Control Valve Flow Sampling With Dynamic Filter Time Constant
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Solution Overview
Problem
Current control valves in HVAC systems face challenges in efficiently sampling and processing flow rate data in response to changes in valve stroke, leading to suboptimal fluid flow dynamics and inefficient use of communication and computation resources.
Innovation Solution
A control valve design that includes a sensor for sampling fluid flow parameters, a filter with an adjustable time constant, and a controller that transmits signals to adjust the throttle position and filter settings, allowing for rapid sampling and processing of flow data, optimized communication bandwidth usage, and efficient computation, while utilizing commercially available sensors and minimizing component failure risks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the sampling rate of flow data is increased to capture rapid changes during valve stroke, then the responsiveness and control precision are improved, but the communication bandwidth and computation resources are consumed more heavily
Solution Approach 1:
The filter time constant is dynamically adjusted based on valve stroke state. During valve stroke changes, the time constant is reduced to enable rapid sampling and capture flow dynamics. During stable operation, the time constant is increased to reduce sampling frequency and conserve communication and computation resources. This dynamic adaptation resolves the contradiction between measurement precision and resource consumption.
Solution Approach 2:
The system changes the filter time constant parameter according to operational conditions. By modifying this parameter, the system adapts its sampling behavior to match the current valve state, enabling high-precision measurement when needed while minimizing resource usage during normal operation.
2Speed
If a fixed small time constant is used in the filter to capture rapid flow changes, then the responsiveness to flow changes is improved, but the filtering effectiveness during stable operation is reduced
Solution Approach 1:
The filter time constant transitions from static to dynamic. The controller adjusts the time constant based on whether the valve is in stroke or stable operation mode. During stroke, a small time constant provides rapid response. During stable operation, a large time constant ensures signal stability and filtering effectiveness.
Solution Approach 2:
The system periodically evaluates valve stroke status and adjusts filter parameters accordingly. This periodic adaptation allows the system to switch between responsive sampling during transient states and stable filtering during normal operation, resolving the contradiction between speed and stability.
3Adaptability or versatility
If the filter time constant is continuously adjusted to optimize performance, then the adaptability to different operating conditions is improved, but the device complexity increases
Solution Approach 1:
The controller receives feedback about valve stroke status and uses this information to adjust the filter time constant. This feedback mechanism enables automatic adaptation to different operating conditions without requiring complex manual intervention or overly sophisticated control algorithms.
Solution Approach 2:
The system performs self-adjustment of filter parameters based on its own operational state. The controller autonomously determines when valve stroke is occurring and modifies the time constant accordingly, eliminating the need for external intervention or complex external control systems.
4Loss of information
If rapid sampling of flow values is performed during valve stroke, then the capture of flow dynamics is improved, but the computation load and communication bandwidth usage increase
Solution Approach 1:
The sampling rate is dynamically controlled based on valve stroke detection. During stroke events, the system increases sampling frequency to capture flow dynamics information. During stable operation, the sampling rate is reduced to improve computation and communication efficiency. This dynamic approach prevents information loss while maintaining system productivity.
Solution Approach 2:
The system applies excessive sampling only when necessary (during valve stroke) rather than continuously. This partial action approach ensures flow dynamics information is captured during critical transient periods while avoiding unnecessary computation and communication overhead during stable operation.
Data Source
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AI summary
A control valve (1) comprising an inlet port (2), an outlet port (3), a fluid (4) path, a throttle (6) situated in the fluid path (4), and an actuator (8) coupled to the throttle (6), the throttle (6) being selectively displaceable between a first position and a second position; a sensor (5) for recording parameters of a fluid flowing through the fluid path (4); a filter (10) for sampling signals indicative of the parameters from the sensor (5) at time intervals defined by a time constant of the filter (10); a controller (9) being configured to transmit a time constant signal to the filter (10), the time constant signal causing the filter (10) to increase its time constant and/or transmit a signal to the filter (10) causing the filter (10) to instantly sample a signal indicative of the one or more parameters.