Rotary System Characteristic Mapping With Predictive Setpoints
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Solution Overview
Problem
Conventional methods for mapping operational characteristics of rotary systems, such as electric motors, are resource- and time-consuming, leading to high costs and bottlenecks in system development and use.
Innovation Solution
A method utilizing seed data, setpoints, and a prediction model to generate mapping data points, reducing the need for extensive measurements while maintaining data quality, by using seed data from similar systems or software models to predict optimal measurement points.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional measurement methods are used to map operational characteristics of rotary systems, then measurement precision is improved, but loss of time and resource consumption increase
Solution Approach 1:
The method performs preliminary actions by obtaining seed data from software models or similar systems before actual measurements. This preliminary data is used to generate an initial map and identify informative setpoints, reducing the need for extensive conventional measurements and thereby reducing time loss while maintaining data quality.
Solution Approach 2:
The method creates a copy of the operational characteristic map using seed data from software models or similar rotary systems. This copied map serves as a foundation that guides actual measurements, reducing the number of measurements needed while preserving measurement precision through targeted data collection at informative setpoints.
2Measurement precision
If conventional measurement methods are used to map operational characteristics of rotary systems, then measurement precision is improved, but resource consumption increases
Solution Approach 1:
The method performs preliminary actions by obtaining seed data from software models or similar systems before actual measurements. This preliminary data is used to generate an initial map and identify informative setpoints, reducing the need for extensive conventional measurements and thereby reducing resource consumption while maintaining data quality.
Solution Approach 2:
The method creates a copy of the operational characteristic map using seed data from software models or similar rotary systems. This copied map serves as a foundation that guides actual measurements, reducing the number of measurements needed and associated resource consumption while preserving measurement precision through targeted data collection.
3Measurement precision
If extensive measurements are performed to ensure data quality, then measurement precision is improved, but productivity decreases
Solution Approach 1:
The method performs preliminary actions by obtaining seed data and generating an initial map before actual measurements. This preliminary work identifies informative setpoints that guide measurements, reducing the total number of measurements needed and thereby improving productivity without sacrificing data quality.
Solution Approach 2:
The method creates a preliminary map copy using seed data that guides the measurement process. This approach reduces the number of measurements required compared to conventional methods, improving system development efficiency while maintaining measurement precision through targeted data collection at informative setpoints.
Data Source
AI summary
The invention relates to systems and methods for mapping an operational characteristic of a first rotary system as a function of one or more operation parameters. The method comprising: obtaining seed data; obtaining a plurality of setpoints; obtaining a plurality of mapping data points; and generating interpolation data utilizing the plurality of mapping data points, wherein the seed data constitutes an initial dataset for the operational characteristic as a function of the one or more operation parameters for the first rotary system, and wherein the plurality of setpoints being obtained utilizing a prediction model, the seed data, and an a priori error setting, and wherein each mapping data point comprises an acquisition data component acquired utilizing one or more measurements of the first rotary system in response to control of the one or more operation parameters of the first rotary system in accordance with a respective setpoint.