Pump Delivery Rate Determination via Probability Density Fusion
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Solution Overview
Problem
Existing methods for determining pump delivery flow, such as H(Q) and P(Q) characteristics, are prone to errors due to flat profiles and non-uniqueness, especially when dealing with pumps having characteristics that initially increase and then decrease, leading to large deviations in delivery flow measurements.
Innovation Solution
The method involves calculating probability density functions for delivery head and power, fusing data from these functions to minimize errors, and using sensors to determine pressure differences and motor actuation frequency, with an electronic evaluation unit processing the data to provide accurate and stable delivery flow values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If indirect methods using H(Q) or P(Q) characteristics are used to determine delivery flow, then measurement cost is reduced, but measurement precision deteriorates due to flat profiles and non-uniqueness
Solution Approach 1:
The invention combines both H(Q) and P(Q) characteristics into a unified evaluation system. By merging the information from both characteristics and their respective probability density functions, the system achieves more reliable delivery flow determination than either characteristic alone, especially for pumps with flat characteristics.
Solution Approach 2:
The invention transforms the deterministic characteristic curves into probability density functions, changing the parameter representation from fixed values to probabilistic distributions. This allows for a more robust evaluation that accounts for uncertainties and flat profiles in the original characteristics.
2Device complexity
If H(Q) characteristics with flat profiles are used, then device complexity is reduced, but reliability deteriorates due to large errors in delivery flow determination
Solution Approach 1:
The system uses feedback from both H(Q) and P(Q) characteristics to continuously refine the delivery flow determination. By evaluating both characteristics and their probability density functions, the system provides mutual validation and correction, improving reliability without significantly increasing complexity.
Solution Approach 2:
The invention creates a composite evaluation system that combines H(Q) and P(Q) characteristics, similar to how composite materials combine different materials to achieve superior properties. The combined system leverages the strengths of both characteristics while compensating for their individual weaknesses.
3Measurement precision
If direct measurement using magnetic inductive flow meters is used, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The invention introduces probability density functions as intermediaries between the measured parameters (delivery head and power) and the delivery flow determination. These probability density functions serve as mediators that transform the characteristic curves into a form that can be reliably evaluated, achieving precision comparable to direct measurement without the associated complexity.
Data Source
AI summary
The invention relates to a method for determining the delivery rate of a pump. In this context, a value of the delivery level and a value of the power of the pump are determined. A probability density function is calculated for the delivery level and the power. A first probability density function of the delivery rate is calculated on the basis of a delivery level-delivery rate relationship and the probability density function of the delivery level. A second probability density function of the delivery rate is determined on the basis of a power-delivery rate relationship and the probability density function of the power. A combined probability density function of the delivery rate is determined on the basis of the first and second probability density functions. The delivery rate is determined on the basis of the combined probability density function.