http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-113361209-B

Outgoing Links

Predicate Object
classificationCPCInventive http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-214
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-2411
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F30-27
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-086
classificationIPCInventive http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-62
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06F30-27
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-08
filingDate 2021-07-23-04:00^^<http://www.w3.org/2001/XMLSchema#date>
grantDate 2022-09-27-04:00^^<http://www.w3.org/2001/XMLSchema#date>
publicationDate 2022-09-27-04:00^^<http://www.w3.org/2001/XMLSchema#date>
publicationNumber CN-113361209-B
titleOfInvention A Quantitative Analysis Method for Magnetic Anomaly of Superalloy Surface Defects
abstract The invention discloses a method for quantitative analysis of magnetic anomalies on the surface of superalloy surface defects. In the natural geomagnetic field environment, a weak magnetic detection instrument is used to scan the surface or near-surface of the superalloy, and the change of the magnetic induction intensity in the direction perpendicular to the surface of the test piece is collected. And carry out data processing, take the eigenvalue of the defect magnetic anomaly signal as the input value, and the length, width and depth parameter values of the corresponding defect as the output value to train the support vector machine model, establish the mapping relationship with the defect parameters, and use the K-fold cross-validation method. And genetic algorithm to optimize the parameters of support vector machine kernel function, use the optimized parameters to establish a defect prediction model, improve the accuracy of defect inversion, and achieve quantitative analysis of superalloy surface defects without additional excitation sources.
priorityDate 2021-07-23-04:00^^<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/SID419583196
http://rdf.ncbi.nlm.nih.gov/pubchem/compound/CID104727

Total number of triples: 17.