Xiangming Intelligent Control
Fully Mechanized Coal Mining Data Analytics System
Contact UsBusiness Background
Taiyuan Xiangming Intelligent Control is a leading provider of intelligent solutions for fully mechanized coal mining industry. It focuses on the R&D and promotion of intelligent and unmanned technologies for fully mechanized coal mining scenarios, and has served large energy and mining groups including China Energy, China Coal Energy, and China Huaneng Group.As a core platform, the Fully Mechanized Coal Mining Ground Control Center integrates equipment monitoring and remote control system, enabling remote monitoring of personnel, equipment status, environment and production, as well as one‑key start/stop and remote intervention for mining equipment. As a key component of the ground control center, the Fully Mechanized Coal Mining Data Analytics System performs intelligent analysis of data including equipment operating rate, automation rate, advancing distance, coal output, and roof pressure. It automatically generates graphs, charts and reports, providing critical data support for intelligent coal mining.
However, the number of connected devices continues to rise, imposing stricter requirements on real-time performance, as well as depth and scope of data analytics. The original InfluxDB faced a lot of chanllenges in data processing and further data applications.
Business Challenges
Due to the harsh underground working environment, complex geological structure, and numerous mining processes, the traditional data base cannot support the business needs of intelligent fully mechanized mining
Difficulty in Massive Time-Series Data Storage
Thousands of sensors in the fully mechanized mining system generate massive volumes of time-series data daily. The original database InfluxDB cannot efficiently and reliably store such growing high-volume time-series data.
Complexity in Multi-model Data Management
Apart from massive time-series data, the system manages large amount of relational data, including metadata and business data. The original solution was to manage different data with both MySQL and InfluxDB, resulting in complex data architecture and operation processes.
Strong Demand for Ad Hoc Data Queries
Business requires 24-hour historical query capability for single data metrics to obtain a full overview of equipment status and daily production.
High Requirements for Batch Data Computing
Multi-dimensional statistical reports and diverse topic data analysis are required for business use. Batch processing over time-series data is critical.
KaiwuDB Solution
Adaptive time-series engine enables end-to-end optimization of data ingestion, pre-computation, compression, storage, and query analytics.
Intelligent data pre-aggregation - real-time aggregation of massive sensor-generated time-series data to reduce storage pressure. Dynamic compression optimization - automatic selection of the optimal compression algorithm based on data characteristics, achieving a compression ratio of over 30x. Efficient query acceleration - millisecond-level query response enabled by adaptive indexing technology. Real-time data processing - supports stream processing to meet the real-time demands of underground equipment monitoring.Multi-model database architecture addresses the challenges of multi-modal data management, including equipment operating rate, automation rate, advancing distance, and coal output, supporting sophisticated data analysis scenarios.
Unified data storage - supports diverse data models including time-series, relational, and document data in a single database. Cross-model query - enables joint analysis of time-series and relational data, such as correlated queries between equipment runtime data and basic device information. Data consistency - ensures consistency across multi-model data via distributed transaction mechanisms. Standardized interface - provides a unified SQL interface to simplify application development.With edge-to-cloud architecture, KaiwuDB adapts to both aboveground and underground coal mining scenarios, ensuring real-time data processing underground while enabling centralized data analysis on the ground data center.
Edge computing capability - deployable on resource-constrained industrial PCs at the edge, with CPU usage below 50% and memory usage stably under 50%. Tiered data processing - end devices store newly collected data while edge nodes aggregate data from multiple terminals, and the cloud completes final data integration. Intelligent data synchronization - enables efficient data synchronization between edge and central layers based on data pub/sub. Flexible scalable architecture - supports elastic scaling from a 4C8G configuration to large-scale clustersBuilt-in AI autonomy enables self-management and self-optimization of the database, provides early warning of equipment failures, and significantly improves system stability.
Intelligent tuning - automatically adjusts database parameters according to workloads to optimize performance. Fault prediction - predicts potential failures based on historical data to enable predictive maintenance. Self-healing capability - automatically detects and resolves database anomalies to enhance system reliability. Resource optimization - intelligently allocates computing and storage resources to improve utilization efficiency.
Client Benefits
Performance Significantly Improved
Data query latency reduced from seconds to milliseconds, while the overall query performance improved by 68%, meeting real‑time analysis demands. Furthermore, powered by KaiwuDB, the platform can write one million row data records per second.
Operational Costs Greatly Reduced
Data storage costs decreased by 32% through high‑ratio compression. By supporting multi-model data processing and management within a single database, the system architecture is greatly simplified. The solution enables flexible, lightweight deployment starting at 4C8G, cutting hardware costs by up to 80%. As a result, overall database operations costs are reduced by 54%.
Reliable and Intelligent Database Operations
With database compatibility exceeding 98%, KaiwuDB enables fully smooth and non‑disruptive data migration. It maintains 100% reliability and stability under mixed read‑write load conditions. The graphical management tool improves efficiency in data administration and system maintenance. Utilizing stream computing, the platform supports real‑time data processing, complex SQL queries, and intelligent assisted decision‑making.