Wind power digital twinning robustness detection method based on time-frequency revolving door perception matching

By adopting the robust detection method of time-frequency rotary door perception matching in the wind power digital twin system, the fan detection signal is preprocessed and the convolutional neural network receptive field is updated, which solves the problems of insufficient data processing capabilities and inaccurate robustness judgment, and achieves more efficient data processing and robustness judgment.

CN119646561AActive Publication Date: 2025-03-18HUNAN UNIV
8 Cites 2 Cited by

Patent Information

Application Number
CN202411502882.1
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-10-25
Publication Date
2025-03-18
Estimated Expiration
2044-10-25

AI Technical Summary

Technical Problem

The existing wind power digital twin systems require high sampling rates when collecting signals, resulting in large data volume and limited data processing capabilities, making it difficult to effectively deal with spectrum deviations and aliasing when signal changes smoothly, as well as misdiagnosis caused by signal mutations, which reduces the accuracy of robust judgments.

Method used

The wind power digital twin robustness detection method based on time-frequency rotational door perception matching is adopted. The fan detection signal is preprocessed through the rotational door algorithm to ensure that the amplitude error of the characteristic frequency is less than the preset threshold, and the receptive field of the convolutional neural network is updated based on the preprocessed signal to determine the number of convolutional layers and improve the accuracy of data processing capabilities and robustness judgment.

Benefits of technology

It effectively solves the misdiagnosis problems caused by signal simultaneous change, as well as signal mutations, improves the robustness and accuracy of the digital twin system, and reduces the storage and calculation pressure of data processing.

✦ Generated by Eureka AI based on patent content.
Patent Text Reader

Abstract

The invention discloses a wind power digital twinning robustness detection method based on time-frequency revolving door perception matching, and the method comprises the steps: obtaining a fan detection signal generated by digital twinning and a fan detection signal collected by a sensor, the fan detection signal being the temperature, radial vibration, axial vibration, current, voltage or power of a fan; the two kinds of fan detection signals are preprocessed through a rotating door algorithm SDA so that the characteristic frequency amplitude error of the preprocessed fan detection signals can be smaller than a preset threshold value; and respectively updating receptive fields of the corresponding convolutional neural networks based on the preprocessed fan detection signals so as to determine the number of convolutional layers of the convolutional neural networks, and outputting the difference between the number of convolutional layers of the convolutional neural networks of the two fan detection signals as a robustness detection result of digital twinning. The invention aims to improve the data processing capability, solve the problem of misdiagnosis possibly caused by spectrum deviation and aliasing and signal abrupt change when the signal stably changes, and improve the accuracy of robustness judgment.
Need to check novelty before this filing date? Find Prior Art