Self-activating adaptive measuring network for weak electromagnetic signals
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Solution Overview
Problem
Current measuring networks for spherics signals, which are weak electromagnetic signals associated with thunderstorms and atmospheric discharges, face challenges in accurately detecting and predicting these events due to interference and noise, particularly in distinguishing between different types of lightning discharges and predicting weather patterns with sufficient resolution.
Innovation Solution
A self-activating and adaptive measuring network with a base network of sensors that pre-process spherics burst signals and activate a sub-network for finer resolution, using orthogonal antennas and digital band filters to analyze pulse frequency and power density, allowing for the compilation of discharge weather maps and improved storm warnings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a dense network of measuring stations is deployed to improve detection precision, then measurement precision improves, but device complexity and cost increase
Solution Approach 1:
The measuring network is segmented into two functional layers: a dense sub-network with simple, low-cost sensors for high spatial resolution detection, and a sparse base network with complex preprocessing capabilities. This segmentation allows the system to achieve high measurement precision through the dense sub-network while avoiding the complexity and cost of making the entire dense network fully functional.
Solution Approach 2:
The base network stations operate in a partial action mode, remaining in standby and only activating when spherics bursts are detected by the sub-network. This allows the system to maintain the capability for high-precision measurement when needed while reducing complexity and power consumption during normal operation.
2Reliability
If all sensors remain active continuously to improve detection reliability, then reliability improves, but energy consumption increases
Solution Approach 1:
The base network sensors operate periodically rather than continuously, switching from a low-power standby state to an active detection state only when spherics bursts are detected by the sub-network. This periodic activation maintains detection reliability for rare events while dramatically reducing overall energy consumption.
Solution Approach 2:
The system uses the detection capability of the dense sub-network to trigger activation of base network stations, allowing the network to self-regulate its energy consumption based on actual detection needs rather than requiring external control.
3Productivity
If base network sensors perform pre-processing to obtain event patterns, then productivity improves, but device complexity increases
Solution Approach 1:
Processing functionality is segmented and concentrated in the base network stations rather than distributed to all sensors. The dense sub-network sensors perform only simple detection and transmission, while the sparse base network stations perform the complex pre-processing and pattern recognition, dividing the system into detection and processing functions.
4Loss of time
If the network operates in standby mode with selective activation, then loss of time is reduced, but measurement precision may deteriorate
Solution Approach 1:
The base network stations perform preliminary action by pre-processing signals and recognizing event patterns locally before transmitting to the control center. This preliminary processing at the edge of the network reduces the time required for data transmission and initial analysis, enabling faster response to spherics bursts.
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 enhances the detection and prediction of spherics bursts, enabling more precise local prediction of lightning and improving storm warnings, while also allowing for cost-effective and efficient data processing and transmission, and providing a basis for understanding biotropic effects and earthquake forecasting.
Implementation Method 1
at least one in particular broadband antenna body for detecting signals that can be assigned to the electromagnetic radiation
Implementation Method 2
at least one amplifier unit for low-noise amplification of the signals detected by means of the respective antenna body
Implementation Method 3
at least one filter unit for filtering the signals amplified by means of the amplifier unit, in particular with regard to technical interference signals
Data Source
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Figure 7
AI summary
Electromagnetic measuring systems for meteorology by means of which spherical signals are registered and analyzed are known in the prior art. According to patent claim 1, in order to configure a measuring network in such a way that the generation, development, and displacement of discharge processes relative to the extensive measuring network can be observed, a sub-network (SN) is subordinated to a basic network (BN), sensors (SSN) are arranged in the cells of the sub-network (SN), distributed with a spacing that is smaller in the ratio between 1:8 and 1:12, preferably 1:10, the sensors (SPN) of the base network (BN) that are in standby operation mode are self-activating upon receipt of spherical burst signals entering in an adjustable time period and perform pre-processing in order to obtain event patterns, and the central unit (Z) switches on the sensors (SSN) of the sub-network (SN) for finer resolution with respect to the observation. The invention belongs to the field of electromagnetic measuring systems, in particular for meteorology.