Power equipment sensing quantity compression and reconstruction method suitable for Internet of Things and related device
By using dictionary matrix to compress and reconstruct the sensor data of the power transformer in the Internet of Things communication system, the problem of high real-time acquisition and transmission of sensing data is solved, effective sparse and efficient transmission of data is achieved, hardware costs are reduced and data quality is maintained.
Patent Information
- Application Number
- CN202411744133.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-30
- Publication Date
- 2025-03-25
AI Technical Summary
In the Internet of Things communication system, the real-time acquisition and transmission of power transformer sensing data requires high sampling speed, resulting in excessive economic cost of equipment and the difficulty in effectively compressing and reconstructing sensing data in the prior art.
The sensor data is compressed and reconstructed by using a dictionary matrix. By constructing a dictionary matrix composed of two basic matrices with as small as possible, the sensing vector is sparse, and the data is effectively compressed, and the correlation of the dictionary matrix is optimized by using the gradient descent iterative method to improve compression efficiency.
By sparsely processing sensor data, the transmission rate requirements of the Internet of Things communication system are significantly reduced and the hardware cost is reduced. At the same time, under the same sparse conditions, the distortion rate is low, and the decompressed data can maintain the characteristics and value of the original data.
Smart Images
Figure CN119696592A_ABST