http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-110110803-A

Outgoing Links

Predicate Object
assignee http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_6fbb91e3f8cdf858527814216aa11142
classificationCPCInventive http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-23
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-2113
classificationIPCInventive http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-62
filingDate 2019-05-15^^<http://www.w3.org/2001/XMLSchema#date>
inventor http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_aea0501ee366eb4305dd890abc793450
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_ae1c4f9af7356a5d515b1cd5b6b73c4b
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_22bd24a5dbc667846bb57009e0003439
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_f754da479edc7b6f28e95d79bbdf8f2e
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_6c554310e8e378d4a31d400bf92b36b0
publicationDate 2019-08-09^^<http://www.w3.org/2001/XMLSchema#date>
publicationNumber CN-110110803-A
titleOfInvention A kind of robot fault diagnosis method, device and equipment
abstract The present application discloses a robot fault diagnosis method, which can collect the operation data of the robot as the original feature set, filter the sensitive feature set from the original feature set, determine the feature weight of the sensitive feature in the sensitive feature set, and then use the inverse based on the feature weight according to the feature weight. The clustering method of the covariance matrix clusters the sensitive feature set, and finally determines the fault diagnosis result of the robot according to the clustering result. It can be seen that this method uses the clustering method based on the inverse covariance matrix to achieve clustering, because the clustering method can perform fault diagnosis by finding different behaviors of the robot under the same operating state, which improves the reliability of diagnosis. Considering the different sensitivity of each sensitive feature in fault diagnosis, assigning corresponding feature weight to each sensitive weight improves the accuracy of diagnosis. The present application also provides a robot fault diagnosis apparatus, device and computer-readable storage medium, the functions of which correspond to the above method.
isCitedBy http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-111126822-B
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-111126822-A
priorityDate 2019-05-15^^<http://www.w3.org/2001/XMLSchema#date>
type http://data.epo.org/linked-data/def/patent/Publication

Incoming Links

Predicate Subject
isDiscussedBy http://rdf.ncbi.nlm.nih.gov/pubchem/substance/SID413985455
http://rdf.ncbi.nlm.nih.gov/pubchem/compound/CID688344

Showing number of triples: 1 to 20 of 20.