Patent application EP18206624A (EP), filed 2018-11-16
Publication number: EP3489780A2
Title: EXAMINING APPARATUS, EXAMINING METHOD, PROGRAM AND RECORDING MEDIUM
Abstract: [0001]    To easily perform examination of at least one facility based on detection signals of a plurality of sensors installed in the facility. Provided are an examining apparatus, an examining method, a program and a recording medium, including: a group designation acquiring unit (120) to acquire designation of a targeted group including a plurality of targeted sensors (20) to be analyzed among a plurality of sensors (20) installed in at least one facility (10); a sensor data acquiring unit (110) to acquire sensor data from each targeted sensor included in the targeted group; a learning unit (160) to learn an analysis model by using the sensor data from each targeted sensor included in the targeted group; and an examining unit (190) to examine the facility (10) by using the learned analysis model.
IPC codes: G05B  23/    02            A I
Claims: number: 1
text: An examining apparatus comprising:
number: 2
text: The examining apparatus according to claim 1, further comprising a user interface unit to input feedback on an examination result obtained by using the analysis model, wherein
the learning unit learns the analysis model by further using the feedback.
number: 3
text: The examining apparatus according to claim 2, further comprising an alarm output unit to output an alarm if the examination result obtained by using the analysis model indicates an abnormality in the facility, wherein
the user interface unit inputs the feedback indicating whether the alarm is correct.
number: 4
text: The examining apparatus according to claim 3, further comprising a storage unit to store labeled data obtained by labeling, with the feedback on the alarm output by the alarm output unit, a portion of the sensor data from each targeted sensor included in the targeted group, on which portion the feedback is made, wherein
the learning unit learns the analysis model by using the labeled data stored in the storage unit.
number: 5
text: The examining apparatus according to any one of claims 1 to 4, further comprising:
number: 6
text: The examining apparatus according to claim 5, wherein the identification unit identifies, from the operational record, at least one of a maintenance period of the facility, a stop period of the facility, a startup period of the facility and a test running period of the facility as the period in which learning of the analysis model is not to be performed.
number: 7
text: The examining apparatus according to any one of claims 1 to 6, wherein
number: 8
text: The examining apparatus according to claim 7, wherein
number: 9
text: The examining apparatus according to claim 7 or 8, wherein the model selecting unit selects the analysis model used for examining the facility from among the learned plurality of types of analysis models according to examination accuracy.
number: 10
text: The examining apparatus according to any one of claims 7 to 9, wherein
number: 11
text: The examining apparatus according to any one of claims 1 to 10, wherein
number: 12
text: An examining apparatus comprising:
number: 13
text: A program that causes a computer to function as an examining apparatus comprising:
number: 14
text: A recording medium having recorded thereon a program that causes a computer to function as an examining apparatus comprising:
number: 15
text: An examining method comprising:
Office action: search_report, dated 2019-05-29
Rejection reasons: novelty_epc_54
Prior art cited: ref_id: - GO TAKAMI; MOE TOKUOKA; HIROTSUGU GOTO; YUUICHI NOZAKA: "Machine Learning Applied to Sensor Data Analysis", YOKOGAWA TECHNICAL REPORT, vol. 59, no. 1, pages 27 - 30, XP002780115
ref_type: npl
severity: background
ref_id: - HIROAKI KANOKOGI; GO TAKAMI: "Machine Learning Applied to Sensor Data Analysis: Part 2", YOKOGAWA TECHNICAL REPORT, vol. 60, no. 1, pages 35 - 38
ref_type: npl
severity: background
ref_id: US2013173218
ref_type: patent
severity: novelty_destroying
ref_id: - SHARMA GEETIKA ET AL, "Multi-sensor Visual Analytics Supported by Machine-Learning Models", 2015 IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOP (ICDMW), IEEE, (20151114), doi:10.1109/ICDMW.2015.190, pages 668 - 674, XP032859277 [X] 1-11,13-15 * page  671  - page  673 *
ref_type: npl
severity: novelty_destroying
Final disposition: pending (2019-05-29)