Valve Assembly On-Board Data Processing for Diagnostic Accuracy
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Solution Overview
Problem
Conventional data collection techniques for valve diagnostics in industrial process lines face challenges due to the large number of valve assemblies and bandwidth limitations, making it difficult to capture and analyze data effectively for predictive maintenance and problem identification.
Innovation Solution
Implementing an on-board data processing system within the valve assembly that includes a sampling device with buffers to continuously collect and analyze data, determining a quality measure for the most useful data sets to predict performance indicators such as friction and stick slip, and prioritizing the transmission of pertinent data for diagnostic analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data is continuously collected from valve assemblies using conventional techniques, then diagnostic accuracy is improved, but network bandwidth consumption increases and data transmission efficiency deteriorates
Solution Approach 1:
The patent performs preliminary data processing and quality assessment at the valve assembly level before transmission. The sampling device continuously collects data and evaluates its quality locally, pre-filtering and pre-processing data to identify only those samples that meet diagnostic quality criteria. This preliminary action at the source prevents unnecessary bandwidth consumption during subsequent transmission to the control system.
Solution Approach 2:
The patent extracts and transmits only the most valuable data samples that meet quality criteria, rather than transmitting all collected data. The sampling device identifies and extracts high-quality diagnostic samples based on quality measures, separating useful data from redundant information. This extraction approach maintains diagnostic accuracy while significantly reducing network bandwidth requirements.
2Reliability
If data sampling rate is increased to capture valve movement, then diagnostic capability is improved, but system complexity and data processing burden increase
Solution Approach 1:
The sampling device performs preliminary quality evaluation of data samples at the valve assembly level before transmission. By continuously assessing data quality and identifying useful samples in advance, the system avoids the need for complex centralized processing of all raw data. This preliminary action at the source reduces the data processing burden on the control system while maintaining reliable diagnostic capability.
Solution Approach 2:
The valve assembly's sampling device autonomously evaluates its own data quality and determines which samples are useful for diagnostics. This self-service approach at the data source eliminates the need for complex centralized quality assessment and reduces the overall system complexity. The sampling device independently performs quality measures and identifies useful data without requiring complex external processing infrastructure.
3Loss of information
If all valve assembly data is transmitted to the control system, then complete analysis is achieved, but network bandwidth is exceeded and transmission efficiency decreases
Solution Approach 1:
The sampling device extracts and transmits only the most valuable data samples that meet quality criteria, rather than transmitting all collected data. By identifying and extracting high-quality diagnostic samples based on quality measures, the system maintains data completeness for effective diagnostics while significantly reducing network bandwidth consumption. This selective extraction approach ensures that the most informative data is transmitted without overwhelming the network infrastructure.
Solution Approach 2:
The system performs preliminary data evaluation and selection at the valve assembly level before transmission to the control system. The sampling device continuously assesses data quality and pre-identifies useful samples, preparing only the necessary data for transmission. This preliminary action ensures that complete and accurate diagnostic information is available at the control system while minimizing network bandwidth usage during data transfer.
Data Source
AI summary
Embodiments of systems and methods that can facilitate data collection for valve diagnostics. The systems can include a valve assembly with a valve and a sampling device that is configured to access a repository with a first buffer and a second buffer. During operation, the valve assembly is configured to read data representing operating variables for the valve into the first buffer. The valve assembly is also configure to determine a quality measure for a first sample set of data from the first buffer, the quality measure indicating the usefulness of the first sample set of data for predicting performance of the valve relative to a second sample set of data from the second buffer. In one embodiment, the valve assembly is further configured to read data from the first buffer into the second buffer in response to the quality measure indicating that the first sample set of data is relatively more useful than the second sample set of data.