Compressor Data Logging via Segmented Storage
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
High-pressure compressor systems often lack real-time monitoring and historical data analysis capabilities, making them vulnerable to poor performance, unexpected maintenance issues, and potential catastrophic failures due to the absence of skilled personnel and past performance data on site.
Innovation Solution
A system and method for remotely controlling multiple operational facets of a compressor system, including real-time monitoring, data logging, and report generation, utilizing a two-server/memory approach for efficient data collection and storage, enabling remote access and predictive analytics through a wireless communication network.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real-time monitoring and historical data collection systems are implemented at remote compressor sites, then operational reliability and predictive maintenance capabilities are improved, but device complexity and data storage requirements increase
Solution Approach 1:
The system divides data storage into two separate data stores: a first data store for real-time data collection with wraparound storage, and a second data store for historical data archiving. This segmentation allows each store to be optimized for its specific function, reducing the complexity burden on any single component while maintaining overall system reliability.
Solution Approach 2:
The first data store acts as an intermediary between the compressor system and the second data store. It collects real-time data locally using wraparound storage and periodically transfers portions of this data to the second data store, mediating between real-time monitoring needs and historical archiving requirements.
2Loss of information
If comprehensive historical data is collected and stored on-site, then predictive maintenance accuracy is improved, but data storage space and system resources are consumed
Solution Approach 1:
The system extracts only portions of the real-time data from the first data store to transfer to the second data store, rather than duplicating all data. This selective extraction maintains predictive maintenance capabilities while reducing overall storage space requirements.
Solution Approach 2:
The first data store performs preliminary data collection and processing using wraparound storage, preparing data for future analysis without requiring all historical data to be stored simultaneously. This preliminary action enables predictive maintenance while managing storage constraints.
3Productivity
If skilled data analysis personnel are deployed on-site, then operational performance optimization is improved, but operational costs and human resource requirements increase
Solution Approach 1:
The system enables self-service through automated data collection, storage, and transfer mechanisms. The wraparound storage scheme and automatic data transfer between data stores eliminate the need for continuous human intervention in data management, allowing operational optimization without requiring skilled personnel on-site.
Solution Approach 2:
The patent replaces the mechanical system of human data analysis personnel with an automated electronic data management system. The computer-implemented methods and automated data transfer mechanisms substitute for human expertise in data collection and initial processing, reducing human resource requirements while maintaining operational performance.
4Measurement precision
If real-time data is continuously stored at high resolution, then monitoring precision is improved, but data storage capacity and energy consumption increase
Solution Approach 1:
The system implements periodic data transfer from the first data store to the second data store, rather than continuous high-resolution storage. The wraparound storage scheme maintains real-time monitoring precision locally while periodic archiving reduces overall energy consumption associated with continuous high-capacity storage operations.
Data Source
AI summary
A method is provided for monitoring and logging data related to a compressed gas operation. A communication interface is coupled to a device supporting a compressed gas operation. Data related to the compressed gas operation is automatically collected via the communication interface at a first data store every first time increment of a first time period. Portions of the data from the first data store are automatically collected at a second data store every second time increment of each first time period. The second time increment is greater than the first time increment, and the portions of the data are collected for a second time period which is greater than the first time period.