Abstract: Disclosed is an accuracy compensation method for discharge caustic alkali concentration measuring device in evaporation process, comprising following steps: step 1. collecting process data of instrument values and laboratory values of alkali liquor refractive index, temperature and caustic alkali concentration in the evaporation process; step 2. performing sliding average filtering, time series matching and normalization on the process data collected in step 1 to obtain preprocessed process data; step 3. inputting the preprocessed process data into an accuracy compensation model of the caustic alkali concentration measuring device to obtain compensation values; step 4. adding the compensation values of the caustic alkali concentration to the instrument values to realize on-line compensation of the caustic alkali concentration.

Abstract: Disclosed are an adaptive deep learning-based intelligent prediction method, apparatus, and device for a complex industrial system, and a storage medium. The method includes establishing a dynamic model for a complex industrial system; establishing an offline deep learning prediction model using the dynamic model; establishing an online deep learning prediction model using the offline deep learning prediction model; establishing a deep learning correction model based on a structure that is the same as a structure of the online deep learning prediction model; and correcting the online deep learning prediction model using the deep learning correction model; where the online deep learning prediction model predicts a parameter of the complex industrial system in real time.

Abstract: The invention provides a decision-making method of comprehensive alumina production indexes based on a multi-scale deep convolutional network. The method mainly consists of several sub-models: a multi-scale deep splicing convolutional neural network prediction sub-model reflecting the influence of bottom-layer production process indexes on the comprehensive alumina production indexes, a full connecting neural network prediction sub-model reflecting the influence of upper-layer dispatching indexes on the comprehensive alumina production indexes, a full connecting neural network prediction sub-model reflecting the influence of the comprehensive alumina production indexes at a past time on current comprehensive alumina production indexes, and a multi-scale information neural network integrated model for collaborative optimization of sub-model parameters.

Abstract: A multi-scale data acquiring and processing device and method for an aluminum oxide production process. The device includes a production index and variable configuring module, a data acquiring module, a data storing module, a main control module, a display module, a data processing module and a data transmitting module. The main control module is used for emitting a command, acquiring production indexes and variables generated in the aluminum oxide production process by different process control devices, and is used for performing unified processing, storage and display on the data, and further the data is transmitted through a transmitting module to systems or devices using the data.

Abstract: Provided is an aluminum oxide production operation optimization system and method based on a cloud-edge collaboration, which relates to the technical field of an aluminum oxide production operation optimization. According to the system and method, firstly the whole-flow data in the aluminum oxide production process is acquired, the data is pre-processed, then the pre-processed data is transmitted to a local collaboration production operation optimization unit, the local collaboration production operation optimization unit firstly judges working conditions for the current aluminum oxide production process, an optimization strategy needing to be operated at present is automatically switched according to the working condition, and the local operation optimization strategy obtains the actual setting value of the aluminum oxide production operation indexes.

Abstract: Provided is a cloud-edge collaboration forecasting system and method for aluminum oxide production indexes. The forecasting system performs forecasting algorithm selection, parameter configuration and model training on indexes and variables of the aluminum oxide production process at a cloud model training server, performs evaluation and parameter correction on the trained model to obtain an optimal training model, and pre-processes the data in the aluminum oxide production process at an aluminum oxide production index forecasting computer at an edge end. The trained model parameters are imported from the cloud, and further the trained forecasting model is used for forecasting aluminum oxide production indexes for different production processes.

Abstract: Disclosed is an accuracy compensation method for discharge caustic alkali concentration measuring device in evaporation process, comprising following steps: step 1. collecting process data of instrument values and laboratory values of alkali liquor diopter, temperature and caustic alkali concentration in the evaporation process; step 2. performing sliding average filtering, time series matching and normalization on the process data collected in step 1 to obtain preprocessed process data; step 3. inputting the preprocessed process data into an accuracy compensation model of the caustic alkali concentration measuring device to obtain compensation values; step 4. adding the compensation values of the caustic alkali concentration to the instrument values to realize on-line compensation of the caustic alkali concentration.

Abstract: The invention provides a decision-making method of comprehensive alumina production indexes based on a multi-scale deep convolutional network. The method mainly consists of several sub-models: a multi-scale deep splicing convolutional neural network prediction sub-model reflecting the influence of bottom-layer production process indexes on the comprehensive alumina production indexes, a full connecting neural network prediction sub-model reflecting the influence of upper-layer dispatching indexes on the comprehensive alumina production indexes, a full connecting neural network prediction sub-model reflecting the influence of the comprehensive alumina production indexes at a past time on current comprehensive alumina production indexes, and a multi-scale information neural network integrated model for collaborative optimization of sub-model parameters.

Abstract: Provided is a disc gap servo control device and method for a powder grinding system, which includes a disc powder grinding machine, a rotating speed regulating device of a rotating disc, the disc gap servo control device and a control cabinet. The method includes the following steps of: (1) inputting a control information; (2) an industrial computer obtaining a current disc gap and displaying the disc gap on a touch screen; (3) the disc gap servo control device adjusting the disc gap; (4) the current disc gap reaches a target disc gap; and (5) a frequency converter controlling a motor rotating speed, so that the actual rotating disc rotating speed can reach a target rotating speed of the rotating disc. The operation parameters of the rotating disc are observed by the industrial computer in real time, and finally a high-precision servo control of the disc gap can be realized.

Abstract: A multi-scale data acquiring and processing device and method for an aluminum oxide production process. The device includes a production index and variable configuring module, a data acquiring module, a data storing module, a main control module, a display module, a data processing module and a data transmitting module. The main control module is used for emitting a command, acquiring production indexes and variables generated in the aluminum oxide production process by different process control devices, and is used for performing unified processing, storage and display on the data, and further the data is transmitted through a transmitting module to systems or devices using the data.

Abstract: Provided is a disc gap servo control device and method for a powder grinding system, which includes a disc powder grinding machine, a rotating speed regulating device of a rotating disc, the disc gap servo control device and a control cabinet. The method includes the following steps of: (1) inputting a control information; (2) an industrial computer obtaining a current disc gap and displaying the disc gap on a touch screen; (3) the disc gap servo control device adjusting the disc gap; (4) the current disc gap reaches a target disc gap; and (5) a frequency converter controlling a motor rotating speed, so that the actual rotating disc rotating speed can reach a target rotating speed of the rotating disc. The operation parameters of the rotating disc are observed by the industrial computer in real time, and finally a high-precision servo control of the disc gap can be realized.

Abstract: A remote monitoring system and method for electricity demand of a fused magnesium furnace group. The system has a data acquisition device, a local PC, a cloud server and a remote PC. The data acquisition device has a voltage transformer, a current transformer, an active power transducer, a first slave computer, a plurality of multi-purpose electronic measuring instruments and a second slave computer. The method includes acquiring smelting current and smelting power of each fused magnesium furnace and electricity demand of the furnace group, controlling the switch off/on of each fused magnesium furnace according to the smelting current and the smelting power of each fused magnesium furnace and the electricity demand of the furnace group, sending basic monitoring data to the local PC, and achieving data exchange between the local PC and the remote PC through the Zookeeper technology.

Abstract: Provided is an optimized decision-making system for multiple ore dressing production indexes based on a cloud server and mobile terminals, including mobile intelligent terminals, a cloud server, a mobile industrial private cloud server, a collecting computer and process controllers PLC or DCS. The mobile industrial private cloud server calculates out multiple decision-making result solution sets; the intelligent mobile terminals determine the final decision-making results; the mobile industrial private cloud server calculates out process control set values; the mobile intelligent terminals determine the final process control set values; and the process controllers PLC or DCS control equipment on a production line for production according to the final process control set values. The present invention further provides an optimized decision-making method for multiple ore dressing production indexes adopting the optimized decision-making system.

Abstract: A remote monitoring system and method for electricity demand of a fused magnesium furnace group. The system has a data acquisition device, a local PC, a cloud server and a remote PC. The data acquisition device has a voltage transformer, a current transformer, an active power transducer, a first slave computer, a plurality of multi-purpose electronic measuring instruments and a second slave computer. The method includes acquiring smelting current and smelting power of each fused magnesium furnace and electricity demand of the furnace group, controlling the switch off/on of each fused magnesium furnace according to the smelting current and the smelting power of each fused magnesium furnace and the electricity demand of the furnace group, sending basic monitoring data to the local PC, and achieving data exchange between the local PC and the remote PC through the Zookeeper technology.

Abstract: Provided is an optimized decision-making system for multiple ore dressing production indexes based on a cloud server and mobile terminals, including mobile intelligent terminals, a cloud server, a mobile industrial private cloud server, a collecting computer and process controllers PLC or DCS. The mobile industrial private cloud server calculates out multiple decision-making result solution sets; the intelligent mobile terminals determine the final decision-making results; the mobile industrial private cloud server calculates out process control set values; the mobile intelligent terminals determine the final process control set values; and the process controllers PLC or DCS control equipment on a production line for production according to the final process control set values. The present invention further provides an optimized decision-making method for multiple ore dressing production indexes adopting the optimized decision-making system.