252 results about "Material type" patented technology

The invention discloses a control method and equipment of a glue spraying system and a storage medium, and relates to the technical field of automatic spraying, the method comprises the following steps: obtaining a distance parameter from a nozzle to the surface of a workpiece at the cut-off position of the nth time step and spraying area image data of the nth time step, and generating a workpiece curvature feature and a spraying state feature; the spraying state characteristics, the workpiece curvature characteristics and the material type of the area corresponding to the (n + 1) th time step are substituted into a compensation algorithm, and difference parameter values are generated; and generating and executing a target control parameter of the (n + 1) th time step according to the difference parameter value and the initial control parameter. According to the method, the change of the surface of the workpiece is monitored in real time, the spraying parameters are automatically adjusted according to the change, the technical problem that the thickness of a coating is not uniform is solved, and the spraying quality and efficiency are improved.

The invention discloses a labeling quality intelligent detection method and system for multiple materials, and the method comprises the steps: S1, collecting original image data of paper, plastic and metal labels through an industrial camera, and carrying out the preprocessing, and obtaining standardized image data; s2, designing an improved edge detection network, extracting an initial edge feature of the label, generating a linear edge feature through curve fitting, calculating a label rotation angle, and executing rotation transformation to obtain image data after rotation correction; s3, constructing a double-branch network comprising material and defect branches, extracting material types, generating defect features in combination with the material types, and finally generating structured defect features; and S4, according to the structured defect features, generating material tolerance, and then calculating a quality score and a quality grade. According to the method, the problems of material misjudgment and defect detection omission caused by low rotation correction precision of the special-shaped label and staged processing of multi-material defect detection in a traditional method can be solved.

The invention provides an aluminum substrate drilling tool wear prediction method based on reinforcement learning, and the method comprises the steps: collecting working condition parameters, such as main shaft rotation speed, feeding speed, cutting depth, material type and historical vibration energy, through the deployment of an industrial sensor network, and achieving data standardization through feature extraction and normalization processing; a dynamic cognitive map with process meaning is constructed by adopting semantic analysis and a map generation strategy, key semantic nodes are identified by utilizing a map attention network, reinforcement learning is driven through a structured reward function, and self-adaptive optimization of a wear prediction strategy is realized; according to the method, abnormal detection and working condition abrupt change increment updating are supported, map consistency optimization is achieved by fusing expert experience, the tool wear prediction precision and the environment adaptability can be improved, and the intelligent sensing and dynamic response capacity to the complex manufacturing process can be enhanced.

The invention relates to the technical field of blister thermoforming, and discloses a high-precision controllable thermoforming method of a blister machine, which comprises the following steps: extracting a feature recognition material type, and calculating to obtain a thermal diffusion coefficient; a temperature field is collected in real time, temperature distribution at the next moment is predicted, a fuzzy rule base is established to dynamically adjust PID parameters, a falling risk coefficient is calculated based on the actually measured temperature, and whether airflow compensation is started or not is judged; a mold cavity structure is constructed, and a vacuum degree curve is set in stages; material flow monitoring is conducted on the material, and the vacuum degree is corrected through fuzzy control; analyzing to obtain a coordinate deviation, and executing dynamic compensation; performing real-time correction according to the coordinate deviation, establishing an inter-station coupling coefficient matrix through multi-station cooperative control, and performing temperature compensation; and constructing a multi-dimensional quality evaluation model, performing analysis to obtain a comprehensive quality index, judging whether to trigger a key parameter optimization process or not based on the comprehensive quality index, and performing real-time feedback optimization.

The invention provides a projection lamp shadow effect intelligent adjustment method based on artificial intelligence, and the method comprises the steps: obtaining the material type and reflection coefficient of the wall surface of each region of an exhibition space through a pre-established wall surface material database, carrying out the classification processing according to the reflection characteristics of different materials, and obtaining a material reflection distribution diagram; acquiring light intensity distribution in the space based on stray light distribution characteristics, performing gridding decomposition on the light intensity distribution, and obtaining light intensity and light field distribution uniformity of each grid area through numerical integration; according to the adjusted projection angle and light source position, generating a control parameter for the projection equipment, adjusting the output intensity and direction of the projection light source, and obtaining the light distribution intensity after the control parameter of the projection equipment is adjusted; and if the contrast ratio and the color deviation value of the detail area do not meet the preset standard, optimizing the light source control parameters through an ambient light compensation mechanism in combination with the accumulated intensity data of the space corner to obtain a light compensation result.

The invention relates to the technical field of cable detection, and discloses a cable DC resistance detection and material identification method and system, and the method comprises the steps: constructing a four-wire system low-impedance electrical connection of a cable sample, compensating and correcting the path measurement precision through contact resistance, and obtaining an optimized electrical connection; monitoring a load state and performing closed-loop regulation on load impedance to obtain high-stability direct current; performing high-precision differential signal conditioning on the original voltage signal to obtain purified voltage data; deriving an initial resistance measurement value based on the purification voltage and the high-stability direct current, and performing system error compensation calibration on the initial resistance measurement value through a reference resistance comparison mechanism to obtain a calibrated direct current resistance value; obtaining material identification reference data according to a pre-stored mapping relation between the material and the resistance value in a material resistance database; the range attribution of the calibration direct-current resistance value in the material identification reference data is judged, and the material type is identified; according to the invention, the efficiency of cable DC resistance detection and material identification can be improved.

The application provides a waste steel monomer instance segmentation method and a waste steel intelligent grading system. The waste steel monomer instance segmentation method comprises the following steps: extracting image features in a waste steel image; generating a target candidate box of each image feature; generating a grade of a monomer, a material type classification of the monomer, a detection box of the monomer and a monomer region mask based on each target candidate box. Based on the above detection result, each target detection box is converted into a boundary line of an image monomer, and a mask region of the monomer is generated, so as to complete the monomer instance segmentation. Through the pre-storage of the material type information and the grade information, the subsequent material type and grade classification of the waste steel monomer can be facilitated according to the pre-stored material type information and grade information, so that the waste steel grading is more accurate, and the accuracy of the waste steel classification is improved.

The invention provides a novel scrubber chassis structure, and relates to the technical field of cleaning equipment, the novel scrubber chassis structure comprises a bearing base, a transition part and a disc brush base which are integrally arranged, the length direction of the disc brush base and the length direction of the bearing base form an included angle of 120-160 degrees, and the top of the bearing base is provided with a hinge lug. By designing the bearing base, the transition part and the disc brush base which are integrally arranged, material types can be reduced, installation is more convenient and faster, the cost is reduced, meanwhile, the chassis strength is greatly enhanced, and the situation that a brush disc part shakes in the working state is weakened; and the length direction of the disc brush base and the length direction of the bearing base are designed to form a certain included angle, after the main body shell of the floor washing machine is installed, the disc brush base inclines towards one side, the outer edge of a brush disc installed on the disc brush base can be slightly arranged, and the corners can be conveniently cleaned.

The application relates to the chip detection technical field, in particular to a semiconductor packaging workpiece identification detection method and device and a cutting and sorting integrated machine, wherein the method comprises the following steps: acquiring a surface image of a workpiece to be detected; the surface image comprises an identification for marking a workpiece type of the workpiece to be detected; the workpiece type is a good material type or a bad material type; image skeleton extraction is performed on the surface image to obtain a skeleton line corresponding to a pattern in the surface image; for each pixel point on the skeleton line, if the minimum distance between the pixel point and a preset identification reference line is less than a first preset distance, the pixel point is projected onto the identification reference line; the identification reference line is drawn in the surface image according to the identification shape corresponding to the bad material type; and the identification corresponding to the workpiece type on the workpiece to be detected is determined according to the proportion of the area of the identification reference line projected by the skeleton line. The application can solve the problems of low identification detection precision and weak anti-interference capability of the identification on the workpiece to be detected.

The invention relates to a rolling method for reducing rolling groove slipping, which comprises the following steps of: S1, reducing the height size of a material type of a rolling mill (X-2 rolling mill) to reduce the height value of the material type of a rolling mill (X-1 rolling mill) after a roller of a certain rolling mill (X-1 rolling mill) is replaced to obtain a new rolling groove; and S2, the height size of the material type of the rolling mill X is increased, due to the fact that the height value of the rolling mill X-1 is engaged by the rolling mill X, after the height value of the material type of the rolling mill X-1 is decreased, if the height size of the rolling mill X is increased, and the engagement angle of the rolling mill X is decreased, the engagement strength is correspondingly increased, and therefore slipping is reduced. According to the invention, the biting can be obviously improved, the slipping effect of the groove is solved, the groove explosion after the groove is polished by electric welding is reduced, and the rolling quantity of the roller is improved.

This invention discloses a precision grinding process for machining the shaft of a swimming pool pump motor, relating to the field of shaft precision grinding technology. The process includes: Step 1: Establishing an incident window using a coherent jet nozzle, allowing the jet to penetrate the air gap into the grinding zone, first wetting and then introducing the load, and recording the incident window, jet posture, and dressing rhythm as working condition metadata; Step 2: After precision grinding, according to the material type, magnetic noise is used for ferromagnetic steel and X-ray diffraction is used for austenitic steel to obtain thermal damage and residual stress, and combining this with cleanliness to generate a surface integrity label and bind it to the working condition metadata; Step 3: Performing deionized ultrasonic cleaning and rinsing according to the label to remove chloride salts and free iron, rebuilding the passivation film according to specifications using chemical passivation, controlled drying, and clean sealing; Step 4: Under the premise of qualified chemical condition, performing isotropic ultra-finishing and low-plasticity rolling on the sealed working zone to form surface compressive stress and maintain geometric tolerances, quickly indicating inspection and writing back the label.

The invention provides a compensation automatic weighing material supply method, device and system for a transport ship and a storage medium. The transport ship is provided with a plurality of storage chambers, and each storage chamber is provided with at least one self-weighing device; the cargo ship compensation automatic weighing material supply method comprises the steps that weighing cargoes are classified according to different material storage conditions and material types to obtain different types of cargo groups; the goods groups are classified through an executing mechanism, and the weight is weighed through the self-weighing equipment; and according to the weight, calculating according to the stored goods classification to obtain the material consumption for subsequent replenishment. Through storage and weighing of different goods groups, the material consumption is calculated and used for follow-up supply, and the technical problem that material supply exceeds the actual situation and then exceeds the volume of a stacking area due to a manual method in the prior art is solved.

The invention provides a scrap steel quality inspection APP pressing block two-end dismounting prompting method, and relates to the technical field of scrap steel quality inspection in the iron and steel industry, and the method comprises the following steps: S1, material type selection: an acceptor selects a to-be-inspected scrap steel pressing block type in a scrap steel quality inspection APP system according to an actual condition; s2, inputting to-be-detected information: inputting specific information of a to-be-detected briquetting vehicle; and S3, two-end unpacking prompting: according to the input layer number, row number and column number of the to-be-detected briquette vehicle, dynamically generating an unpacking instruction by the APP, and prompting an acceptor to carry out unpacking detection. According to the scrap steel quality inspection APP pressing block two-end-disassembly prompting method, an unpredictable and tamper-resistant random unpacking mark generation system is constructed, dynamic generation of an unpacking instruction is achieved, the sampling rule is transparent, man-made interference is resisted, and the unpacking efficiency is improved. Therefore, the problems that the inspection efficiency is reduced due to full-amount disassembly of the two ends and the internal quality of the pressing block is possibly covered due to lack of randomness are solved, and the accuracy and the high efficiency of scrap steel inspection are effectively improved.

A nondestructive evaluation system and method are provided for detecting the material type and leakage of an underground service line. An impactor applies a controlled impact to an instrumented rod in contact or proximity with the service line, inducing stress waves that propagate into the service line and surrounding soil. Sensors on the rod and / or on the ground surface detect the resulting waveforms. A processing unit analyzes time and frequency domain characteristics such as wave speed, attenuation, and vibration response to determine service line material and identify anomalies associated with leakage. The system enables accurate, real-time diagnostics of buried pipelines without excavation or fluid interruption.

The present application relates to the technical field of structural design and optimization, in particular to a continuity step length topology optimization method based on multi-material stress constraint, which comprises parameter initialization, material attribute interpolation and finite element calculation, interpolation calculation of each unit stress constraint, stress constraint relaxation criterion construction, incremental Lagrange stress constraint integration to form an optimization problem and calculate the sensitivity of design variables, moving progressive line method to update multiple design variables, iterative optimization and step length parameter update until the convergence condition is met. The present application is applicable to more material types and different stress criterion combinations, can meet the continuity step length minimum value and control the step length change rate in the specified iteration round, the output structure is reasonable and reasonable, the boundary is clear and the structure is novel, the design variable change in the iteration process is stable, and the abnormal numerical oscillation problem is solved.

The invention relates to the technical field of engineering construction safety, and discloses an engineering construction site intelligent supervision system, which comprises a front-end data acquisition layer, an edge calculation layer, a cloud data processing layer and an application layer which are in communication connection in sequence, and the front-end data acquisition layer comprises a high-definition spherical camera, a BT-452 Beidou positioning module and a BT-878 wireless communication module. According to the intelligent supervision system for the engineering construction site, a high-definition spherical camera of the front-end data acquisition layer acquires construction material images, a Shufflev2-YOLOv5 detection algorithm of the edge calculation layer takes Shufflev2 as a main network and is combined with FocalLoss to relieve unbalance of material types, a data fusion module of the cloud data processing layer dynamically weights and fuses material detection data, and the data fusion module performs data fusion on the material detection data. And a material metering module of the application layer calculates the volume and mass of the material according to the size of a target frame output by an algorithm, and when the mass exceeds the standard, a safety early warning module of the application layer is directly triggered to send a sound-light alarm signal to form a closed loop, so that the problems of insufficient material detection precision, inaccurate metering and lack of cooperative early warning are solved.

This application discloses a multimedia material management method, apparatus, device, and storage medium, comprising: upon receiving a selection operation based on a material type selection interface, displaying a material list corresponding to the material type, wherein the material list includes a material tag for each material content and a corresponding first operation control, and the material type includes one or more of image type, video type, and text type; upon receiving a click operation on the first control, obtaining the corresponding basic material content according to the material tag corresponding to the first control; and forwarding the basic material content to the target application. This solution can solve the technical problem of low efficiency in multimedia material management, allowing users to quickly find the basic material content of the corresponding material type through selection on the material type selection interface, significantly improving the efficiency of multimedia material search, and thus improving the overall efficiency of multimedia material management.

The application discloses an accessory list generation method and device, equipment and medium, and relates to the technical field of computers, which comprises the following steps: obtaining an accessory bar code and a production task sheet, determining accessory information from the production task sheet, and comparing the accessory bar code with the accessory information; if the information comparison is passed, generating a serial number based on the accessory bar code, and saving the accessory bar code and the serial number to a local device; judging the accessory material type based on the serial number, if the accessory material type is non-test material, checking the serial number, if the checking is passed, generating an accessory list according to the accessory bar code and the serial number. Through the above technical scheme of the application, the material loss in the production process can be avoided, and the accuracy and traceability of the accessory list generation are improved.

The application discloses a double coil for binding, and aims to solve the problem that the existing double coil needs to be opened and closed when disassembling and assembling the pages, and deformation occurs in the opening and closing process, and metal fatigue is caused after a large number of times, so that the double coil cannot be restored to the original state, that is, the double coil cannot be completely closed, and then the normal use is affected.The technical scheme points are as follows: including a double coil body, the double coil body includes a first connecting block, a second connecting block, a plurality of first arc strips fixedly connected to the first connecting block and a plurality of second arc strips fixedly connected to the second connecting block.The application can complete the disassembly and assembly of the pages without moving the first arc strips and the second arc strips, and then the problem that the first arc strips and the second arc strips cannot be closed can be avoided, and the first arc strips and the second arc strips also do not need to be limited by the material type, and the service life of the double coil can be further improved.

1. Name of the product in this design: Protective Fence (Fiber Composite Material Type C). 2. Purpose of this design: It is used for area isolation and safety protection of railways and roads, serving as a barrier, protection, and warning. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: a 3D model.

The invention provides a method for detecting the porosity of a cement-based material by adopting an ultrasonic sound velocity method, and belongs to the technical field of detection of the porosity of the cement-based material.The method comprises the steps that a multi-phase sound velocity prediction model is established by preparing a gradient moisture content standard test piece, and a pore water saturation correction function is established by adopting a longitudinal and transverse wave velocity ratio; the moisture content interference is eliminated by using a saturation-sound velocity coupling inversion algorithm, the accurate detection of the three-dimensional porosity distribution of the to-be-detected material is realized by combining multi-angle ultrasonic tomography and a multiphase sound velocity distribution optimization game model, the result reliability is ensured through multi-path cross validation, the rationality of the porosity result obtained by inversion is judged, and the accuracy of the three-dimensional porosity distribution of the to-be-detected material is improved. When the porosity value exceeds the normal range threshold value corresponding to the material type, a multi-path sound velocity data cross validation program is started, the porosity is recalculated after abnormal measurement values are removed, and the technical problem that the porosity detection precision of the ultrasonic method is interfered by the water-containing state is solved.

The invention discloses a road construction waste recycling method and system, and relates to the field of construction waste recovery, and the method comprises the following steps: S1, carrying out on-site investigation and evaluation, determining the type, output and pollution degree of waste, and detecting the physicochemical properties of the waste; s2, waste materials are classified and collected, and the waste materials are sorted according to material types; s3, waste treatment planning is carried out, and a treatment scheme is selected by combining waste characteristics and utilizing scenes; step S4, crushing treatment: crushing the large materials by using a crusher; s5, detecting the performance of the waste material, namely detecting the performance of the waste material; and S6, regeneration treatment is conducted, specifically, different waste materials are recycled according to the types and performance of the materials. According to the method, the recovery process can be optimized, the resource utilization rate can be increased and the cost can be reduced by constructing the waste recovery model, analyzing and processing the waste data and generating the optimal recovery processing scheme and establishing the scientific data model.

1. The name of the design product: shovel (loose material type earthwork shovel). 2. The use of the design product: loose material type earthwork shovel for excavator. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view.

The invention discloses a multi-section furnace body movable type space material experiment furnace, and relates to the technical field of material preparation devices, the multi-section furnace body movable type space material experiment furnace comprises a driving assembly and a plurality of furnace bodies arranged side by side in the axial direction; each furnace body is provided with a hot cavity along the axial direction, the hot cavities between the adjacent furnace bodies can be communicated to form an integral thermal field thermal environment, and material samples with fixed positions can be accommodated in the hot cavities; the driving assembly is in transmission connection with the furnace bodies and can independently drive the furnace bodies so that the furnace bodies can move in the axial direction, and the furnace bodies can move relative to the material samples. According to the multi-section furnace body movable type space material experiment furnace provided by the invention, a temperature field mode can be conveniently adjusted through respective moving speeds, respective temperature control temperatures, relative position changes and the like of different furnace bodies, so that a variable temperature zone or an adjustable solidification speed is realized, and the space experiment requirements of more material types and more experiment modes are favorably met.

The invention relates to the technical field of warehouse management, in particular to a field warehouse management method and device based on a WMS, a medium and a product. The method comprises the steps of obtaining a project plan, a current progress and an actual inventory of a corresponding warehouse of a target project, and identifying a current stage and a next stage of the current progress in the project plan; obtaining stage consumption data of the current stage, extracting stage demand lower limits of the current stage and the next stage from the project plan, and determining a safety inventory of a warehouse corresponding to the target project based on the stage consumption data and the stage demand lower limits; generating a global material shortage list and a global excess material list of each material type based on the respective project plans and the current progress of the plurality of projects and the actual inventory and the safe inventory of the corresponding warehouse; and formulating a cross-project allocation strategy of each material type based on the global material shortage list and the global excess material list. According to the invention, material barriers among projects can be broken, and the material supply stability of each project is ensured.

The application relates to a mechanical hand intelligent grabbing closed-loop control method based on weighing-range finding fusion, a relationship model is established, the total weight G0 of a material bin before grabbing and materials in the material bin is weighed, the type of the materials in the material bin is determined, and an initial grabbing depth H1 is determined; the present grabbing task is executed; the total weight G1 of the material bin after grabbing and the remaining materials in the material bin is weighed, the present grabbing weight G is calculated; a deviation value AG=|G-G 目标 | is calculated, if AG<=weight deviation threshold value, the grabbing is qualified, and the next grabbing task is cyclically executed, and if AG>weight deviation threshold value, the grabbing is unqualified, and according to the deviation value AG, a correction depth Delta H of the next grabbing is determined, if G>G 目标 , the next grabbing depth H2=H1-Delta H; if G 目标 , the next grabbing depth H2=H1+Delta H; the next grabbing task is executed according to the corrected grabbing depth H2. Beneficial effects are that dynamic correction can be realized, and the deviation of single grabbing weight is reduced.

The invention discloses an optimization method for an electroosmosis drying model of a composite adsorption regenerated material. The optimization method comprises the following steps: acquiring parameters such as electric field intensity, electrokinetic potential, composite material type and proportion, composite material granularity and particle size, composite material particle density and composite material porosity; establishing an initial electroosmosis drying model of the composite adsorption regenerated material according to the parameters; performing a multi-factor coupling simulation test on the initial electroosmosis drying model to obtain a simulation data set containing an electroosmosis flow rate; and comparing the electroosmotic flow rate in the simulation data set with a preset performance standard, and performing iterative optimization on the initial electroosmotic drying model based on a comparison result to obtain an optimized drying model. Core parameters are efficiently screened through sensitivity analysis, rapid iterative optimization of the model is achieved, the output instructive parameters can provide a reliable basis for material selection and design of an electroosmosis dehumidification device, and the performance and practicability of an electroosmosis drying system are guaranteed.

The invention provides a multi-energy system cluster fault intelligent diagnosis and analysis method, which comprises the steps of collecting original vibration signal data corresponding to a bearing wear signal from a multi-energy system cluster equipment node, extracting specific frequency vibration and amplitude reduction process characteristics, and performing material type identification; according to the material type identification result, the propagation process of the bearing wear signal from the source device to the adjacent device is analyzed, and propagation path analysis data is obtained; according to the propagation path analysis data, identifying the signal contribution degree of each equipment node corresponding to the fault feature difference, and judging the origin point of the potential fault feature; obtaining a vibration frequency subset corresponding to the origin point of the fault feature, and extracting the fault feature after feature correction; and determining the position of fault source equipment in the multi-energy system cluster according to the extracted fault features.

The application discloses a kind of compatible multiple incoming material type electric power fitting automatic loading and unloading operation device, including mechanical arm and identification system, conveying line group and mechanical arm clamp group.Mechanical arm and identification system include scene recognition system, flexible mechanical arm sliding device, material identification system and flexible mechanical arm, scene recognition system is used to obtain the panoramic image of material in carriage and identify the packaging type and distribution position of material, material identification system is used to the material of target grabbing area is positioned and size identified again.Conveying line group at least includes the servo telescopic conveying line that can retract along the length direction of carriage, the access section of servo telescopic conveying line is located in the operation range of flexible mechanical arm.The application visual identification, multiple clamp library, follow-up transport mutually cooperate, realize the leap of electric power fitting warehousing logistics link from manual handling to full automation loading and unloading, with the significant technical progress of cost reduction and efficiency increase, operation precision, scheduling intelligence.

This application discloses a method and apparatus for material classification, a machine-readable storage medium, and an electronic device. The classification method includes: traversing model files to establish a first dataset, a second dataset, a third dataset, a fourth dataset, a fifth dataset, a sixth dataset, and a seventh dataset; for each object in each of the third, fourth, fifth, and sixth datasets, using an AI large language model, determining the corresponding recommended material type, and assigning the determined recommended material type to the object's material classification attribute. This achieves automated material classification.