A data-driven approach to diagnostics of repetitive processes in the distribution domain: Applications to gearbox diagnosticsin industrial robots and rotating machines

Carvalho Bittencourt, André,1984-Linköpings universitet,Reglerteknik,Tekniska högskolan (författare)

A data-driven approach to diagnostics of repetitive processes in the distribution domain : Applications to gearbox diagnosticsin industrial robots and rotating machines

This paper presents a data-driven approach to diagnostics of systems that operate in a repetitive manner. Considering that data batches collected from a repetitive operation will be similar unless in the presence of an abnormality, a condition change is inferred by comparing the monitored data against an available nominal batch. The method proposed considers the comparison of data in the distribution domain, which reveals information of the data amplitude. This is achieved with the use of kernel density estimates and the Kullback–Leibler distance. To decrease sensitivity to disturbances while increasing sensitivity to faults, the use of a weighting vector is suggested which is chosen based on a labeled dataset. The framework is simple to implement and can be used without process interruption, in a batch manner. The approach is demonstrated with successful experimental and simulation applications to wear diagnostics in an industrial robot gearbox and for diagnostics of gear faults in a rotating machine.

Saarinen, KariABB Corporate Research, Västerås, Sweden (författare)
Sander Tavallaey, ShivaABB Corporate Research, Västerås, Sweden (författare)
Gunnarsson, SvanteLinköpings universitet,Reglerteknik,Tekniska högskolan(Swepub:liu)svagu90 (författare)
Norrlöf, MikaelLinköpings universitet,Reglerteknik,Tekniska högskolan,ABB Robotics, Västerås, Sweden(Swepub:liu)mikno78 (författare)
Linköpings universitetReglerteknik (creator_code:org_t)

Av författaren/redakt...: Carvalho Bittenc ...; Saarinen, Kari; Sander Tavallaey ...; Gunnarsson, Svan ...; Norrlöf, Mikael

Om ämnet

TEKNIK OCH TEKNOLOGIER: TEKNIK OCH TEKNO ...; och Elektroteknik oc ...; och Robotteknik och ...

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.