Method for learning application shutdowns by finding characteristic signal shapes

US12296445B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-12296445-B2
Application numberUS-202017754380-A
CountryUS
Kind codeB2
Filing dateSep 23, 2020
Priority dateOct 9, 2019
Publication dateMay 13, 2025
Grant dateMay 13, 2025

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  1. Title

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  5. First independent claim

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Abstract

Official abstract text for this publication.

The disclosure relates to a method for operating a handheld power tool comprising an electric motor and the method comprising: S1 providing comparative information, comprising: S1a providing at least one model signal shape, the model signal shape being assignable to progress of work of the handheld power tool; S1b providing a threshold value of correspondence; S2 ascertaining a signal of an operating variable of the electric motor; S3 comparing the signal of the operating variable with the model signal shape and ascertaining assessment of correspondence from the comparison, the assessment of correspondence at least partially taking place on the basis of the threshold value of correspondence; S4 detecting the progress of work at least partially on the basis of the assessment of correspondence ascertained in method step S3; the providing of the comparative information at least partially taking place on the basis of a learning process.

First claim

Opening claim text (preview).

The invention claimed is: 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. 2. The method as claimed in claim 1 , wherein the at least one model signal shape is at least partially provided based on the learning process, the learning process further comprising: (A1) ascertaining a further signal of an operating variable of the electric motor based on the example application; (A2) determining a first further model signal shape, assigned to the example application, based on the further signal of the operating variable while achieving the specified progress of work; and (A2′) determining a second further model signal shape, assigned to the example application, based on the further signal of the operating variable, at a time of achieving the specified progress of work. 3. The method as claimed in claim 2 , the learning process further comprising: one of the performing and reading in at least two example applications; and ascertaining the at least one model signal shape from the first and second further model signal shapes assigned to the at least two example applications. 4. The method as claimed in claim 1 , the (B1) providing the at least one further model signal shape further comprising: (A1) ascertaining a further signal of an operating variable of the electric motor based on the example application; (A2) determining a first further model signal shape, assigned to the example application, based on the further signal of the operating variable while achieving the specified progress of work; (A2′) determining a second further model signal shape, assigned to the example application, based on the further signal of the operating variable, at a time of achieving the specified progress of work. 5. The method as claimed in claim 1 , the learning process further comprising: one of the performing and reading in at least two example applications; and ascertaining of an average value of the threshold value of correspondence from two or more threshold values of correspondence assigned to the at least two example applications. 6. The method as claimed in claim 1 , the reading in the at least one example application further comprising: reading in an example signal of an operating variable of the electric motor by the handheld power tool. 7. The method as claimed in claim 1 further comprising: (S5) performing a first routine of the handheld power tool at least partially based on the progress of work. 8. The method as claimed in claim 7 , the first routine comprising: stopping the electric motor while taking into account at least one of a defined parameter, a predetermined parameter, and a parameter predetermined by a user of the handheld power tool. 9. The method as claimed in claim 7 , the first routine comprising: changing a speed of the electric motor. 10. The method as claimed in claim 9 , wherein the changing the speed of the electric motor takes place at least one of multiply and dynamically, the changing the speed being at least partially determined based on the learning process based on the example applications. 11. The method as claimed in claim 1 , wherein the operating variable is one of a speed of the electric motor and an operating variable correlating with the speed. 12. The method as claimed in claim 1 , the (S2) ascertaining the signal of the operating variable further comprising: recording the signal of the operating variable as one of (i) a progression over time of measured values of the operating variable and (ii) as measured values of the operating variable as a variable of the electric motor correlating with the progression over time. 13. The method as claimed in claim 1 , the (S2) ascertaining the signal of the operating variable further comprising: recording the signal of the operating variable as a progression over time of measured values of the operating variable, wherein the method further comprises, after the (S2) ascertaining the signal of the operating variable: (S2a) transforming the progression over time of the measured values of the operating variable into a progression of the measured values of the operating variable as a variable of the electric motor correlating with the progression over time. 14. The method as claimed in claim 1 , wherein the handheld power tool is an impact screwdriver and the progress of work is impact operation. 15. A handheld power tool comprising: an electric motor; a measured-value pickup of an operating variable of the electric motor; and a control unit configured to: (S1) provide comparative information by (S1a) providing at least one model signal shape, the at least one model signal shape being assignable 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) ascertain a signal of an operating variable of the electric motor during the progress of work; (S3) ascertain 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) detect 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

Assignees

Inventors

Classifications

  • in which a parameter or coefficient is automatically adjusted to optimise the performance · CPC title

  • the criterion being a learning criterion · CPC title

  • Gearings, speed selectors, clutches or the like specially adapted for rotary tools · CPC title

  • Sensors · CPC title

  • for impact wrenches or screwdrivers · CPC title

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Frequently asked questions

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What does patent US12296445B2 cover?
The disclosure relates to a method for operating a handheld power tool comprising an electric motor and the method comprising: S1 providing comparative information, comprising: S1a providing at least one model signal shape, the model signal shape being assignable to progress of work of the handheld power tool; S1b providing a threshold value of correspondence; S2 ascertaining a signal of an ope…
Who is the assignee on this patent?
Bosch Gmbh Robert
What technology area does this patent fall under?
Primary CPC classification B25B23/1475. Mapped technology areas include Operations & Transport.
When was this patent published?
Publication date Tue May 13 2025 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 6 related publications on this page (citations in our corpus or others sharing the same primary CPC).