Supports a variety of industrial protocols and data interfaces, seamlessly integrating with existing IT/OT systems. It is compatible with multi-source heterogeneous data, enabling smooth integration of time-series data, as well as sensor data from sources such as vibration, temperature, pressure, current, and oil fluid measurements.

Visualized Panoramic Monitoring

A one-stop overview of the real-time health status of all devices, enabling quick identification of abnormal equipment. From the factory and production lines down to individual devices, drill down layer by layer while visually presenting historical data, real-time trends, spectrum analysis charts, and more. Integrated with the digital twin model, this solution delivers precise, 3D visualized localization of fault locations.

A flexible and configurable early warning system

Supports multi-level alarm threshold customization (Normal, Medium, Severe). Offers multiple alert methods (in-station messages, email, SMS, WeChat, phone calls, audio-visual alerts) to ensure critical information is promptly delivered to the responsible parties.

Powerful integration and scalability

Provides a rich set of RESTful APIs, enabling seamless integration with third-party systems such as ERP, MES, CMMS, and EAM, and automatically triggering maintenance work orders. Each functional module is decoupled, allowing for flexible combination and scalable expansion based on customer needs, while supporting public cloud, private cloud, and hybrid deployment options.

Comprehensive Value Decision Support

Deep integration has ushered in an unprecedented level of decision-making sophistication. Managers can now not only answer questions like "When will the equipment fail?" but also address more strategic, lifecycle-oriented inquiries: "Which equipment brands and models are most reliable? (Optimizing procurement)," "What’s the return on investment for our current maintenance strategies? (Optimizing strategies)," and "When is the most cost-effective time to upgrade or replace equipment? (Optimizing upgrades)." This shift enables a transformative leap—from managing individual equipment health to maximizing the overall return on investment (ROI) of your entire asset portfolio. Through this deep integration, we’re redefining equipment management: it’s no longer just a cost center, but rather a pivotal driver of value creation. Our platform ensures that every piece of equipment remains in peak condition throughout its entire lifecycle—delivering optimal performance at the lowest total cost of ownership (TCO), while unlocking maximum productivity potential.

Algorithm Engine

The algorithm engine is the platform's "intelligent brain," transforming cutting-edge algorithms into simple, user-friendly system functionalities. This allows you to effortlessly harness expert-level equipment prediction and health management capabilities—without needing to delve into complex models yourself. At the core of its predictive diagnostics, graph analysis, and intelligent decision-making are powerful, integrated smart algorithms that deliver seamless, end-to-end solutions. Moreover, this engine serves as a highly modular, fully functional, and standardized algorithmic service center, providing "ready-to-use" professional analytical capabilities for advanced applications above it.

Signal Preprocessing and Feature Extraction Center

It provides a rich library of standardized functions that automatically perform pre-processing tasks such as data cleaning, noise reduction, filtering, and normalization on multi-source, heterogeneous raw data (e.g., vibration, current, temperature, acoustics, etc.). Built-in algorithms enable the automatic extraction of dozens of time-domain, frequency-domain, and time-frequency-domain features—including metrics like amplitude, mean, variance, kurtosis, FFT spectra, and wavelet packet energy—providing high-quality, standardized input feature vectors for subsequent diagnostic models.

Diagnostic Model and Atlas Generator

The core computing unit of the engine integrates all advanced diagnostic algorithms. This module provides all diagnostic functions, including fault identification, health assessment, trend prediction, and Remaining Useful Life (RUL) calculation, among others.

Data Management and Model Training Center

Provides a visualized model training and hyperparameter tuning system, supporting data annotation, feature selection, model training, validation, and one-click deployment. Through the closed-loop process of "Data-Diagnosis-Decision-Feedback," it automatically collects operations and maintenance feedback data, continuously optimizing model performance to enable self-learning and self-evolution of algorithms.

Real-time Scheduling and Business Orchestrator

As the "nervous system" of the engine, it handles the dynamic hot-plug loading and collaborative scheduling of all algorithmic modules. Based on a pre-defined, complex business topology, it invokes the corresponding preprocessing, feature-extraction, or diagnostic models with millisecond-level response speeds.