Distributed Fill-Level Detection with Selective Echo-Point Transmission
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Solution Overview
Problem
Existing fill level determination systems face challenges in energy efficiency and the need for parameterization, especially when using sensors with limited bandwidth and in potentially explosive environments, and they often require extensive data transmission.
Innovation Solution
A method for distributed fill level determination using a sensor that identifies and transmits only characteristic parameters of significant reflection points, reducing data transmission and eliminating the need for parameterization, while utilizing a cloud for decision-making and historical data processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all measurement data is transmitted from sensor to cloud, then complete information is available for analysis, but energy consumption and data transmission bandwidth increase significantly
Solution Approach 1:
The patent extracts only the essential characteristic parameters (time values, amplitude values, positions of reflection points) from the complete measurement data before transmission to the cloud. This selective extraction maintains the information necessary for fill level determination while significantly reducing the data volume transmitted, thereby lowering energy consumption and bandwidth requirements.
Solution Approach 2:
The measurement data is segmented into distinct characteristic parameters that are individually evaluated for their relevance to fill level determination. Only those parameters representing significant reflection points are transmitted to the cloud, separating essential information from redundant data to optimize energy efficiency.
2Measurement precision
If sensor performs full data processing locally, then accurate fill level determination is achieved, but device complexity and computational requirements increase
Solution Approach 1:
The processing tasks are segmented and distributed between the sensor and the cloud. The sensor performs initial processing to extract characteristic parameters of significant reflection points, while the cloud performs the final fill level determination. This distribution reduces the computational burden and complexity of the local sensor device.
Solution Approach 2:
The patent introduces an intermediary processing step where characteristic parameters are extracted and transmitted to the cloud for final analysis. This intermediary approach allows the sensor to remain relatively simple while still enabling accurate fill level determination through cloud-based processing.
3Adaptability or versatility
If parameterization is performed on-site, then sensor is optimized for specific application, but installation time and complexity increase
Solution Approach 1:
The sensor is pre-configured with the capability to identify and extract characteristic parameters of significant reflection points without requiring application-specific parameterization. This preliminary configuration allows the sensor to be universally deployed across different applications while maintaining adaptability through cloud-based analysis of the extracted parameters.
4Loss of information
If bandwidth is increased for data transmission, then more complete data can be transmitted, but cost and energy consumption increase
Solution Approach 1:
The patent extracts only the essential characteristic parameters needed for fill level determination and transmits only these extracted parameters to the cloud. This selective transmission maintains data completeness for the intended purpose while significantly reducing the bandwidth and energy required for transmission compared to sending complete measurement data.
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
This approach reduces energy consumption, simplifies installation, enhances robustness, and allows for accurate fill level determination without on-site parameterization, leveraging cloud resources for decision-making and data refinement.
Implementation Method 1
receiving an echo signal reflected from a surface of the fill material through the sensor
Implementation Method 2
echo signal reflected from a surface of the fill material
Data Source
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AI summary
The invention concerns in particular a method for distributed determination of a fill level or limit level. A sensor (100) determines characteristic parameters of significant reflection points (312, 404, 406, 602) on an echo curve (300, 400, 500 600). Moreover, the sensor (100) transmits characteristic parameters of significant reflection points (312, 404, 406, 602) to a server (200), the characteristic parameters being able to be used to determine the fill level (65) in a decision process. The server (200) receives the characteristic parameters of significant reflection points (312, 404, 406, 602). Said parameters are transformed into the fill level (65) of the filling material (60) by the server (200) by means of the decision process and/or using parameter data.