10results about "Registering/indicating during manufacturing process" patented technology

The present invention belongs to the technical field of automated steel production and discloses a method for predicting the composition of molten iron applied to an automated steel production process, wherein the method is: performing a sampling and an examination of molten iron in a process in which the molten iron is tapped from a torpedo tank into a ladle, and calculating a loss of composition of this molten iron, wherein the composition of the molten iron is calibrated before the molten iron is tapped into the ladle;Performing a sampling and analysis of the molten iron in a process where the molten iron is transferred from the ladle to a converter, and calculating any loss in the composition of this molten iron, wherein the composition of the molten iron is calibrated before the molten iron is transferred to the converter. The present invention is easy to use and implement, and can acquire more accurate and reliable real-time parameters for computational models at all levels; in its specific application, the present invention does not require the modernization of existing automated steelmaking equipment; and it can be applied to a wide range of automated steelmaking scenarios.

The application discloses a method for evaluating the loading operation performance of a excavator, an electronic device and a storage medium, and the technical scheme is that a gyroscope is installed on the left and right handles of the excavator, the fixed working condition and the fixed material throwing are excavated, the operation actions of the operating hand are recorded by the gyroscope, and the excavator operation performance is evaluated by the composite degree and the control time of each action of the handle. The application has the characteristics of simple operation and intuitive data.

The application discloses a coating abnormality analysis method and related equipment and a storage medium. The coating abnormality analysis method comprises the following steps: obtaining a coating abnormality feature input by a user, wherein the coating abnormality feature reflects a phenomenon of the current coating abnormality; obtaining event features of a plurality of coating abnormality basic events corresponding to the coating abnormality feature in a fault tree, and obtaining a target probability corresponding to the coating abnormality feature; calculating abnormal probabilities of the plurality of coating abnormality basic events based on the features of the plurality of coating abnormality basic events and the target probability; calculating decision game contribution degrees of the coating abnormality basic events based on the abnormal probabilities, and selecting at least one coating abnormality basic event as a key factor of the current coating abnormality based on the decision game contribution degrees of the coating abnormality basic events. The above scheme can alleviate the problem of missing key factors caused by relying on experience judgment or local data troubleshooting.

This invention relates to the field of digital manufacturing and industrial information management technology, and discloses an information management system for a digital processing workshop, comprising: acquiring equipment abnormal event records to generate a subgraph of equipment fault propagation with observational evidence; calculating process similarity to screen source domain products; fusing source domain prior causal graphs to perform Bayesian causal structure learning to generate a posterior cross-process quality causal subgraph; calculating conditional Granger causal relationships to generate a set of cross-layer causal edges; assembling a two-layer causal graph; establishing an extended structured Bayesian network model; performing structured variational inference to output joint attribution results; and performing propagation path tracing to generate an attribution report with uncertainty quantification. This invention solves the technical problems in related technologies of digital processing workshop fault attribution, such as the inability to effectively integrate multi-source heterogeneous information from the equipment layer and process layer, the difficulty in completing cross-process causal structure learning under limited sample conditions, and the lack of uncertainty quantification in the attribution results.

An example method for enabling inspection of a space includes: obtaining a space map representing the space to be inspected; rendering the space map to be presented at an inspection station for the inspection of the space; in response to navigation data, navigating within the space map for the inspection of the space; in response to a selection of an inspection capture point defined in the space map, presenting data representing the space captured at the inspection capture point; and generating inspection result data for the space, the inspection result data representing results of the inspection.

The application discloses a hydrogen-rich smelting blast furnace initial coal gas flow temperature field optimization method and system. The method comprises the following steps: controlling hydrogen-rich gas, coal powder and coke to be sequentially combusted in front of tuyere; regarding the front of the tuyere as an adiabatic environment, collecting blast furnace tuyere data; calculating the theoretical combustion temperature of the front of all tuyeres of the blast furnace; under the premise of ensuring the total coal powder injection amount, gradually reducing the coal powder injection amount of the hydrogen injection tuyere, and increasing the coal powder injection amount of the tuyere without hydrogen injection until the absolute error of the calculated theoretical combustion temperature T0 of the hydrogen injection tuyere and the theoretical combustion temperature T1 of the tuyere without hydrogen injection is less than the set error threshold. The method can effectively improve the uneven distribution of hydrogen cold-state injection of the initial gas flow of the blast furnace through analysis of the blast furnace tuyere data.

The application relates to the technical field of production parameter storage methods, and discloses a shell production parameter storage method and system based on an Internet of Things, which comprises the following steps: determining a sub-storage path of a production data set of each shell according to a bidirectional storage path determined by the data amount of the production data set of each shell and the Internet of Things, a storage node of the production data set and a storage congestion coefficient of the Internet of Things; determining a plurality of abnormal storage parameters according to each sub-storage path; determining an abnormal storage area according to the plurality of abnormal storage parameters and corresponding production procedures; determining a storage abnormality processing item based on the abnormal storage area and a storage progress of the production data set of each shell; determining a plurality of sub-processing events according to the identification of the storage abnormality processing item; and determining a production parameter storage system based on the plurality of sub-processing events, each sub-storage path and a production state of each shell. The method can realize the synchronous storage of production parameters of shells in a production process.

The application provides a glass production line cold end stress detection system and method. It belongs to the technical field of glass production detection. The method comprises the following steps: collecting stress-related spectral data of the cold end region of the glass production line through a multispectral stress sensing array, and preprocessing the collected spectral data to obtain a pretreated spectral data set; extracting spectral features from the pretreated spectral data set to construct a spectral feature vector set; based on the spectral feature vector set, extracting the time-space features of the glass cold end stress by using a time-space correlation analysis algorithm to obtain a stress time-space feature matrix; and collecting spectral data through the multispectral stress sensing array, which avoids the influence of traditional contact detection on the glass product and the production line, and improves the detection accuracy and real-time performance.

This invention discloses a method for predicting the polishing effect of a flexible abrasive tool under eccentricity. The method involves measuring key physical parameters of the abrasive tool; establishing a deformation model of the abrasive tool under no-load conditions based on the spindle speed and key physical parameters; determining the motion trajectory of the abrasive tool based on the feed rate and spindle speed; calculating the theoretical contact depth curve when the abrasive tool contacts the workpiece based on the radial depth of cut and the initial rotation angle of the abrasive tool; and obtaining the theoretical polished surface produced under eccentricity based on the time axis variation. This invention can effectively predict the polishing effect of a flexible abrasive tool under eccentricity, accurately simulate the contact state between the abrasive tool and the workpiece during the polishing process, and determine the influence and laws of flexible abrasive tool eccentricity on the actual machined surface. It provides a theoretical basis and technical support for optimizing process parameters and controlling surface quality in subsequent actual machining, and also provides a reference for the design and application of flexible abrasive tools, strongly promoting the development and application of CNC machining technology.