Method for data analysis in coal mine industry

Abstract

The invention provides a method for analyzing data in the coal mine industry, belongs to the technical field of data processing, and aims to innovatively integrate all-around and multi-type data sources in the coal mine industry, cover traditional coal mine business entity data, and introduce Internet to collect data, deeply mine and associate data values of the data sources. Therefore, leading-edge functions of construction query, multi-dimensional association configuration of data, data analysis presentation, data collection, data sharing and the like of a data source in the coal mine field are achieved, the whole process from collection, real-time monitoring to dynamic analysis of the data in the coal mine field is completed in a one-stop mode, and a data working party is enabled with unique convenience; and service is provided for a data lookup party by using distinctive intuition.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and particularly to a method for data analysis in the coal mining industry. Background Art

[0002] Data analysis, as a key process for mining data value, uses multivariate statistical methods and advanced data mining techniques to explore deep patterns, trends, and relationships in data. Currently, the coal industry is booming and the digital transformation is accelerating, presenting both opportunities and challenges for coal mining enterprises. On the one hand, the coal mining operation process is complex, and a large amount of structured, semi-structured, and unstructured data is generated in each link. The disadvantages of traditional manual and decentralized storage models are obvious, with data being easily lost, incorrect, and the analysis being severely lagged. On the other hand, the requirements for real-time and accurate data in safety production are extremely high, and existing management means are difficult to meet. Moreover, as the demand for data analysis advances, the lack of a unified data center leads to scattered data and blocked data circulation, making it difficult for management to make decisions and adapt to market changes. In summary, building a dedicated data center for the coal mining industry to achieve intelligent integration of multi-source data, optimized presentation, and in-depth analysis has become an urgent matter for the informatization of governments and enterprises. The present invention emerges as the times require and overcomes problems by leveraging cutting-edge data management on the Internet and flexible resource allocation. Summary of the Invention

[0003] To solve the above technical problems, the present invention provides a method for data analysis in the coal mining industry, aiming to build a high-performance data center by leveraging the advantages of Internet data management and innovative flexible resource allocation strategies. It comprehensively improves the data storage capacity and processing speed, strengthens the data security defense line, innovates the analysis efficiency and accuracy, and perfectly meets the stringent data analysis requirements of the coal mining industry.

[0004] The technical solution of the present invention is as follows:

[0005] A method for data analysis in the coal mining industry, which innovatively integrates data from multiple data sources in depth and precisely collects data in the coal mining industry, selects suitable data analysis technologies and diverse visualization innovation tools, establishes a close connection between the data center in the coal mining industry and the data analysis and presentation in the coal mining field, and innovatively forms a process for constructing a high-performance data center based on multi-dimensional correlation configuration of data.

[0006] Use intelligent fusion technology to compatibly integrate various types of data sources, continuously iterate and optimize the data collection mechanism to ensure comprehensive and accurate data, and lay a solid foundation for the stable construction of the data center in the coal mining industry.

[0007] Initiate a multi-dimensional correlation model for coal mine data, use deep learning algorithms to deeply correlate the data in different data sources, and thus break through to achieve an ultra-fast construction query function for data sources, enabling users to quickly retrieve the required key data to construct information from a vast amount of data in the coal mining field.

[0008] Design a professional visualization report template exclusively for coal mines. According to the personalized needs of users and the characteristics of complex data, intelligently select and adapt chart types and optimal layout methods to complete the full life cycle management of data in the coal mine field, covering collection, real-time monitoring and dynamic analysis. Innovatively fill the data analysis results into the visualization report template without feeling, and generate intuitive and clear reports with one click. At the same time, the report has many interactive functions, supports data filtering, sorting, drilling, exporting, collection, etc., and introduces intelligent insight recommendations to provide unique data presentation services for data workers and reviewers, helping the coal mining industry to produce and make decisions accurately.

[0009] We have pioneered the introduction of an intelligent permission management ecosystem, and through the comprehensive introduction of cutting-edge security measures such as access control, multi-layer identity authentication, and dynamic role management, we have comprehensively protected the security and confidentiality of industrial data and built an iron wall of data security.

[0010] Create a secure data sharing mechanism based on encrypted lists and centralized records, allowing users to share data with other users or teams under a trust framework. Perform ultra-fine permission management and intelligent expiration time control on data sharing to double guarantee data security and confidentiality. With the help of this mechanism, it strongly promotes the high-speed circulation and sharing of data in multiple industries such as coal mines, and builds a convenient communication bridge for data workers and reviewers.

[0011] The beneficial effects of the present invention are

[0012] The present invention is based on the deep integration of multiple data sources, closely combines the data collection characteristics of the coal mining industry, and builds a unique user data analysis data center architecture with the help of cutting-edge technology for big data processing. On the one hand, it is endowed with super capabilities of centralized storage, ultra-high-speed processing and precise analysis, deeply analyzes the real-time status of equipment and underground environmental monitoring data, and accurately warns in advance, pushing the level of safe production to a new height, optimizing each link of production operations, and greatly improving efficiency. On the other hand, it presents all-round and intelligent data management services to information users, and realizes multi-source data integration and deep mining in a flash. Furthermore, with scientific and sophisticated data authority configuration, the data is guaranteed to be as solid as a rock. At the same time, the data analysis results are clear at a glance with highly creative visualization. Internally, it breaks down departmental data barriers and employees collaborate and upgrade tacitly; externally, it shares desensitized data with scientific research institutions, upstream and downstream, introduces cutting-edge technologies, expands market channels, and strongly promotes the intelligent and efficient advancement of coal mining enterprises, helping enterprises stand out in the complex and changing market and steadily move towards sustainable development. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 It is a schematic diagram of the workflow of the present invention. DETAILED DESCRIPTION

[0014] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0015] The present invention provides a method for data analysis in the coal mining industry, integrating all-round and multi-type data sources in the coal mining industry. While covering traditional coal mine business entity data, it introduces Internet-collected data and deeply mines and correlates the data value of the two. Thereby, it realizes cutting-edge functions such as the construction and query of data sources in the coal mine field, multi-dimensional correlation configuration of data, data analysis and presentation, data collection, and data sharing, and completes the entire process of data collection, real-time monitoring, and dynamic analysis in the coal mine field in one stop, empowering data workers with unique convenience and serving data viewers with special intuitiveness.

[0016] Specifically, it includes:

[0017] 1. Data center construction: Pioneeringly configure and integrate various data sources in the coal mining industry, mobilize each business department to cooperate to complete Internet data collection, and use intelligent adaptation technology to achieve precise monitoring of data sources, seconds-level query of complex table structures and massive data inside the database, and achieve all-round and intelligent monitoring and scheduling of hardware and data resources, laying a solid foundation for the efficient operation of the data center.

[0018] 2. Data resource configuration: Initiate a dual-mode data cleaning and denoising system of regular automatic and manual modes, combine intelligent algorithms with professional manual verification to ensure data purity. Classify data finely according to data types, introduce an intelligent label system, and classify and organize coal mine collected data with one key, which is convenient for subsequent lightning query and in-depth analysis. Develop an adaptive data adaptation module, which automatically converts and matches different data source formats and protocols and seamlessly accesses the data center, breaking the data format barrier.

[0019] 3. Data permission configuration: After creating a large amount of data resources, innovatively introduce a dynamic permission grading system. In addition to the conventional unrestricted, specified department, specified role, and specified user, according to the real-time working conditions of coal mine production and the urgency of tasks, temporarily authorize specific data access permissions, and cooperate with confidentiality level identification and multi-factor authentication to strictly control data access and ensure data security. Combine with access log records, analyze each data access behavior record, and immediately warn of abnormal behaviors to escort data security.

[0020] 4. Data analysis and presentation: Select cutting-edge data analysis tools and customized technologies that are suitable for the coal mining industry. For example, accurate statistics and scientific predictions are made on the occurrence of disasters such as gas to lay a solid foundation for decision-making in coal mine safety production. In addition, in-depth analysis is conducted on safety hazards to explore hidden features hidden in accident data, and combined with real-time information on underground personnel and vehicles, an intelligent monitoring mechanism is initiated to ensure all-round safety in coal mine production. A visual interactive interface is designed to present the analysis results to users in the most intuitive and easy-to-understand way. The report not only supports conventional screening, sorting, and drilling, but also relies on innovative design and integration of visualization tools to deeply explore the value of data for users, analyze data from multiple perspectives, and provide all-round, multi-level solid support for decision-making.

[0021] 5. Data resource sharing: Innovatively adopt a shared data resource model based on encrypted lists and centralized records, and use encrypted hashes and distributed ledgers to ensure that data flows are traceable and cannot be tampered with. Through multiple methods such as sharing codes, specifying users, and accurately setting expiration times, clarify the boundaries of data sharing, promote the establishment of a trusted data sharing mechanism between the coal mining industry, scientific research institutions, and upstream and downstream enterprises, and share desensitized high-value statistical data with the outside world. Create a cross-enterprise data collaboration platform to support real-time online collaborative analysis of shared data by multiple parties, seamless cross-regional and cross-organizational interaction between users of different systems, promote high-speed information circulation and collaborative innovation, and enhance the overall competitiveness of the industry.

[0022] The above description is only a preferred embodiment of the present invention, which is only used to illustrate the technical solution of the present invention, and is not used to limit the protection scope of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention are included in the protection scope of the present invention.

Claims

1. A method for coal mining industry data analysis, characterized in that: Based on the deep integration and data collection of multiple data sources, suitable data analysis technology and multi-dimensional visualization innovation tools are selected to link the data center with data analysis in the coal mining field, and a high-efficiency data center construction process is formed by relying on the innovative multi-dimensional correlation configuration of data.

2. The method according to claim 1, characterized in that Use intelligent adaptation technology to monitor data sources, query database internal table structures and massive data, and achieve all-round and intelligent monitoring and scheduling of hardware and data resources; A multi-dimensional data association model is designed, and the data in different data sources are associated using deep learning algorithms, thereby realizing the rapid construction query function of the data source, enabling users to quickly retrieve the required key data construction information from massive coal mining data.

3. The method according to claim 2, characterized in that A regular automatic and manual dual-mode data cleaning and denoising system combines intelligent algorithms with manual verification to ensure data purity; fine classification based on data type, introduction of an intelligent labeling system to classify and organize collected data with one click; automatic conversion and matching for different data source formats and protocols, and seamless access to the data center.

4. The method according to claim 3, characterized in that Design visual report templates, intelligently filter and adapt chart types and optimal layout methods according to user personalized needs and data characteristics, complete data life cycle management, covering collection, real-time monitoring and dynamic analysis; fill data analysis results into visual report templates seamlessly, generate reports with one click, and the reports have many interactive functions, support data filtering, sorting, drilling, exporting, and collection, introduce intelligent insight recommendations, and provide data presentation services for data workers and reviewers.

5. The method according to claim 1, characterized in that Introduce an intelligent permission management ecosystem, and protect the security and confidentiality of industrial data in all aspects by introducing cutting-edge security measures such as access control, multi-layer identity authentication, and dynamic role management.

6. The method according to claim 5, characterized in that After the massive data resources are created, a dynamic permission classification system is innovatively introduced. In addition to the conventional unlimited, designated departments, designated roles, and designated users, specific data access rights are temporarily authorized based on the real-time production conditions and task urgency. With the help of confidentiality identification and multi-factor authentication, data access is strictly controlled to ensure data security. Cooperate with access log records to record and analyze every data access behavior, and issue an immediate warning for abnormal behavior.

7. The method according to claim 1, characterized in that A secure data sharing mechanism based on encrypted lists and centralized records is set up to allow users to share data with other users or teams under a trust framework; permission management and intelligent expiration time control are performed on data sharing to double-protect data security and confidentiality.

8. The method according to claim 1, characterized in that We use cutting-edge data analysis tools and customized technologies to conduct in-depth analysis, unearth hidden features in accident data, and combine it with real-time information on underground personnel and vehicles to activate intelligent monitoring mechanisms to ensure production safety.

9. The method according to claim 1, wherein a sharing-type data resource mode based on an encryption list and centralized recording is adopted, and an encryption hash and a distributed ledger are used to ensure that the data flow is traceable and tamper-proof; through sharing codes, designated users, and precisely set expiration times, the data sharing boundaries are clarified, a trusted data sharing mechanism is established, and high-value statistical data after desensitization is shared externally.

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