US 11,989,013 B2
Abnormality detection apparatus, abnormality detection system, and learning apparatus, and methods for the same and non-temporary computer-readable medium storing the same
Kosuke Yoshida, Tokyo (JP)
Assigned to NEC CORPORATION, Tokyo (JP)
Appl. No. 17/421,521
Filed by NEC Corporation, Tokyo (JP)
PCT Filed Jan. 18, 2019, PCT No. PCT/JP2019/001535
§ 371(c)(1), (2) Date Jul. 8, 2021,
PCT Pub. No. WO2020/148904, PCT Pub. Date Jul. 23, 2020.
Prior Publication US 2022/0083039 A1, Mar. 17, 2022
Int. Cl. G05B 23/02 (2006.01); G06F 18/2132 (2023.01); G06N 3/04 (2023.01)
CPC G05B 23/0221 (2013.01) [G06F 18/2132 (2023.01); G06N 3/04 (2013.01)] 10 Claims
OG exemplary drawing
 
1. An abnormality detection apparatus comprising:
at least one memory configured to store instructions and a learned self-encoder, the learned self-encoder including a predetermined number of two or more elements as input layers, and
at least one processor configured to execute the instructions to:
extract, from time series data measured by one or more sensors during a first period of time, a target data group including a number of data pieces equal to the predetermined number of the elements of the learned self-encoder, the target data group being for a predetermined period of time which is at least part of the first period;
convert the target data group into multi-dimensional vector data having a number of elements equal to the predetermined number of elements of the learned self-encoder;
input the multi-dimensional vector data to the self-encoder to obtain output vector data having a number of elements equal to the predetermined number of elements of the learned self-encoder;
identify a time period in which there may be an abnormality within the predetermined period based on a difference between the output vector data and the multi-dimensional vector data; and
output abnormality detection information including the identified time period.