42 results about "Industrial data processing" patented technology

The invention discloses an optimized execution estimation method for massive data processing and storage process in an industrial process. The method includes S1: structural modeling of industrial data acquisition systems; S2: calculating desired performance indicators of industrial data processing and storage processes according to the model; S3: a strategy for establishing a massive data processing layer, a transport layer, and a storage layer; S4: extracting process parameters related to performance indicators from the database; S5: calculating actual performance indicators; S6: comparing the expected performance index and the actual performance index, and adjusting the data processing and storage mechanism of the next cycle until the performance of the industrial data acquisition system meets the requirements. The beneficial effects obtained by the method are: the efficiency of the whole data collection and storage process can be improved, the data can be sorted and excavated in anorderly manner, and the storage space is saved, optimizing the collection and storage process of massive data in industrial processes, and preparing for subsequent data analysis.

The invention belongs to the technical field of Internet of Things data acquisition and monitoring. The invention discloses an embedded industrial Internet of Things data acquisition monitoring systemand method. The embedded industrial Internet of Things data acquisition monitoring system comprises an industrial data acquisition module, an industrial data processing module, an industrial data transmission module, a central control module, an Internet of Things communication module, a data calibration module, a data analysis module, a data statistics module, a cloud storage module and a display module. Through the industrial data processing module, the accuracy, efficiency and quality of data processing are improved, data visualization is achieved through the analysis module, trend comparative analysis can be conducted on various kinds of data, the incidence relation between the data is found, the requirement for data analysis in industrial production is met, engineers are assisted inaccurately mastering the current production state and the historical production state, and more scientific and reasonable decisions are made; the cloud storage module is simple in storage, can be compatible with various databases, is large in page view, and meets the demands of third-party access.

The invention relates to a chemical system multi-working-condition fault detection method based on local adaptive standardization and belongs to the technical field of chemical process monitoring, industrial data processing and process system engineering. According to the method, a local adaptive standardization method is provided, the variational automatic encoder technology of the deep neural network is applied, an average value of the data in the local moving window is calculated to serve as an average value parameter of local adaptive standardization, different average values are used fordifferent data, and the adaptive capacity is achieved. The method is advantaged in that local adaptive standardization processing is utilized, and fault detection is carried out by detecting whether the data in a local moving window deviates or not, and the method can be suitable for any working condition, has higher accuracy and stronger generalization ability, can meet the requirement of real-time detection, and avoids chemical accidents or reduces the harm caused by accidents through early warning of faults.

The invention discloses a building ground decoration industrial data processing method, an electronic device and a storage medium. The method includes the steps of responding to a calling instructionof a user, calling decoration group module data corresponding to the calling instruction as current decoration ground module data, receiving individualized configuration data related to the current decoration ground module data and input by the user, modifying material information of the current decoration ground module data according to the individualized configuration data to obtain combined decoration ground module data, calling a customizing standard corresponding to the current decoration ground module data as a current customizing standard, verifying the combined ground module data, andoutputting a module data list and a material list if the combined decoration ground module data meets the current customizing standard. With the building decoration part modularization as the core, the industrial production organization as the basis and the on-site decoration type construction as the means, a novel assembly type ground system suitable for industrialization on the Internet era is obtained.

The invention discloses a system for automatically generating a report from industrial data. The system comprises an industrial data server, a distributed processing server, a report server, an industrial data database and a report database, the industrial data server is used for collecting industrial data and driving the distributed processing server to process and package the distributed industrial data according to a pre-configured data processing rule and then input the packaged industrial data into the industrial data database; and the report server is used for selecting one of the automatically generated industrial report template files according to a preset timing task, calling the corresponding industrial data, and filling or replacing part or all of the activity cells in the industrial report template file after processing to generate a report file. According to the invention, the complex work of manual calculation and input can be overcome by automatically acquiring the industrial data and automatically generating the report, so that the report generation mode and the whole data and report processing process are more flexible, the adaptability is high, and the data processing pressure is relieved by adopting the distributed processing server.

The invention relates to industrial data processing, in particular to a big data interaction method for industrial production, and a main logic architecture of the method comprises a database, blockchain data, a data interaction center, a sub-data platform and a data unit. The method includes the step S1 that parameters such as a warehousing system, a security system, instruments and meters, equipment parameters, a power medium, a production process, a raw material ratio and the like in an industrial production link are independently parameterized and integrated by taking a time axis as a reference and are stored in a register, and the register is taken as a variable and the parameters are transparently transmitted into the sub-data platform through a DTU (Data Transfer Unit). Parameters such as an existing security system, instruments and meters, equipment parameters, a power medium, a production process and a raw material ratio are integrated to enter a data platform, unmanned automatic operation is achieved, an intensive means is adopted, safety production is achieved, and the upgrading cost is low.

The invention relates to the technical field of data processing, and discloses an industry data processing method and a storage medium thereof, and the method comprises the following steps: 1, obtaining and transmitting multiple types of data; 2, diagnosing data, and confirming normal data, abnormal data and suspected data; and when the data is judged to be abnormal data, an alarm is given immediately, and when the data is judged to be doubt data, early warning is made or doubt is cancelled according to prediction strategy processing. The method can achieve the effects of comprehensively processing data, improving the fault detection perfection and accuracy, and predicting faults.

The invention provides an industrial big data collection method and system. The method comprises the steps: carrying out the multi-process concurrent collection of industrial data, carrying out the self-correlation analysis of the collected industrial data through all collection nodes, and transmitting the industrial data to a server; and creating a multi-thread industrial data processing task based on an NIO server, generating a multi-task message queue through Kafka, processing data in the multi-task message queue by using Spark Streami ng, and storing a processing result to an HDFS file system. By means of the method, the processing efficiency of industrial data acquisition, storage and other processes can be improved, the server load is reduced, and orderly and reliable management of industrial big data is facilitated.

The invention belongs to the technical field of industrial data processing, and discloses an industrial big data search optimization method, system, device, medium and terminal. The industrial big data search optimization method comprises the steps of firstly collecting industrial field specialized vocabularies to form a related set, and storing the content into a new document and placing the document in an ik word segmentation device configuration folder; and then configuring an industrial extension dictionary in the XML document to form an industrial word segmentation device, restarting an Elasticsearch search engine, and at the moment, completing the construction of the industrial word segmentation device. The invention provides a word segmentation device specially applied to industry, an industrial word segmentation device is constructed by analyzing the technical principle of the word segmentation device, and the difference between the word segmentation results of the industrial word segmentation device and mainstream general Chinese word segmentation devices jieba and Ansj in the industrial field is compared, and the result shows that based on the industrial word segmentation device, more excellent classification performance and robustness are achieved according to the word segmentation, and the word segmentation effect and the search efficiency are effectively improved by expanding industrial specialized vocabularies.

The invention discloses an industry data processing method and device, a storage medium and an electronic device. The method comprises the steps that industry field packets are generated by analyzing industry historical business data, the industry historical business data are covered with different business scene data, and each industry field packet is provided with corresponding industry data; storing the industry field package to a target server or a target client; the business scene data and the corresponding industry data are updated by updating the industry field packet, and the industry field packet is used for being reused in the business scene data. The technical problem that industry experience data cannot be reused or shared is solved.

The invention discloses an injection molding industrial data processing system and method based on big data, and belongs to the technical field of industrial data processing. The system comprises a data process monitoring module, a data terminal monitoring module and a server, wherein the data process monitoring module is used for detecting and processing injection molding machine process data, the data terminal monitoring module is used for monitoring and processing the injection molding machine data according to injection molding machine production products, the process data of an injection molding machine is detected through the data process monitoring module, the detection data, the working duration and the working environment of the injection molding machine are obtained in real time, integrated and marked as input data, a prediction model is obtained, the input data is input into the prediction model to obtain an output result and mark an output result as a prediction label, the prediction label is the state label corresponding to the input data, the data problem in the operation process of the injection molding machine can be known in time, warning is provided for a user, the problem can be found in time, and loss is reduced.