Patent · US Active

Training a deep learning system to detect engine knock with accuracy associated with high fidelity knock detection sensors despite using data from a low fidelity knock detection sensor

US11526747B2 · kind B2 · utility

0Cited by

6References

12Claims

0Family size

Assignee

Robert Bosch GmbH · DE

Inventors

Joseph Szurley · Saint Clair, US
Samarjit Das · Wexford, US

Key dates

Filing date	Dec 28, 2018
Grant date	Dec 13, 2022
Priority date	—
Expiry date	Jan 27, 2040

Classification

Technology area (CPC G)Physics
CPC primaryG06N20/00
WIPO fieldComputer technology
WIPO sectorElectrical engineering

Abstract

A system for training a deep learning system to detect engine knock with accuracy associated with high fidelity knock detection sensors despite using data from a low fidelity knock detection sensor. The system includes an engine, a high fidelity knock detection sensor, a low fidelity knock detection sensor, and an electronic processor. The electronic processor is configured to receive first data from the high fidelity knock detection sensor. The electronic processor is also configured to receive second data from the low fidelity knock detection sensor. The electronic processor is further configured to map the first data to the second data, train the deep learning system, using training data including the mapped data, to determine a predicted peak pressure using data from the low fidelity knock detection sensor, receive third data from the low fidelity knock detection sensor, and using the third data, determine the predicted peak pressure.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.