35762 results about "Conveyor belt" patented technology

The invention relates to a landing platform for a drone (6), comprising a landing surface comprising two conveyor belts (2) which are arranged parallel in the same horizontal plane and which are spaced apart such that a drone (6) standing on the landing surface can simultaneously have contact with both conveyor belts (drone conveyor belts), two sliding bars (3) which each extend at least partially parallel to the running direction of the drone conveyor belts (2) and can be moved toward each other above the drone conveyor belts in a direction perpendicular to the running direction of the drone conveyor belts so that the sliding bars can slide a drone (6) standing on the landing surface, and a loading unit (5) comprising a lifting device (7) for cargo, the lifting device being arranged between the drone conveyor belts, wherein the drone (6) standing on the landing surface can be moved, by movement of the drone conveyor belts (2) and / or movement of the sliding bars (3), into a position in which the drone (6) can receive cargo arranged on the lifting device (7) (loading position).

The invention relates to the technical field of image processing, and discloses a device and a method for recognizing longitudinal tearing of a mining conveying belt, which are used for improving the accuracy of recognizing the longitudinal tearing of the mining conveying belt. The device comprises: an acquisition module performing structured light projection and image acquisition to obtain original image data; the extraction module performs preprocessing and contour line extraction on the original image data to obtain geometric feature information; the generation module performs feature point analysis and stress distribution analysis on the geometric feature information to generate dynamic change features and a stress distribution diagram; the fusion module carries out fusion analysis on the sensing data set to obtain conveyor belt tearing risk evaluation data; the analysis module performs tearing probability distribution analysis based on a multi-modal neural network on the conveyor belt tearing risk evaluation data to obtain tearing identification probability distribution data; and the early warning module performs early warning information analysis according to the tear identification probability distribution data to obtain target early warning information, and performs real-time early warning according to the target early warning information.

The invention relates to the technical field of recoverable material sorting, and discloses an efficient intelligent sorting system for life source low-value recoverable materials, which comprises an acquisition unit used for monitoring environmental parameters of an urban low-value recoverable material sorting center and the speed of a conveyor belt in real time, synchronously acquiring voiceprint data, three-dimensional point cloud data and hyperspectral data of the recoverable materials, and sending the voiceprint data, the three-dimensional point cloud data and the hyperspectral data to a cloud server; through close cooperation and data interaction among all the functional units, rapid and comprehensive analysis and accurate classification of low-value recoverable materials are achieved, under the complex working condition of a large-scale solid waste treatment scene, the system can recognize and judge the recoverable materials conveyed at a high speed and then classify and sort the recoverable materials, and in the process, the recoverable materials are classified and sorted, so that the recovery efficiency of the recoverable materials is improved. According to the method, the interference of external conveyor belt speed change and environmental factor fluctuation on identification can be reduced, so that the accuracy of overall classification is ensured, and the overall identification effect can completely meet the requirements of mixing and sorting of recyclable materials under complex working conditions.

The invention relates to the technical field of fire early-stage recognition, in particular to a multi-source information-based conveying belt fire early-stage recognition and early-warning system, which comprises a sudden change detection module, a synchronous analysis module, a spatial trend recognition module, a coupling fluctuation screening module and a probability evaluation module. According to the invention, through multi-source information linkage acquisition, collaborative monitoring of parameters such as along-line temperature, smoke, gas, images, load and heat source temperature difference, combined characteristic analysis among parameters and synchronous response trend determination are driven, and active revelation of early risk hidden dangers and dynamic discrimination of spatial distribution consistency and fluctuation continuity are realized. Potential abnormal focusing locking under a high-interference complex working condition is promoted, collaborative fluctuation between a load and a heat source temperature difference further eliminates environmental noise influence, risk weight dynamic adjustment strengthens classification sensitivity of probability identification, fire risk clustering division promotes accurate mastering of distribution of tiny initial hidden dangers, and the probability identification accuracy is improved. And the reliability of fire early warning in a coal mine area conveying belt scene is obviously improved.

The present invention relates to an intelligent material distribution and material taking device and method for solid fermentation of powdery and granular fertilizers, comprising at least one production line, the production line comprising: a longitudinal conveyor belt parallel to the length direction of the fermentation tank; a transverse conveyor belt arranged above the fermentation tank along the width direction of the fermentation tank; a discharge vehicle, including a longitudinal discharge vehicle and a transverse discharge vehicle; a material distribution conveyor belt for receiving the fermentation raw materials scattered by the longitudinal discharge vehicle; a longitudinal receiving hopper; a mobile spiral material taking machine, which is longitudinally slidably arranged in the fermentation tank to collect the intermediate products in the fermentation tank; a controller, which controls the intelligent material distribution and material taking device for solid fermentation of powdery and granular fertilizers to switch between the two working states of distribution and material taking, and controls the transverse conveyor belt and the longitudinal discharge vehicle to keep synchronous longitudinal movement. The controller is used to switch the working state of the material distribution and material taking device, so as to realize intelligent and automatic material distribution and material taking, so as to meet the needs of solid fermentation of powdery and granular fertilizers.

The invention discloses an intelligent material conveying deviation remote monitoring system based on Internet of Things, which relates to the technical field of material conveying deviation remote monitoring and comprises a signal monitoring module, an abnormal window calibration module, a distortion evaluation module, a data correction module and a remote optimization module. The distortion evaluation module is used for acquiring ultrasonic propagation distortion characteristic information in a signal propagation abnormal window in real time, analyzing and evaluating the echo signal distortion degree under the condition of ultrasonic signal propagation path distortion after acquisition, and dividing the echo signal distortion degree into three types, namely a light distortion degree, a medium distortion degree and a heavy distortion degree; and the data correction module is used for taking corresponding correction measures on the to-be-corrected measurement data under the condition of different echo signal distortion degrees based on the evaluation result. According to the method, the problem of measurement errors caused by propagation path distortion of ultrasonic signals in conveyor belt deviation monitoring is solved, accurate distortion evaluation and adaptive data correction are realized, and the monitoring precision and stability are improved.

The invention relates to an intelligent garbage sorting method based on multi-modal recognition. The method comprises the following steps that S1, three-dimensional shape information and material information of objects on a conveying belt are captured; s2, preprocessing the acquired image data and sensor data; s3, based on the preprocessed image data and sensor data, generating a unified bounding box and a classification result based on a Hybrid Net model; s4, based on a bounding box and a classification result output by the Hybrid Net model, a discrete PID algorithm is adopted to calculate a motion instruction, a depth sensor is utilized to calculate three-dimensional point cloud data of an object, the stacking layer number of the position where the object is located is judged, a surface layer object is grabbed preferentially, and an initial grabbing path based on a position error and a stacking priority is generated; and S5, on the basis of the initial grabbing path, DQN deep reinforcement learning is used to optimize the initial grabbing path into an optimal grabbing path. According to the method, the grabbing optimization problem of the robot in a dynamic environment (such as stacking and obstacle interference) is effectively solved.

The invention provides an aluminum film sealing defect real-time detection method and system based on multi-algorithm fusion, and relates to the technical field of intelligent manufacturing, and the method comprises the steps: triggering an industrial camera at a detection station to collect an original image of a pesticide aluminum film sealing on a conveyor belt; performing adaptive equalization operation on the original image through pixel brightness distribution data, eliminating light fluctuation and surface reflection interference, and outputting a standardized image; three types of defect detection are synchronously executed based on the standardized image, a dynamic threshold segmentation algorithm is combined with local area brightness analysis to detect edge damage, a contour extraction algorithm is adopted to calculate bottleneck center offset to recognize seal offset, wrinkle defects are recognized based on a surface texture feature analysis algorithm, and a primary detection result is output. The aluminum film sealing defect detection method is based on multi-algorithm fusion, has strong anti-interference capability, real-time detection performance and data traceability, and provides an efficient and reliable automatic solution for aluminum film sealing quality management and control.

The invention discloses a visual and three-dimensional modeling luggage automatic identification method, equipment, a medium and a product. The method comprises the following steps: firstly, carrying out dynamic multi-view scanning on luggage entering a scanning area of a conveyor belt to obtain a multi-view image, carrying out deep learning to obtain three-dimensional point cloud data, and fusing the three-dimensional point cloud data with X-ray transmission density data to form a preliminary three-dimensional model; whether the model is complete or not is judged by combining geometric closure and material density continuity, and if not, features are extracted through an adversarial generative network, and occlusion area point cloud data are predicted for complementation; and finally, matching the complementation model features with a dangerous goods feature library, and judging whether the dangerous goods are dangerous goods or not. By implementing the technical scheme provided by the invention, the information of the articles in the luggage can be comprehensively obtained, the complete and accurate three-dimensional model can be constructed, whether the articles are dangerous articles or not can be efficiently and accurately judged, and the efficiency and the safety of aviation security inspection are improved.

The invention relates to the technical field of intelligent manufacturing, in particular to an HTCC ceramic defect automatic identification method based on industrial model assistance, which comprises the following steps: step 1, collecting sintering temperature gradient, lamination pressure and green body water content process parameters in the HTCC production process in real time; step 2, performing non-contact dielectric property scanning on the sintered HTCC substrate on a production line conveyor belt; 3, based on the coordinates of the dielectric abnormal region, controlling an annular polarization light source to inhibit the incident angle reflected by the metallization layer from irradiating the target region; 4, inputting the dielectric anomaly frequency band feature vector and the defect image texture feature in the step 3 into a cross-modal attention network to generate a fusion feature map; and 5, establishing an association mapping library of the defect type and the process deviation type. Through accurate real-time monitoring, intelligent defect identification and classification, automatic process adjustment and a continuously optimized feedback mechanism, the efficiency, quality and intelligent level of the ceramic production process are greatly improved.

The invention discloses an aluminum electrolytic capacitor appearance defect detection device, relates to the field of aluminum electrolytic capacitor detection, and solves the problem that an existing detection device is difficult to comprehensively detect an aluminum electrolytic capacitor. The aluminum electrolytic capacitor appearance defect detection device comprises a device base and two first supporting plates, and two first transmission belts are arranged between the two first supporting plates; a push roller is arranged on the outer side of the first transmission belt, supporting frames are installed on the corresponding sides of the two first supporting plates, a first detection box is fixedly installed at the top of the device base, and a plurality of first laser probes are arranged on the inner side of the first detection box; the transfer mechanism is used for detecting pins of the capacitor, and the transfer mechanism is mounted at the top of the device base; through the transfer mechanism, the first laser probe detects the capacitor entering the first detection box, under the conveying of the first transmission belt, the capacitor is turned over, and the pins of the capacitor can face upwards, so that the pins of the capacitor can be detected conveniently, and the effect of comprehensive detection is achieved.

The invention relates to a composite material garbage sorting method based on a hyper-spectrum technology and an AI classification model. The method comprises the following steps that S1, multi-modal data collection is conducted; s2, the collected multi-modal data are preprocessed and fused, and combined features of the multi-modal data are obtained; s3, constructing a classification model based on the multi-modal neural network model, and performing classification according to the joint features; s4, based on a classification result, using a SegFormer deep segmentation network to identify junk components at a pixel level, and realizing accurate segmentation of a plurality of material composition objects; s5, target tracking of the garbage trajectory is kept through a target tracking algorithm; and S6, on the basis of the target tracking result in the S5, the position of the garbage on the conveying belt is predicted in real time, and the sorting action is precisely executed according to the classification and segmentation result. According to the invention, the complex composite material garbage can be efficiently and accurately treated.

Described is a system for conveying wet sand. The system includes containers with a slip coating for storing wet sand. Each container includes an outlet formed in a bottom portion to facilitate removal of the wet sand from the container to a hopper. Each hopper has end walls, side walls, and an interior wall extending at an angle from the top to the bottom of the hopper to reduce an area of the outlet. A flow gate over the outlet controls discharge of the wet sand from the hopper onto a conveyor belt of a conveyor system. The hopper also includes a vibration system coupled to its exterior surface for shaking the hopper to assist in releasing sand. A discharge assembly is located at the end of the conveyor system for directing wet sand from the conveyor belt.

The invention provides a helical gear speed reducer fault diagnosis method under intelligent monitoring, and relates to the technical field of fault diagnosis, and the method comprises the steps: obtaining real-time operation parameters of an inclined logistics conveyor belt, carrying out the load state evaluation of a helical gear speed reducer, configuring a first monitoring frequency and a first monitoring index number based on a load scale, activating a first sensing device, and carrying out the fault diagnosis of the helical gear speed reducer; monitoring is carried out according to the first monitoring frequency to obtain a first fault risk coefficient, if the first fault risk coefficient exceeds a first fault risk threshold, the sensing monitoring array is activated to obtain a second fault risk coefficient, and if the second fault risk coefficient exceeds a second fault risk threshold, the acousto-optic early warning device is activated to send out an early warning signal to carry out fault early warning. The technical problem of low fault diagnosis efficiency and accuracy caused by the lack of real-time monitoring and intelligent diagnosis means of the helical gear speed reducer in the prior art is solved. The technical effects of monitoring the running state of the helical gear speed reducer in real time and improving the fault diagnosis efficiency and accuracy are achieved.

The invention discloses a consigned luggage measurement and identification method and system, electronic equipment and a storage medium, and relates to the technical field of intelligent logistics. The method comprises the steps that multi-dimensional data of current luggage on a luggage conveying belt are collected, the multi-dimensional data are preprocessed and fused, luggage parameters of the current luggage are obtained, and the luggage parameters comprise size information, weight information and luggage structure characteristics; determining the type of the current luggage based on the luggage parameters; determining the processing priority of the current luggage based on the flight information corresponding to the current luggage and the luggage parameters; and determining the processing flow of the current luggage based on the processing priority and the real-time load of the luggage processing system. By implementing the technical scheme provided by the invention, the efficiency and safety of the luggage processing flow can be improved.

The utility model provides a manual hot stamping mechanism which comprises a working table, an unwinding roller, a winding roller and a hot stamping assembly, the hot stamping assembly is located between the unwinding roller and the winding roller, the unwinding roller and the winding roller are both rotationally connected to the working table, and the manual hot stamping mechanism further comprises a conveying belt. The two ends of the workbench are rotationally connected with a first conveying roller and a second conveying roller correspondingly, the conveying belt is tensioned through the first conveying roller and the second conveying roller, the workbench is fixedly connected with a supporting plate, and the supporting plate supports the conveying belt and is located between the conveying belt and the hot stamping assembly. The purpose of conveniently guiding the license plate out of the workbench is achieved.

A board diagonal measurement system and method suitable for multiple specifications of gypsum boards (1). The system comprises a cross-type guide rail (2), diagonal point positioning members (3), and a driving structure (4); the cross-type guide rail (2) is composed of two sliding rails (21) crossing each other; the driving structure (4) is used for driving the two sliding rails (21) to rotate, so that the sliding rails (21) keep parallel to diagonals of a gypsum board (1) having a corresponding size, wherein in an initial state, a rectangular area formed by connecting position points where the diagonal point positioning members (3) are located is located outside the gypsum board (1). The cross-type guide rail (2) is arranged above a conveyor belt (5), the sliding rails (21) keep parallel to the diagonals of the gypsum board (1) having the corresponding size, the positions of the diagonal point positioning members (3) also change along with the sliding rails, so that the length and the width of the rectangular area are adjusted, and the rectangular area which is inwardly contracted and then completes positioning of the gypsum board is just matched with the specification of the gypsum board (1). The present invention is suitable for diagonal measurement of the multiple specifications of gypsum boards (1).

The invention relates to the technical field of solid waste treatment, in particular to an intelligent waste sorting method based on multi-sensor fusion. Carrying out multi-level fusion decision making: carrying out sewage reflection suppression on the visible light image; carrying out matching identification and rejecting a liquid pollution area based on a near infrared spectrum; fusing the visible light texture, the spectral feature and the electromagnetic signal to generate a space grid feature vector; identifying the material category through a cascade classifier, and dynamically adjusting the weight of each sensor in the decision according to the environmental parameters; self-adaptive sorting execution: triggering a corresponding sorting execution mechanism according to an identification result; based on the transmission belt speed, the execution mechanism response delay and the material physical attribute, the action advance compensation amount is calculated; the action time of an execution mechanism is adaptively prolonged for the stacked materials according to the stacking hierarchy; and online feedback optimization. Through dynamic compensation and time sequence adjustment, the time sequence consistency of multi-sensor data is ensured, and the influence of band speed fluctuation is overcome.

The invention relates to the technical field of agricultural machinery control, in particular to a multi-variety vegetable harvester dynamic identification and feeding control system based on image processing, which comprises an image acquisition module, an environment sensing module, an image processing module, a data fusion module, a dynamic identification and tracking module and a feeding control module. Through binocular stereo vision and millimeter wave radar fusion, three-dimensional space positioning and dynamic tracking of the brassica oleracea corm are realized. Track prediction is carried out in combination with extended Kalman filtering and a long-short-term memory network, and the clamping path of the mechanical arm is optimized; the clamping force is adaptively adjusted through fuzzy PID control, and accurate feeding of the cabbages is achieved in combination with speed control of the conveying belt. The automatic cabbage harvesting machine improves the automation level of cabbage harvesting, effectively reduces the damage rate, improves the operation stability and harvesting efficiency, and is suitable for intelligent harvesting operation of a large-scale cabbage planting base.

The invention discloses a coal conveying belt fault early warning method and system, relates to the field of safety monitoring of coal conveying equipment, and solves the problems of lagging and high false alarm rate of traditional single-parameter early warning. The system comprises a multi-dimensional data acquisition layer, a dynamic feature extraction layer, a belt-material coupling analysis module, a fault judgment layer and an early warning output layer, wherein the acquisition layer acquires parameters such as belt tension, speed, material granularity and weight; noise reduction is carried out on the extraction layer, parameters are normalized, and features are extracted; the coupling module builds a dynamic coupling model to calculate a coupling coefficient, matches a fault feature library and outputs an abnormal signal; determining a layer fault type and a risk level; and the output layer gives early warning information and suggestions. According to the method, the system is applied, belt and material characteristic correlation early warning is achieved through sub-model construction and coupling coefficient calculation, the early warning accuracy and timeliness are improved, and the method is suitable for multiple scenes and low in operation and maintenance cost.

The invention belongs to the technical field of optical fiber laser welding, and particularly relates to optical fiber laser welding equipment which comprises a rack, a conveying mechanism used for conveying a battery module is arranged in the rack, an XYZ-axis moving mechanism is installed on one side of the rack, a laser welding device is installed on the XYZ-axis moving mechanism, and a conveying belt is connected to one side of the end of the rack. The conveying mechanism comprises two sets of transmission shafts, the two sets of transmission shafts are rotationally installed in the rack, chain wheels are installed on the two sets of transmission shafts, the two sets of chain wheels are meshed with a chain, a plurality of sets of shifting forks used for containing battery modules are arranged around the chain, and one ends of the shifting forks are fixedly connected with the chain. According to the battery module welding device, feeding, welding and discharging of the battery module can be conducted at the same time, the automation rate of the device is increased, meanwhile, the battery module can be continuously welded, and the welding efficiency of the battery module is improved.

The invention discloses an L-shaped conveyor belt path dynamic planning and congestion prediction system, which relates to the technical field of automatic control, and constructs a conveying path node diagram by collecting material weight, speed and spacing information of each node on a conveying path, and calculates a congestion index of each path section; the method comprises the following steps: combining a light-mass material jumping sensitivity model, identifying a high-risk node and marking the high-risk node as a congestion prediction area, constructing a dynamic optimization model based on path risk distribution and a material flow direction, generating and evaluating a plurality of path adjustment strategies, executing an optimal strategy according to priority, and realizing path speed adjustment, standby path switching and feeding rhythm control; through a feedback mechanism, a strategy effect is evaluated in real time, a path state is updated, operation data is synchronized to a historical database, a learnable conveying operation file is formed, the stability and the intelligent response capability of a conveying system can be effectively improved, and the method is suitable for high-speed sorting and automatic packaging scenes.

The invention relates to the technical field of belt conveyor dynamic characteristic research, in particular to a trailer type belt conveyor dynamic characteristic simulation method, which comprises the following steps: respectively carrying out stress analysis on a trailer frame, each wheel and a conveying belt unit in a trailer unit, and sorting the degree of freedom; establishing an overall coordinate system, a vehicle body coordinate system, a contact coordinate system and a conversion relation; respectively establishing kinetic equations of the wheel pair and the vehicle supporting frame; kinetic parameters of the trailer unit are determined; according to the Hamiltonian principle, a vehicle supporting frame vertical motion equation and a vehicle supporting frame nodding motion equation are established, and then a linear second-order differential equation of a vehicle supporting unit is obtained; and compiling a calculation program by using numerical calculation software, and simulating the wheel-rail vibration characteristics of the trailer unit in the straight-line-segment advancing process. On the basis of the multi-degree-of-freedom multi-body dynamics theory, a trailer type belt conveyor system nonlinear dynamics equation is constructed, and a wheel pair, a trailer frame and a six-degree-of-freedom motion equation for coupling the wheel pair and the trailer frame are analyzed.

The invention belongs to the technical field of button processing, and particularly relates to feeding equipment for processing buttons, which comprises a rack, a conveying belt is arranged on the rack, and a button sorting assembly is further arranged on the rack; the button sorting assembly comprises a frame body fixedly connected to one side of the upper end of the rack, a visual detection mechanism is arranged on one side of the upper end of the frame body, first sliding rods are fixedly connected to the two ends of the upper side of the frame body, sorting plates are slidably connected to the two sides of the first sliding rods, and limiting plates are slidably connected to one sides of the sorting plates in an inserted mode. And a sorting track is arranged at the minimum distance between the two sorting plates. According to the button sorting device, scattered buttons can be in an ordered arrangement state in the sorting track, follow-up processing is facilitated, the buttons in the sorting track do not make contact with one another, and the situation that in the sorting process, due to the fact that the arc faces of the buttons make contact with the conveying belt and the rear buttons collide with the front buttons, the rear buttons and the front buttons are overlapped, and the button sorting effect is affected is avoided.

Provided is a conveyor belt including at least two parallel chains each including a plurality of consecutive links; and a plurality of rods extending between the at least two parallel chains for linking the consecutive links. Each rod extends with each end through the corresponding chain linking two consecutive links to each other. One of the two consecutive links is at least axially locked to the rod to avoid movement of the link relative to the rod. The other of the two consecutive links is rotatably arranged around the respective rod. Also provided is at least one device for providing the lock between a rod and a respective link of the conveyor belt. The device includes a body; an insertion hole in which an end of the rod is inserted along an insertion axis, which insertion hole is arranged in the body and a protrusion arranged to the body and extending from the body parallel to and at a distance of the insertion axis; fixing means for fixing the end of the rod in the hole in at least axial direction and preferably also in rotational direction. The respective link is provided with a locking opening through which the protrusion extends.

When x-ray fluorescence (“XRF”) spectroscopy is utilized to classify materials transported on a moving conveyor belt, there is the possibility of the x-ray beam only partially irradiating the material piece, which can result in the capture of an inaccurate XRF spectrum needed to classify the material piece. This can lead to an improper (erroneous) classification and resultant sortation of material pieces (e.g., aluminum alloys). In a material handling system, the area of the intersections between the x-ray beam spots from an x-ray fluorescence system and the material pieces are measured and correspondingly used to correct the measured XRF spectrum associated with each material piece. The material pieces can then be sorted according to the corrected XRF spectrum.

Disclosed in the present invention is an apparatus for measuring the thickness of heat insulation cotton after hot pressing. The apparatus comprises an inspection platform, and a conveyor belt used for conveying heat insulation cotton, wherein the conveyor belt closely passes over the top plane of the inspection platform. The apparatus further comprises: a thickness measurement assembly, which is used for measuring the thickness of the heat insulation cotton when the conveyor belt stops; and a surface inspection assembly, which comprises a laser scanning portion and an image collection portion, wherein the laser scanning portion obliquely emits a laser line to the surface of the heat insulation cotton and moves along the surface of the heat insulation cotton, and the image collection portion is located right above the heat insulation cotton and performs image collection on the trajectory of the laser line. The present invention can measure the thickness of heat insulation cotton by means of a thickness measurement assembly, and can further perform image collection on the trajectory of a laser line by means of an image collection portion, and therefore the surface quality of the heat insulation cotton can be inspected on the basis of a change in the laser line in an image, and then in combination with the measurement of the thickness of the heat insulation cotton, the range of heat insulation cotton inspection can be wider, and inspection results are also more objective.

The invention relates to the technical field of textile dyeing sewage treatment, in particular to textile dyeing sewage treatment equipment. Comprising a purification box and a pretreatment box, and the interior of the pretreatment box communicates with the interior of the purification box; a sewage collecting box is fixedly connected to the purifying box, an auxiliary box is fixedly connected to the purifying box, an incomplete gear is driven by a first motor to rotate in the anticlockwise direction, so that a first conveying roller and a second conveying roller rotate synchronously, synchronous movement of a filter screen conveying belt is achieved, the filter screen conveying belt moves uninterruptedly while filtering is conducted, and the filtering efficiency is improved. The filter screen conveying belt entering the cleaning box is deeply cleaned through the wadding scraping mechanism and the deep cleaning mechanism, the filtering effect of the filter screen conveying belt is effectively improved, the filtering effect of sewage is improved through secondary filtering, the device enables sewage to be filtered more thoroughly, meanwhile, self-cleaning of the filter screen conveying belt can be conducted, and the service life of the filter screen conveying belt is prolonged. Manual replacement and manual cleaning are not needed, and the workload of workers is effectively reduced.

Drone roosts, storage facilities, and / or drone delivery mailbox systems can be used to aid in drone deliveries and / or drone deployment. A roost can include a top hatch, a conveyor belt, a drone storage wheel with at least one drone storage shelf, and a conveyor door. In some embodiments a roost can include a plurality of trays configured to move along at least one guiderail and store drones. A storage facility can include an outer shell, a top aperture, a cargo delivery hatch, a gantry robot, a conveyor belt, an overhead camera, and / or a backstop. In some embodiments, the storage facility can include a landing tower, a package elevator, a cargo delivery door, and / or a package shuttle. In some embodiments, the storage facility is a circular drone delivery station. In some embodiments, a drone delivery mailbox system can a conveyor belt, a pair of bumpers, and / or a docking clamp.

The invention discloses a coal quality online detection multispectral analysis system and analysis method, and belongs to the technical field of coal quality detection. Comprising a detection table, a crushing barrel, a supporting frame, a spectrum detector and a conveying belt are installed at the top end of the detection table, the conveying belt is driven by a second motor, and a flattening assembly, a collecting guide plate, a collecting box and a smoothing assembly are arranged at the top of the conveying belt. Through cooperation of the crushing cylinder and the flattening assembly, coal samples can be conveyed to the conveying belt after being crushed, the coal samples are automatically flattened and concentrated so that the coal samples can be conveyed into a spectrum detector to be subjected to spectrum analysis through a laser head, automatic operation is achieved in the whole process, rapidness and convenience are achieved, the detection efficiency is high, manual participation is not needed, and the labor intensity of workers is reduced. Meanwhile, through cooperation of the collecting box, the collecting guide plate and the smoothing assembly, the detected coal samples can be collected and stored in a targeted mode, and waste of coal resources is avoided.