Agitator Fault Detection via Pressure Signal Filtering
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Solution Overview
Problem
Current process control systems in stirred vessels struggle to promptly detect abnormal situations, such as agitator failures, leading to suboptimal performance and potential equipment damage, as existing techniques are inadequate for predicting and preventing these issues before they cause significant losses or downtime.
Innovation Solution
A system and method that utilize a pressure sensor to collect and filter data, isolating frequency components associated with agitator blade rotation, generating statistical data to detect abnormalities like broken, unbalanced, or missing blades, and generating indicators for abnormal situations, allowing for early intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional monitoring techniques are used, then the system is simple and easy to operate, but abnormal situations cannot be detected promptly
Solution Approach 1:
The patent replaces conventional mechanical monitoring systems with a signal processing-based detection system. A pressure sensor captures pressure signals from the stirred vessel, which are then processed through filtering and spectral analysis to detect agitator abnormalities. This substitution of mechanical monitoring with signal processing enables prompt detection of abnormal situations while maintaining operational simplicity.
Solution Approach 2:
The patent introduces pressure signals as an intermediary medium to detect agitator conditions. Instead of directly monitoring the agitator's mechanical state, the system uses pressure signals generated by the interaction between agitator blades and process material as an indirect indicator. This intermediary approach enables detection of abnormalities without complex direct mechanical sensors on the agitator itself.
2Loss of time
If advanced signal processing is implemented, then abnormal situations are detected promptly, but the device complexity increases
Solution Approach 1:
The patent applies preliminary filtering actions to the pressure signals before full spectral analysis. A bandpass filter is first applied to isolate the frequency range containing agitator blade passage signals, removing irrelevant high-frequency noise and low-frequency drift. This preliminary processing step reduces the complexity of subsequent analysis while enabling prompt detection by focusing computational resources on the relevant signal components.
Solution Approach 2:
The patent segments the pressure signal analysis into distinct frequency components through spectral analysis. By transforming the time-domain pressure signal into the frequency domain, the system separates the agitator blade passage frequencies from other process signals. This segmentation enables targeted detection of abnormal situations without requiring complex full-spectrum analysis, reducing overall processing complexity while maintaining fast detection capability.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables timely detection of agitator-related abnormalities, preventing suboptimal performance and equipment damage by providing early warnings and allowing for proactive maintenance, thus reducing downtime and operational costs.
Implementation Method 1
A pressure sensor disposed at least partially within a stirred vessel generates a pressure signal
Implementation Method 2
The pressure signal is filtered by a digital filter to isolate a frequency component corresponding to pressure changes caused by a blade of an agitator
Data Source
AI summary
A system and method for detecting abnormal situations associated with a stirred vessel in a process plant receives statistical data associated with a pressure within a stirred vessel. A pressure signal associated with the pressure in the vessel is filtered by a digital filter to isolate a frequency component corresponding to pressure changes caused by the movement of a blade of an agitator through a fluid. For example, a pressure sensor device disposed at least partially within the stirred vessel may generate the statistical data based on a pressure signal. The statistical data is analyzed to detect whether one or more abnormal situations associated with an agitator of the stirred vessel exist. For example, the statistical data may be analyzed to detect whether the agitator is broken/unbalanced, corroded, missing a blade or multiple blades, etc. If an abnormal situation is detected, an indicator of the abnormal situation may be generated.