Real-Time Equipment Diagnostics via Sensor Segmentation and 3D Visualization
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Solution Overview
Problem
Current systems for real-time diagnostics of equipment that generates vibration and static equipment face challenges such as high time consumption, discrepancies in diagnostic control, inability to display large quantities of equipment, difficulty in determining equipment state and position, and inefficiencies in data visualization, leading to delayed maintenance and operational inefficiencies.
Innovation Solution
A system comprising sensors that transmit data to peripheral intellectual measurement equipment for processing, which is then compared to threshold values to generate diagnostic information, presented through multiple executive dashboards for real-time monitoring, analysis, and reporting, enabling automatic real-time diagnostics and maintenance scheduling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional diagnostic systems are used to monitor equipment, then diagnostic accuracy can be maintained, but time consumption increases and real-time monitoring is not achieved
Solution Approach 1:
The system segments the monitoring task by deploying multiple independent sensors (vibration, temperature, pressure) that simultaneously collect different diagnostic parameters. Each sensor operates independently to capture specific equipment states, enabling parallel data acquisition that reduces overall diagnostic time while maintaining comprehensive accuracy through multi-parameter analysis
Solution Approach 2:
The system performs preliminary action by continuously collecting and pre-processing diagnostic data in real-time before failures occur. Sensors continuously monitor equipment parameters and the system maintains a ready state with processed diagnostic information, enabling immediate detection and response to equipment anomalies without waiting for scheduled inspections
2Quantity of substance
If multiple equipment units are monitored, then comprehensive diagnostics are achieved, but the system cannot display large quantities of equipment simultaneously
Solution Approach 1:
The system transitions from two-dimensional flat displays to three-dimensional virtual models of equipment. These 3D visualizations allow operators to navigate and inspect equipment states from multiple angles, enabling comprehensive monitoring of large quantities of equipment while maintaining clear visualization through spatial depth and hierarchical navigation capabilities
Solution Approach 2:
The system creates a universal virtual tag interface that can represent multiple equipment types and states through a single standardized interaction paradigm. This multi-functional interface allows operators to monitor diverse equipment units using consistent visual elements and control mechanisms, simplifying the operation of systems that track large quantities of different equipment
3Measurement precision
If detailed diagnostic information is provided for each equipment, then diagnostic precision is improved, but information overload occurs and equipment position determination becomes difficult
Solution Approach 1:
The system segments diagnostic information into hierarchical levels: equipment-level summaries, component-level details, and parameter-level data. This segmentation allows operators to access comprehensive diagnostic precision when needed while defaulting to organized, digestible summaries that prevent information overload and maintain clear equipment position awareness
Solution Approach 2:
The system introduces virtual tags as intermediary elements between the operator and detailed diagnostic data. These virtual tags serve as organized access points that aggregate multiple diagnostic parameters into structured, position-aware representations, enabling precise diagnostic information to be delivered in an organized manner that maintains spatial context and prevents information loss
4Productivity
If real-time data processing is implemented, then maintenance scheduling is improved, but system complexity increases
Solution Approach 1:
The system implements self-service by automatically processing sensor data, comparing readings against threshold values, and generating maintenance schedules without human intervention. The automated system performs data collection, analysis, and scheduling functions independently, improving maintenance efficiency while the standardized automated processes actually reduce overall system complexity compared to manual procedures
Data Source
AI summary
A system for automatic real-time diagnostics for equipment that generates vibration and static equipment with a plurality of sensors installed on or mounted proximate to the equipment that generates vibration and static equipment, at least one peripheral intellectual measurement equipment (PIM) for collecting sensor data and removing signal noise or averaging collected sensor data from a sensor over time, a plurality of diagnostic stations receiving assembled data from the PIM comparing to threshold values for diagnostic features and generating diagnostic information and calculating technical states generate diagnostic prescriptions for each diagnostic feature, and generating simultaneously a Monitor, Trend, Analysis, Report, System and Oscilloscope Executive Dashboards.