Wind Turbine Lightning Detection Using Existing Sensor Signals
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Solution Overview
Problem
Conventional lightning detection systems for wind turbines are inadequate as they fail to detect the number of lightning sequences between readings, cannot automatically identify affected blades, and require costly installations of sensors, while also lacking the ability to register lightning event parameters or localize impacts.
Innovation Solution
A lightning detection system comprising sensing devices that generate sensor signals representing working state parameters, a lightning signal processing subsystem to combine and process these signals, extract noise signals, and compare them with lightning signal profiles to determine the presence of lightning noise signals, thereby detecting lightning strikes effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional lightning detection systems use specialized sensors (magnetic cards, antennas), then lightning strike detection is enabled, but additional installation cost and device complexity are incurred
Solution Approach 1:
The patent applies universality by utilizing existing sensors (temperature, humidity, pressure, vibration) that are already installed in wind turbines for monitoring purposes. These sensors serve dual functions: their primary function for monitoring and the secondary function of detecting lightning strikes through noise signal analysis. This eliminates the need for separate specialized lightning detection sensors, reducing device complexity and installation costs while maintaining reliable lightning detection capability.
2Measurement precision
If magnetic cards are used for lightning detection, then peak current measurement is achieved, but the system cannot detect the number of lightning sequences between readings
Solution Approach 1:
The patent applies continuity of useful action by using sensors that continuously monitor environmental parameters without interruption. The noise signal analysis continues uninterrupted, allowing the system to detect and count multiple lightning sequences that occur between magnetic card readings. This continuous monitoring ensures that no lightning events are missed and provides complete information about the number and timing of all lightning strikes.
3Reliability
If antennas are installed on wind turbine towers for lightning detection, then lightning currents and magnetic fields are detected, but the system requires reset by acknowledgement signal and cannot automatically identify affected blades
Solution Approach 1:
The patent applies segmentation by dividing the wind turbine into multiple monitored sections (different blades, tower sections) with distributed sensors. Each sensor or sensor group is associated with a specific location, allowing the system to identify which specific blade or section was affected by a lightning strike. This segmentation enables automatic identification of affected components without requiring system reset or manual intervention.
4Reliability
If conventional lightning detection systems register lightning events, then occurrence is detected, but lightning event parameters and impact localization are not registered
Solution Approach 1:
The patent applies dimensionality change by transitioning from simple binary detection (lightning strike occurred or not) to multi-parameter analysis. The system analyzes multiple dimensions of data including temperature changes, humidity variations, pressure fluctuations, and vibration patterns simultaneously. This multi-dimensional approach enables the system to not only detect lightning events but also determine their parameters (intensity, timing, duration) and localize the impact position based on which sensors detected the noise signals.
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
The system enables timely detection of lightning strikes, reduces downtime and repair costs by accurately identifying lightning events and their parameters, and automates the process without the need for additional sensor installations.
Implementation Method 1
sensing devices configured to generate sensor signals representative of one or more working state parameters
Implementation Method 2
extract noise signals from the composite signal, and compare the extracted noise signals with one or more lightning signal profiles
Data Source
AI summary
A lightning detection system is presented. The lightning detection system includes a plurality of sensing devices configured to generate sensor signals representative of one or more working state parameters of an object. The lightning detection system further includes a lightning signal processing subsystem configured to combine the sensor signals representative of the one or more working state parameters received from the plurality of sensing devices to generate a composite signal, extract noise signals from the composite signal, and compare the extracted noise signals with one or more lightning signal profiles to determine existence of lightning noise signals in the extracted noise signals, wherein the lightning noise signals are induced in the sensor signals in response to a lightning strike on the object.