a projection distance, completes tower distribution through extreme value judgment and parallel scene processing rules; a naming adaptation module integrates multi-source data to construct a scene feature vector, divides a risk range through clustering, realizes differential naming by adopting multi-source filling and normalization sorting; a feedback checking module locates a preferential analysis interval through deviation analysis, constructs a space neighborhood group and judges a high-risk area, and replaces an original algorithm to complete grading renaming and closed-loop checking by adopting a space index-hash mapping method; the application realizes dynamic optimization of point cloud grading naming, improves grading precision and naming compliance, and provides data support for power transmission line operation and maintenance.

The utility model provides a novel antifouling noise-reduction easy-to-clean protective cover for a cement mortar jolting table, which comprises a cover body, a lining cover is sleeved in the cover body, a sound insulation cotton layer is filled between the lining cover and the cover body, an inner container is sleeved in the lining cover, the inner container and the lining cover are fixedly mounted through a positioning knob, and the inner container is provided with a sound insulation cotton layer. Positioning holes are formed in the two sides of the interior of the lining cover, the positioning holes are in butt joint with the positioning rotary knobs in a matched mode, and a movable assembly is assembled at the bottom of one side of the cover body; the lining cover and the cover body are installed and fixed through a positioning part. The lining cover is arranged on the inner side of the sound insulation cotton, and the inner container is arranged on the inner side of the lining cover, so that slurry can be effectively prevented from splashing, the cleanliness of the sound insulation cotton is guaranteed, and the service life of the sound insulation cotton is prolonged; the arrangement of the lining cover and the inner container can further improve the sound insulation effect, and the noise decibel can be effectively reduced.

The present invention relates to the field of building construction technology, and discloses an integrated decoration structure of a lightweight partition wall and a concrete beam and a construction method thereof, comprising a partition wall body and a concrete beam, wherein the partition wall body is provided with longitudinal ribs, a concrete floor slab is provided on the top of the concrete beam, a circle of ecological panels is provided around the outer side of the concrete beam, the ecological panels are arranged in an open-top structure, the top of the ecological panels is abutted against the bottom wall of the concrete floor slab, the left inner wall of the ecological panel and the left wall of the concrete beam, and the right inner wall of the ecological panel and the right wall of the concrete beam are connected together by setting a first connecting component, an installation notch is provided on the bottom outer wall of the ecological panel, a second connecting component for connecting with the longitudinal ribs is provided in the installation notch, and the partition wall body is connected to the concrete beam through the connection between the longitudinal ribs and the second connecting component; the present invention has the characteristics of simple installation structure, shortened installation time and beautiful appearance.

The invention relates to the technical field of solar energy. The multifunctional solar radar velocimeter comprises a solar panel and an adjusting device connected with the bottom of the solar panel, the adjusting device integrates a driving mechanism, a sliding mechanism and a reinforcing mechanism, and the placing angle and the unfolding state of the solar panel can be adjusted so that the light energy absorption efficiency can be improved. The driving device drives the solar panel to rotate through gear transmission so as to adapt to sunlight in different directions; the sliding device drives the solar panel to be stably unfolded or folded by means of transmission of a bevel gear, a rack and the like, the light receiving area is increased, and various installation spaces are adapted. The reinforcing device is locked and fixed to the clamping structure through the tightening assembly, and external force is resisted to prevent loosening and deviation. The three parts work cooperatively, the problems that existing equipment is inconvenient to adjust, unstable in fixation, low in integration and the like are solved, the equipment operation stability and environment adaptability are improved, and the device is suitable for outdoor road scenes and has the characteristics of energy conservation, environmental protection and easy maintenance.

The application discloses a nozzle and belongs to the technical field of fluid injection equipment. The nozzle comprises a nozzle body, a first cavity, a second cavity and a third cavity which are sequentially arranged in the nozzle body, the diameters of the three cavities are sequentially reduced, and steps are arranged between adjacent cavities. The second cavity is provided with an injection cylinder, and the first cavity is provided with a compression ring. The injection cylinder is provided with a second channel, an outer side wall is provided with a third channel, the two channels are communicated through a through hole, and an extension part with a fluid outlet and a guide inclined surface is arranged at the end. The application can reduce pressure loss, improve injection stability and uniformity, is convenient to install, and has a long service life.

The present invention relates to the field of multi-agent collaborative technology, and discloses a ship collaborative control method based on self-learning, step S10, using an input module to obtain the parameters of each ship in the multi-agent system, including the expected operation trajectory of the ship; step S20, using a parameter and network initialization module, a network weight assignment module and a global loop module to start the global loop; step S30, using a network training module and a local loop module to start the local loop based on the initialized related parameters; step S40, using the iterative control law and the local optimal performance index function to replace the current iterative control law and performance index function, and using the output module to obtain the ship collaborative control strategy. In the present invention, combined with the key technologies of self-learning optimization ADP algorithm and multi-agent system communication, with the support of these technologies, it can be realized that multiple ships can automatically obtain control strategies according to the status of themselves and adjacent ships during operation, thereby achieving the purpose.

The invention discloses a space-time three-dimensional neural network calculation method based on flow field distribution characteristics of a wind power plant, and belongs to the technical field of wind power. The method comprises the following steps: acquiring position data of an anemometer tower, a wind turbine generator and a wind speed measuring instrument and wind speed and wind direction data of corresponding positions by using a communication system at a set time resolution; constructing a space-time three-dimensional neural network calculation model of the flow field of the wind power plant according to the space position relation among the anemometer tower, the wind turbine generator and the wind speed measuring instrument and the space-time correlation among the wind speed and the wind direction; and based on the space-time three-dimensional neural network calculation model of the wind power plant flow field, providing a training strategy of the space-time three-dimensional neural network calculation model. The problem of unsafe and unstable power grid operation caused by unreasonable switching-out of the distributed photovoltaic power generation system in the prior art is solved. According to the space-time three-dimensional neural network model structure, a mathematical calculation formula considering the space-time distribution characteristics of neurons is provided, and a new calculation method is provided for accurate calculation of the space-time distribution characteristics of the flow field of the wind power plant.

This utility model discloses a substrate-grown leek cultivation device, comprising a black horticultural ground cover arranged in an inverted U-shape, with multiple equally spaced perforations at the top; a sliding support rod inserted through the perforations, with sliding parts connected to both ends of the sliding support rod, the sliding parts connected to a guide support rod, and an insertion rod assembly connected to the lower end of the guide support rod, the insertion rod assembly being inserted into the soil; a black shade net arranged in an inverted U-shape; a sliding support rod also arranged in an inverted U-shape, connected to the sliding support rod, with a groove on the sliding support rod; a sliding pressure rod also arranged in an inverted U-shape, pressing the black shade net tightly into the groove; and a fixing plate connected to a fixing nail, the fixing nail being inserted into the soil, with the lower end of the sliding support rod connected to the fixing plate and able to slide on the fixing plate. This utility model allows the black horticultural ground cover and black shade net to be simultaneously unfolded and folded by pushing the sliding support rod or the sliding support rod, improving the production efficiency of leek cultivation.

This utility model discloses an air conditioner, comprising a refrigerant circulation loop. The refrigerant circulation loop includes: a main pipe connected to a compressor; and multiple branch pipes, each connected to the main pipe and to an indoor or outdoor heat exchanger. At least one of the branch pipes is equipped with a variable flow component, comprising: a pipe body connected to the branch pipes, the pipe body being adapted for refrigerant flow; and multiple blades arranged circumferentially along the pipe body, each blade having a connecting end and a free end. The connecting end is connected to the inner circumferential wall of the pipe body, and the free end is adapted to expand and contract to change the cross-sectional area of ​​the refrigerant flowing within the pipe body. The air conditioner according to this utility model embodiment has advantages such as balancing cooling and heating effects and fully utilizing the heat exchanger's heat exchange function.

The present application relates to the technical fields of flame-retardant protective clothing, and particularly relates to a flame-retardant protective clothing with mechanically adjustable tightness and a method for adjusting the tightness, which comprises a protective vest, symmetrical tightness belts are arranged on the protective vest, and one end of each tightness belt is connected with an adjusting device arranged on the protective vest; the adjusting device comprises a winder and a tightness assembly arranged on the winder; a supporting sleeve is arranged at one end of the winder, a plurality of locking mechanisms for limiting the tightness assembly are distributed along the circumference of the supporting sleeve; and a driving pushing piece is arranged in the supporting sleeve. By pressing the driving pushing piece, the plurality of locking mechanisms are driven to release the complete locking state of the tightness assembly, the tightness assembly is controlled to rotate and the rotation angle is limited through meshing transmission, the situation that the tightness is too tight or too loose during manual adjustment is avoided, and the tightness belt can be gathered or released through forward rotation or reverse rotation.

The present application discloses a comic bubble recognition training and response method and its device, equipment, and medium, wherein the training method comprises: extracting a bubble feature map from a comic original image using an image segmentation model used by a generator of a generative adversarial model; fusing the comic original image with the extracted bubble feature map and the pre-labeled bubble feature map respectively by a fusion network in the generator, and correspondingly generating a synthetic map of a false value type and a true value type; feeding the synthetic map into the discriminator of the generative adversarial model for training, so that it has the ability to identify the true and false categories to which the bubble features contained in the image belong; using the trained discriminator as the basis for distinguishing the true and false categories of the synthetic map output by the generator, training the image segmentation model, so that it improves the accuracy of extracting bubble features from comic original images. The present application can train an image segmentation model suitable for segmenting a bubble highlight map containing its bubble features from a comic image with a small number of samples.

The invention discloses a wastewater filtering and treating device for aquaculture, which relates to the technical field of wastewater treatment, and comprises a frame seat, a filter tank is arranged above the frame seat, a pair of brackets are fixedly installed between the top of the filter tank and the frame seat, a primary filtering assembly is arranged on one side of the filter tank, and a secondary filtering assembly is arranged below the filter tank; the primary filtering assembly comprises a rotating column arranged on one side of the filter tank, and a filter disc is fixedly installed on a section of the outer peripheral wall of the rotating column, a plurality of fan-shaped notches distributed at equal distances are provided in the filter disc, and one end of each fan-shaped notch is connected to a filter plate by a hinge, and a notch that slidably cooperates with the filter disc is provided on one side of the filter tank; the invention can quickly connect the filter plate and the filter cavity, and automatically clean up impurities on the filter plate, and at the same time, automatically discharge unusable filter cotton, so that wastewater treatment is more efficient and convenient, and personnel only need to add filter cotton regularly during the whole process.

This utility model provides a pipeline inspection auxiliary device, including a bottom support frame and an extension mechanism installed on the top of the bottom support frame. The extension mechanism includes a base plate, a middle plate, an upper plate, connecting rods, and a linear movement component. The base plate is fixedly installed on the top of the bottom support frame. Four connecting rods are provided and vertically installed at the four corners of the base plate surface. The middle plate is installed on the top of the connecting rods. The linear movement component is disposed on the base plate, and the moving end of the linear movement component is connected to the upper plate. An extension hole corresponding to the moving end of the linear movement component is opened on the middle plate. The bottom support frame supports the extension mechanism. The extension mechanism enters the well from the wellhead and drives the upper plate to move towards the corresponding pipeline opening through the linear movement component, realizing the connection between the middle plate and the pipeline opening, which facilitates the pipeline robot to enter the pipeline for inspection.