Method for self-diagnostic data acquisition system and self-diagnostic system

By using the subspace approximation technique of singular value decomposition, the problem of separating foreground signals from background noise on a mobile platform was solved, enabling high-quality acoustic monitoring and platform health monitoring.

CN114690122BActive Publication Date: 2026-06-12ROBERT BOSCH GMBH
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
ROBERT BOSCH GMBH
Filing Date
2021-12-30
Publication Date
2026-06-12

AI Technical Summary

⚠Technical Problem

Existing technologies struggle to effectively separate foreground signals from background noise in complex environments, especially when performing acoustic surveillance on mobile platforms, where background noise interferes with the identification of objects of interest and the monitoring of platform health.

⚗Method used

A subspace approximation method based on singular value decomposition is used to remove background noise from the signal. The foreground signal is extracted from the sensor data of the mobile platform through the subspace approximation technique based on singular value decomposition, and the platform's operating characteristics are monitored by detecting spectral changes in background noise.

🎯Benefits of technology

It improves signal quality, enables accurate identification of directional signal sources, and provides real-time health monitoring of the platform's operational status, enhancing acoustic monitoring capabilities in complex environments.

✦ Generated by Eureka AI based on patent content.

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Abstract

The invention relates to a dynamic spatio-temporal beamforming self-diagnostic system. A method for self-diagnosis by a controller of a data acquisition system for acquiring a calibration image of a region includes requesting a signal from a sensor associated with a mobile platform in the region, removing background noise associated with the mobile platform from the signal, thereby concentrating the measurements on a foreground signal, wherein the background noise is removed from the foreground signal via a subspace approximation using singular values, requesting a temporally preceding signal indicative of temporally preceding measurements of a parameter, wherein temporally preceding background noise is removed from the temporally preceding foreground signal via a subspace approximation using singular value decomposition, and outputting a status signal indicative of a change in an operational characteristic of the mobile platform in response to a change detection that a difference between a spectrogram indicative of the background noise and a temporally preceding spectrogram of the temporally preceding background noise exceeds a predetermined threshold at a predetermined frequency.
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