ABNORMALITY DIAGNOSTIC DEVICE AND ABNORMALITY DIAGNOSTIC METHOD

• Main Authors: KUSANO MASAMI, MIYABE SHOZO, MIYAKOSHI NAOKI, MAEDA SHUNJI, CHIKUMA SHIGEYOSHI, SUZUKI TADASHI, NODA TOJIRO, SHIBUYA HISAE, NAKAJIMA IWAO, KOBARI TOSHIAKI
• Format: Patent
• Language: English; Japanese
• Published: 04.04.2016
• Subjects: CONTROL OR REGULATING SYSTEMS IN GENERAL; CONTROLLING; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS; PHYSICS; REGULATING

PROBLEM TO BE SOLVED: To enable diagnosis of a state of a machine plant with excellent reliability.SOLUTION: An abnormality diagnostic device 1 comprises: time series data acquisition unit 10 which acquires sensor data from a plurality of sensors installed in a machine plant as time series data; a performance measure calculation unit 12 which calculates a performance measure that is an index indicating the performance of the machine plant on the basis of a statistical method using the time series data as learning data; an approximate equation calculation unit 13 which calculates an approximate equation approximating transition of the performance measure calculated on the basis of the time series data acquired in the past by use of a polynomial equation; and a performance measure estimation unit 14 which estimates the performance measure until a predetermined time in the future by use of the approximate equation. Whenever acquiring the time series data, the performance measure is calculated with respect to the latest time series data, the performance measure of the latest time series data is added to the transition to calculate the approximate equation, and the performance measure in the future is estimated by use of that approximate equation.SELECTED DRAWING: Figure 1 【課題】機械設備の状態の診断を良好な信頼性で行うことを可能とする。【解決手段】異常診断装置１は、機械設備に設置した複数のセンサからのセンサデータを時系列データとして取得する時系列データ取得部１０と、時系列データを学習データとした統計的手法により、機械設備の性能を示す指標である性能測度を算出する性能測度算出部１２と、過去に取得した時系列データに基づいて算出した性能測度の推移を、多項式により近似した近似式を算出する近似式算出部１３と、近似式を用いて、将来の所定の時点までの性能測度を推定する性能測度推定部１４と、を備え、時系列データを取得するごとに、最新の時系列データについての性能測度を算出し、最新の時系列データについての性能測度を前記推移に加えた近似式を算出し、その近似式を用いて将来の性能測度を推定する。【選択図】図１