186results about How to "Reduce production risk" patented technology

The invention discloses a coal mining intelligent scheduling method based on an artificial intelligence platform. The method comprises the following steps: S1, constructing a data set; s2, preprocessing the data set; s3, analyzing the preprocessed data set to generate an analysis result; s4, based on an analysis result, constructing and training a prediction model by adopting a variational auto-encoder and a graph neural network; s5, multi-agent deep reinforcement learning is adopted, a hybrid expert model and a distributed depth deterministic strategy gradient are combined, and an optimization model is constructed and trained; s6, predicting the fault of the equipment by using the prediction model, generating a prediction result, performing early warning in advance, and taking measures; s7, dynamically adjusting a production plan by using the optimization model according to the prediction result and the real-time data, performing resource scheduling, and optimizing resource allocation; and S8, establishing a feedback mechanism, collecting feedback information, and optimizing and improving a resource scheduling strategy. According to the invention, efficient intelligent scheduling is realized by using big data analysis, deep learning and a multi-agent system.

The invention discloses a cloth defect detection method and system based on machine vision, and relates to the technical field of detection and evaluation, and the method comprises the following steps: optimizing a cloth detection environment, deploying an industrial camera and a sensor to capture an image of a cloth surface and environmental factor data, and preprocessing the collected data; according to the preprocessed data, defect features and environment interference features are extracted, and the extracted defect features and environment interference features are marked. According to the cloth flaw detection method and system based on machine vision, continuous and uninterrupted detection of cloth surface flaws is realized through automatic image acquisition and processing, and compared with a traditional manual detection mode, the detection efficiency is greatly improved, the labor cost is reduced, and the detection efficiency is improved. Automatic detection can ensure that products on a production line quickly pass through a detection area, and defect positions are found and marked in time, so that subsequent treatment is quicker and more accurate.

The invention relates to the technical field of intelligent temperature control, and discloses an intelligent temperature control lead-free tin bar production method and device.The method comprises the steps that data of a plurality of sensors of a production line are collected and preprocessed, and a time sequence data set is obtained; carrying out attention-guided position-sensitive multiple interpolation to obtain a target data set; constructing and training based on the target data set to obtain an anomaly recognition model; according to normal production data screened by the anomaly recognition model, analysis is carried out based on an implicit subspace recognition regression neural network of orthogonal basis decomposition and reconstruction, and a production process parameter model is obtained; based on the production process parameter model, a multi-task feature fusion framework is used for parameter optimization, target production process parameters are obtained, the problem of data missing in the production process can be effectively solved, abnormal conditions can be accurately recognized, self-adaptive process parameter optimization can be conducted according to the characteristics of different production lines or batches, and the production process parameter optimization efficiency is improved. Therefore, the production quality and efficiency of the lead-free tin bar are improved.

The invention discloses a probe card simulation method and system based on counter-acting force analysis, which are used in the field of wafer simulation test, and the probe card simulation method comprises the following steps: integrating multiple physical field working conditions to construct a probe card geometric model, and importing the probe card geometric model into finite element simulation analysis software; carrying out grid division on the geometric model of the probe card by utilizing the hybrid voxel tree model, adjusting the grid density according to the distribution requirement of the multi-physical field, and setting a simulation boundary condition by utilizing a preset boundary condition template according to the actual simulation requirement; starting a simulation calculation process based on the adjusted grid density and simulated boundary conditions; and providing a visual interface of physical field distribution and a structural stress state in the simulation calculation process, and performing iterative optimization on the performance of the probe card in the simulation process according to a reactive force distribution result. According to the method, the grid density is automatically adjusted to adapt to changes of a physical field, and it is ensured that higher simulation precision is obtained in a key area.

The invention provides an ultrafast laser heat dissipation state real-time monitoring system based on cloud computing, and relates to the technical field of laser heat dissipation, and the system comprises a laser monitoring module which is used for transmitting ultrafast laser and is internally provided with a temperature sensor so as to monitor the working temperature of a laser in real time; the data acquisition module is used for being connected with the laser monitoring module, acquiring temperature data and key parameters, including laser power and working current, of the temperature sensor in real time, and uploading the temperature data and the key parameters to the cloud server; and the cloud analysis module is used for receiving and analyzing the temperature data and the key parameter data, identifying an abnormal temperature mode, predicting a potential overheating risk and calculating heat dissipation efficiency to obtain an analysis result. According to the invention, comprehensive, real-time and intelligent management of the heat dissipation state of the laser is realized, the operation stability and safety of the laser are effectively improved, the overheating risk is reduced, the heat dissipation efficiency is optimized, and remote monitoring and data analysis services are provided for users.

The invention relates to the technical field of assembly line scheduling, in particular to an intelligent scheduling method and system for an automatic assembly line of a charging pile. The method comprises the following steps: acquiring a charging pile assembly production log; performing sliding window segmentation processing on the charging pile assembly production log, and performing staged assembly demand feature analysis to obtain assembly demand feature data of different stages; the real-time production progress of each assembly line is extracted based on the charging pile assembly production log; demand supply deviation prediction is carried out on the real-time production progress of each assembly line according to the assembly demand characteristic data of different stages, and assembly lines lack of productivity are marked; an all-dimensional real-time monitoring image of the assembly line is collected; and carrying out dynamic behavior analysis on the omnibearing real-time monitoring image of the assembly line, carrying out process operation logic analysis, and generating multi-stage process operation logic. According to the invention, high-efficiency and self-adaptive intelligent scheduling of the assembly line is realized.

The invention discloses a product process route generation method and device based on a bill of materials, a medium and equipment, and belongs to the technical field of computer intelligence. The method comprises the following steps: acquiring an engineering drawing of a to-be-processed product; extracting a bill of material of the to-be-processed product according to the engineering drawing of the to-be-processed product; according to the bill of material of the to-be-processed product, establishing association relationship data between parts related to the to-be-processed product; and according to the incidence relation data among the parts related to the to-be-processed product and the existing process database, a preliminary process route of the to-be-processed product is generated through operation. The device, the medium and the equipment can be used for realizing the method. By integrating the functions of engineering drawing analysis, BOM automatic generation, process database matching, process route intelligent planning and optimization and the like, full-automatic conversion from a product design drawing to a production process route is realized, and powerful support is provided for digital transformation of enterprises in the manufacturing industry.

The invention provides a process window optimization method and device, a medium, a program product and a terminal, and solves the problems of low light intensity contrast ratio, limited process window and high finished product defect rate of weak point and dead pixel areas through an objective function optimization and numerical programming solution method. And establishing a reasonable optimization model by taking the sum of squares of light intensity logarithmic slopes of weak and dead pixel areas as an optimization target and combining an edge section moving range, an edge position error and mutual influence factors. And meanwhile, a plurality of matrix methods such as a sparse matrix and a dense matrix are introduced, so that the optimization efficiency and precision are improved, the accurate optimization of the mask pattern is realized, the process window is expanded, the defect rate is reduced, the process stability and adaptability are enhanced, and the production efficiency and the product quality are remarkably improved.

The invention relates to the technical field of process management, in particular to a sealing integrated collaborative process optimization method and system. The method comprises the following steps: obtaining sealing process data; performing sensor data acquisition according to the sealing process data to obtain a multi-modal sensor acquisition data set; performing data preprocessing on the multi-modal sensor acquisition data set to generate a standard multi-modal sensor acquisition data set; performing process flow analysis on the sealing process data to generate sealing process flow data, the sealing process flow data including a sealing flow, a cover closing flow and a cover pressing flow; and performing intelligent process modeling on the sealing process, the cover closing process and the cover pressing process to generate a process procedure mathematical model. According to the invention, through multi-modal data acquisition, detailed process flow analysis, real-time monitoring and dynamic adjustment strategies, the flexibility and adaptability of sealing process production process management are improved.

The present invention provides a production traceability and transaction collaboration method and system for an MES system, which relates to the technical field of production traceability, including using graph database technology to construct a production process knowledge graph, mapping the fused multi-source heterogeneous data to the entities and relationships of the knowledge graph; based on a time series graph algorithm, establishing a dynamic time series association in the knowledge graph to form a traceable production process chain; based on a knowledge graph and anomaly detection model, constructing a transaction trigger mechanism to automatically identify production transactions that need to be collaboratively processed and obtain transaction collaboration records; using a reinforcement learning algorithm to establish a multi-agent collaborative decision-making model, which can adaptively allocate tasks and resources according to the current production status and historical experience; through a sequence-to-sequence model enhanced by an attention mechanism, converting unstructured collaboration requirements into executable workflows; and automatically generating a multi-dimensional production analysis report based on the traceable production process chain and transaction collaboration records.

The invention belongs to the technical field of cutter wear monitoring, and discloses a titanium alloy aviation structural member rough machining cutter wear self-adaptive monitoring method, which comprises the following steps: step 1, determining a cutter wear monitoring threshold T0 according to a machine tool spindle load torque value; 2, within the fixed period T1, a numerical control machine tool spindle load torque value set A in the rough machining process of a tool is collected; 3, performing low-pass filtering on the data in the set A to obtain a data set B; 4, performing kurtosis value analysis and evaluation processing on the set B to obtain a data set X; 5, performing data classification on the data set X by using a support vector machine, and obtaining a data set T by taking a set with the maximum number after classification; step 6, calculating a torque average value # imgabs0 # of the data set T; and step 7, performing cutter wear self-adaptive monitoring on the torque average value # imgabs1 # of each period according to a threshold value T0.

The present application relates to a fan fault detection method and system based on AI auscultation, and a fan safety system, which collects a third sound signal during the operation of the fan blades, performs digital-to-analog conversion and noise reduction processing on the third sound signal to obtain a sound signal C, extracts the actual features of the sound signal C, and compares them with the standard features to calculate the first similarity; when the first similarity is less than or equal to the first preset value, the actual features are compared with any one of the fault feature sets, and the second similarity is calculated respectively, the second similarity is arranged in descending order, and the first M fault features corresponding to the second similarity are taken to obtain the corresponding fault type or a combination of M fault types; after detecting a fault, an alarm is sounded and fault diagnosis advice and maintenance plans are provided. The above scheme can use AI auscultation combined with deep learning technology to extract and compare acoustic features of the real-time collected working noise to detect whether the blades are faulty in real time.

The invention discloses a standard component design effectiveness evaluation method. The method comprises the following steps: determining form design parameters, material characteristics and a production process flow according to a standard component design scheme; determining original morphological parameters and material attributes of the original processing material according to the production process flow, and applying the original morphological parameters and the material attributes to the finite element model; the production process flow is simulated through process simulation software, and state parameters of the standard part in the whole machining and forming period are obtained; driving the finite element model to enter processing and forming dynamic performance analysis of the standard component based on the state parameters to obtain multiple performance indexes of the standard component; and evaluating the plurality of performance indexes based on preset performance index requirements to obtain an evaluation result of the design effectiveness of the standard component. By physically simulating the production process of the standard component and performing finite element analysis on the whole cycle of the production process, the effectiveness of the design of the standard component is extracted and evaluated, and a designer can conveniently optimize the standard component in the design stage.

The invention discloses a molybdenum disulfide acid leaching purification process, relates to the technical field of molybdenum disulfide purification, and aims to solve the problems of waste acid recycling, wastewater treatment and equipment corrosion in the molybdenum disulfide purification process. The molybdenum disulfide acid leaching purification process comprises the following steps: S1, acid purification: adding a molybdenum concentrate raw material into a reaction kettle; adding reaction acid into the reaction kettle according to a certain solid-to-liquid ratio, heating the reaction kettle to react for a period of time, and cooling to dissolve impurities in the molybdenum concentrate; s2, filter pressing and cleaning: conveying the acid-washed material to a plate frame for filter pressing to form a filter cake, cleaning the filter cake with clear water for 2-4 times until the wastewater is neutral, and conveying the filter cake to the plate frame for filter pressing again; s3, repeating acid purification and filter-pressing cleaning for several times until various acids are used up in the process; and S4, drying: putting the cleaned filter cake into a drying system for drying to obtain the high-purity molybdenum disulfide with the purity of more than or equal to 99%. According to the acid leaching purification process, impurities in molybdenum disulfide are selectively dissolved, the purity of molybdenum disulfide is remarkably improved, and the industrial application requirement is met.

The invention discloses a thermoelectric power plant abnormal state monitoring method and system based on deep learning. The method comprises the following steps: S1, extracting a thermoelectric power plant image sequence frame X from a video; s2, constructing a thermoelectric power plant image multi-level spatial-temporal feature extraction model which comprises a multi-scale spatial-temporal feature extraction sub-model, a spatial-temporal feature enhancement sub-model and a spatial-temporal feature attention fusion sub-model; extracting the multi-level spatial-temporal characteristics of the thermoelectric power plant image; s3, predicting a category label of the multi-level spatial-temporal characteristics of the thermoelectric power plant image, and constructing a loss function to evaluate and predict a difference between the category label and a real label to obtain abnormal state information; and S4, establishing a multi-level early warning system, and triggering different levels of early warning according to the severity of the abnormal state. According to the invention, abnormity monitoring and early warning can be automatically carried out, and the safety performance is improved.

The invention discloses a computer data intelligent identification system and method, and relates to the technical field of data intelligent identification. Equipment state parameters are obtained by carrying out real-time monitoring and state evaluation on equipment in a large-scale factory, comprehensive analysis is carried out according to the equipment state parameters to obtain the latest acquisition frequency of the equipment, the data acquisition frequency can be dynamically adjusted according to the equipment state, self-adaption of computer data acquisition of the large-scale factory is achieved, and the data acquisition efficiency is improved. The change of the equipment state is better reflected, and the validity and timeliness of data acquisition are ensured; through comprehensive analysis of equipment operation values, vibration abnormal values, important scores and the like of all equipment in the large-scale factory, the production state of the large-scale factory is judged, corresponding decisions are output, changes of the production state can be quickly responded, the risk of equipment faults to production is reduced, and the safety and stability of the production process are ensured; and meanwhile, an automatic decision output module can reduce errors and delay of manual judgment and improve the decision speed and accuracy.

The utility model relates to the technical field of puncture outfit, and provides a sealing valve assembly and a puncture outfit, the sealing valve assembly comprises a sealing upper cover, a sealing lower cover connected to the lower portion of the sealing upper cover, an integrally-formed elastic sealing valve and a sealing cover, the sealing upper cover and the sealing lower cover form a mounting cavity, and the elastic sealing valve is located in the mounting cavity; the elastic sealing valve comprises a sealing valve mounting part and a funnel part narrowing and extending away from the sealing valve mounting part from the sealing valve mounting part, an orifice is formed in the tail end of the funnel part, and the peripheral wall of the orifice can wrap surgical instruments with different diameters penetrating through the orifice; the integrally-formed protection piece is installed in the elastic sealing valve and comprises a main body ring and a stopping part connected to the main body ring, the main body ring is connected with the sealing valve installation part in a clamped mode, and the stopping part covers the upper surface of the funnel part and is used for stopping the funnel part from moving in the direction from the sealing lower cover to the sealing upper cover; the sealing valve assembly solves the problems that in the prior art, a puncture outfit is large in structural part number, large in mold number, large in assembly procedure number and high in manual assembly cost.

The invention discloses a broken polycrystalline silicon material packaging moisture residue prevention water quenching system, and particularly relates to the technical field of polycrystalline silicon processing, and the system comprises an integrated control unit, a water quenching module, a moisture residue prevention processing module, a packaging module, a crushing module, a screening module, a drying module, a quality detection module and an environment adaptability module. According to the water quenching system for preventing moisture residues in polycrystalline silicon broken material packaging, the material utilization rate is increased through efficient crushing and accurate screening, the waterproof performance of a product is enhanced through vacuum degassing and automatic humidity control, the product quality consistency is ensured through automatic quality detection, and the production efficiency is improved. And the safety of the system is improved through integrated control and an emergency discharge device. The characteristics jointly improve the production efficiency, and ensure the stability and reliability of the product in a changeable environment.

The invention discloses an electricity consumption information monitoring method and system based on hardware industry electric power big data, and belongs to the technical field of electric power information monitoring, and the method comprises the steps: S1, calculating segmented energy consumption data and classified energy consumption data based on electricity consumption data; s2, correcting the classified energy consumption data based on the working duration and rated power of the production equipment, and detecting whether the classified energy consumption data is abnormal or not; s3, constructing a fitting function by using the classified energy consumption data, the raw material feeding data and the finished product data, and judging whether the fluctuation information is abnormal or not; s4, judging the relationship between the power consumption data of the hardware feeding equipment and the threshold value to determine whether to adjust the feeding speed; s5, calculating the number of theoretical products based on the power consumption of the heating equipment, and adjusting the feeding speed if the actual number is smaller than a theoretical value; and S6, judging whether the heating equipment is abnormal or not according to the load current of the die forging equipment, and sending warning information. According to the scheme, multi-level power fault analysis is carried out on the hardware industry, so that the coverage range of power fault detection can be remarkably expanded.

The invention discloses a control and regulation system for hemostatic gauze production, which comprises a raw material supply control module, a production process monitoring module, an intelligent regulation execution module, a quality detection and feedback module and a human-computer interaction interface, and is characterized in that the raw material supply module is used for accurately controlling raw material supply and is provided with a material level sensor and a stirring device; the conveying speed is accurately regulated and controlled through a formula, the uniformity of raw materials is ensured, the production process monitoring module monitors key parameters in real time, the sensor wirelessly transmits data, and the intelligent adjusting module automatically adjusts equipment operation parameters. The quality detection module detects products and feeds back results, and a man-machine interaction interface is convenient to operate. Through cooperation of all the modules, raw material supply is accurately controlled, production parameters are monitored in real time, equipment operation is intelligently adjusted, product quality is strictly detected, convenient interaction is provided, the production quality and efficiency of hemostatic gauze are improved, cost is reduced, and high-quality and reliable hemostatic products are provided for the medical field.

The invention discloses a manufacturing unit innovation platform building method based on a digital twin industrial robot, and relates to the field of digital twin industrial robots, and the manufacturing unit innovation platform building method based on the digital twin industrial robot comprises the following steps: collecting a building parameter set, generating a construction plan according to the construction parameter set, inputting manual intervention, and combining the manual intervention with the construction plan to generate a construction scheme; and receiving building construction parameters, and comparing the building construction parameters with the building scheme to obtain a deviation correction data set. The building scheme is generated by collecting the building parameters and combining with manual intervention, then the building construction parameters and the building scheme are compared in real time to obtain deviation correction data, and the building accuracy of the manufacturing unit is ensured. The process not only improves the building efficiency, but also effectively reduces the production risk caused by the building deviation, and improves the overall performance of the manufacturing unit.

The utility model discloses a material taking device of connecting rod type stamping equipment, and relates to the technical field of stamping equipment. The device comprises a shell, a fixing plate is fixedly connected to the inner wall of the shell, a hydraulic telescopic rod is fixedly connected to the top of the fixing plate, the bottom end of the hydraulic telescopic rod penetrates through the fixing plate and is fixedly connected with an upper mold plate, a lower mold plate is fixedly connected to the interior of the shell, a discharging plate is movably arranged in the shell, and the discharging plate is arranged to be inclined; a material storage box is slidably arranged in the shell and located below the discharging plate, a through hole is formed in the shell and located below the lower die plate, a waste material box is arranged in the shell, a high-pressure air gun is arranged on one side of the discharging plate, connecting rod mechanisms are arranged on the two sides of the shell, the discharging plate moves to the position below the lower die plate, and only parts need to be blown off at the moment. The position adjusting frequency of the high-pressure air gun is reduced, production errors caused by position deviation are reduced, and the stability and reliability of a production line are improved.

The invention belongs to the technical field of synthesis of organic compounds, and particularly discloses a continuous production system and a production method of 1-(4-chlorphenyl)-3-pyrazole alcohol. The method is used for solving the problems of low production efficiency, high operation cost and danger and large wastewater discharge of a traditional intermittent hydrogen peroxide oxidation process. The production system comprises a raw material premixing tank, a conveying pump, an air source, an ejector, a reaction unit, a pH adjusting tank, a continuous filter, a temporary storage tank, a continuous dryer and an ion resin exchanger, the reaction unit comprises a plurality of static mixing tubular continuous flow reactors which are connected in series, static mixing elements are arranged in the static mixing tubular continuous flow reactors, and heat exchange jackets are arranged outside the static mixing tubular continuous flow reactors; heat exchange jackets or coil pipes are arranged on the outer side walls of the raw material premixing tank and the pH adjusting tank; and the ion resin exchanger is provided with a backwashing port. According to the invention, full-process continuous production is realized, green and safe preparation is realized, and the production efficiency, the product yield and the product purity are improved.

The invention belongs to the technical field of titanium-based compound powder, and particularly discloses low-oxygen non-stoichiometric titanium hydride powder and a continuous preparation method thereof. The preparation method specifically comprises the steps that raw material titanium is added into a continuous vacuum atmosphere rotary kiln, after hydrogen mixed gas is fed till the pressure in the furnace is stable, the raw material titanium sequentially passes through a preheating zone, a primary hydrogenation zone, a transition zone, a dehydrogenation zone, a transition zone, a secondary hydrogenation zone and a low-temperature cooling zone, and finally the raw material titanium is crushed and classified through airflow. The brittle and low-oxygen non-stoichiometric TiH1.924 powder can be prepared by optimizing the process parameters such as the temperatures of two-time hydrogenation and one-time dehydrogenation, the length of each area, the mixed gas of high-purity hydrogen and TiCl4 as inlet gas and the like, and a titanium alloy product prepared from the powder also has excellent processing formability and mechanical properties; and the method has continuous production capacity, so that the production efficiency is greatly improved, and the production risk is also reduced.

The invention provides a feeding and discharging tool suitable for automatic coating of optical lenses, which comprises a rotating cylinder, a lens placing plate detachably arranged on the outer side wall of the rotating cylinder, and a discharging clamping jaw capable of detaching the lens placing plate, the mirror placing plate is provided with a plurality of mirror placing holes arranged in an array, the mirror placing plate is also provided with a lens fixing device capable of fixing lenses from the hole walls of the mirror placing holes, the mirror placing plate is provided with mounting holes, and the hole walls of the mirror placing plate are provided with locking mechanisms; a plurality of quick fixing piles are arranged on the outer side face of the vertically-arranged rotating cylinder, the axes of the quick fixing piles are perpendicular to the rotating cylinder, the quick fixing piles can be coaxially inserted into the mounting holes and matched with the locking mechanism to lock the mirror plate, and releasing mechanisms are arranged on the quick fixing piles. And after the releasing mechanism is triggered, the quick fixing pile can release the locking mechanism, so that the mirror placing plate can move in the axis direction of the quick fixing pile, and the discharging clamping jaw can clamp the mirror placing plate.

The pipe ironing equipment for indoor water and electricity installation comprises a base, a hot melting device body is slidably arranged above the base, a moving groove is formed in the upper wall of the base in a penetrating mode, two moving blocks are slidably connected into the moving groove, moving blocks are fixed to the upper walls of the moving blocks, and the two moving blocks are located on the two sides of the hot melting device body; according to the scheme, the appropriate die head size is selected according to the diameter of the pipeline, the movable plate can slide by pulling the pull plate, the position of the limiting ring is adjusted, the pull plate is loosened, the mold head can be clamped, the mold head can be clamped, the mold head can be clamped, and the mold head can be clamped. At the moment, the circle centers of the limiting rings and the circle center of the die head are located at the same height, the pipeline passes through the limiting rings and is connected with the die head in a sleeving mode, bolts are rotated to fix the pipeline, and after the pipeline is heated to the splicing temperature, the two limiting rings on a motor are started to be away from each other till being separated from the die head; and the motor is started again, so that the two pipelines are spliced together and fixed.

The present invention relates to the field of chip manufacturing, and proposes a method and system for realizing the preparation of semiconductor memory chips, the method comprising: first obtaining chip parameters, selecting semiconductor materials and pre-processing, determining the area to be deposited, and then depositing insulating layers and conductive layers to build a multi-layer structure framework, and then determining the optimal thickness and layout of each layer and calculating the expected reading and writing values, then determining the performance indicators according to the expected reading and writing values, evaluating the feasibility of preparation to obtain preparation evaluation data, querying the influencing factors to calculate the influence degree value, and then configuring the packaging materials according to the influence degree value to build a curing environment, monitoring the curing process state and tracing the abnormality, and finally analyzing the target concentrated in the abnormal source, identifying the abnormal storage factor, and generating a chip preparation plan based on this monitoring feedback data. The present invention can improve the preparation stability of semiconductor memory chips.

The invention discloses a remote monitoring system for intelligent information of facility agriculture, which specifically relates to the technical field of intelligent agricultural monitoring, and comprises a microclimate monitoring module, a microclimate comprehensive analysis module, a soil microorganism monitoring module, a microorganism evaluation module and a remote management module; the microclimate monitoring module collects microclimate data in a greenhouse and forms a data set; the comprehensive analysis module performs deviation analysis on the microclimate data and determines whether to trigger an evaluation mechanism; the soil microorganism monitoring module collects microbial activity data in real time; the microorganism evaluation module performs quality evaluation when the evaluation mechanism is triggered and generates a quality evaluation value; the remote management module accesses data through a network and determines whether to issue an abnormal warning according to the evaluation value; the invention can issue an alarm in time at an early stage when the microbial activity is too high or too low, so that managers can take appropriate intervention measures to ensure the balance and stability of the soil environment, thereby improving the overall production efficiency of crops.

The invention discloses an unmanned loader scheduling system and method in the technical field of production resource scheduling, the unmanned loader scheduling system comprises a proportion management module and a task distribution module, the proportion management module is used for selecting a specified effective material proportion according to the production demand of a production scene; the task distribution module is used for selecting a target material storage pile according to the effective material ratio and material information pre-configured in the production scene, and driving a loader to take materials from the target material storage pile to execute a loading task; and the control module is used for selecting a target unloading bin according to the specified unloading mode and driving the loader to execute an unloading task on the unloading bin. The system is applied to an unmanned production scene, the proportion management module ensures that the material proportion is accurate in the production process, and the task distribution module can adjust a task execution strategy in real time in the operation process, so that the system can quickly respond to the change of a production environment or demand, and the continuity and stability of production are ensured.

The utility model belongs to the field of aluminum product processing, particularly relates to an automatic feeding device of an aluminum product processing production line, and aims to solve the problems that an existing aluminum product of which the size is smaller than the distance between the middle points of two moving rods can only be adsorbed through four vacuum chucks of which the suction force cannot be adjusted at the same time, the suction force capacity is relatively small, and the suction force cannot be adjusted. In order to solve the problems that in the prior art, suction forces of all suction cups are different during adsorption, stability is relatively poor, adsorption of aluminum products is removed in a vibration mode, and the aluminum products cannot fall down horizontally and are prone to collision due to the fact that the suction forces of all the vacuum suction cups are not uniform, the aluminum products comprise a movable frame and an installation disc. The device has the advantages of being high in flexibility, efficient in cleaning function, stable and reliable in adsorption mechanism, high in automation degree, compact in structure, easy and convenient to operate and the like between the two connecting columns, the production efficiency and product quality of an aluminum product machining production line can be remarkably improved, and the production cost and risk are reduced.