US 12,296,445 B2
Method for learning application shutdowns by finding characteristic signal shapes
Simon Erbele, Nufringen (DE); and Wolfgang Herberger, Stuttgart (DE)
Assigned to Robert Bosch GmbH, Stuttgart (DE)
Appl. No. 17/754,380
Filed by Robert Bosch GmbH, Stuttgart (DE)
PCT Filed Sep. 23, 2020, PCT No. PCT/EP2020/076484
§ 371(c)(1), (2) Date Mar. 31, 2022,
PCT Pub. No. WO2021/069208, PCT Pub. Date Apr. 15, 2021.
Claims priority of application No. 10 2019 215 415.8 (DE), filed on Oct. 9, 2019.
Prior Publication US 2022/0266429 A1, Aug. 25, 2022
Int. Cl. B25B 23/147 (2006.01); B25F 5/00 (2006.01); G05B 13/02 (2006.01); G05B 13/04 (2006.01)
CPC B25B 23/1475 (2013.01) [B25F 5/001 (2013.01); G05B 13/0265 (2013.01); G05B 13/042 (2013.01); B25D 2250/221 (2013.01)] 19 Claims
OG exemplary drawing
 
1. A method for operating a handheld power tool having an electric motor, the method comprising:
(S1) providing comparative information by (S1a) providing at least one model signal shape, and assigning the at least one model signal shape to a progress of work of the handheld power tool detected during the progress of work, and (S1b) providing a threshold value of correspondence;
(S2) ascertaining a signal of an operating variable of the electric motor during the progress of work;
(S3) ascertaining an assessment of correspondence by comparing the signal of the operating variable with the at least one model signal shape during the progress of work, the assessment of correspondence at least partially taking place based on the threshold value of correspondence; and
(S4) detecting the progress of work at least partially based on the assessment of correspondence during the progress of work,
wherein the providing comparative information takes place at least partially based on a learning process that occurs during the progress of work,
wherein the learning process includes performing and reading in at least one example application of the handheld power tool, the at least one example application including achievement of a specified progress of work of the handheld power tool, and
wherein the threshold value of correspondence is determined based on the learning process, the learning process further comprising:
(B1) providing at least one further model signal shape, the at least one further model signal shape being assignable to the progress of work of the handheld power tool;
(B2) ascertaining a further signal of an operating variable of the electric motor; and
(B3) comparing the further signal of the operating variable with the at least one further model signal shape at a time when a speed of the electric motor is being reduced during the progress of work and ascertaining a further threshold value of correspondence assigned to the example application during the progress of work.