Anomaly detection device for rotating machinery

Abstract

To provide a rotating machinery anomaly diagnostic device with excellent accuracy in diagnosing abnormalities in rotating machinery. [Solution] A vibration sensor for measuring the vibration of rotating machinery; an operation database for collecting and storing measurement data from the vibration sensor; a rotating machinery information database for recording at least the model, specifications, and performance information of the rotating machinery; a maintenance work history database for recording the maintenance work history of the rotating machinery; and a diagnostic processing unit for diagnosing abnormalities in the rotating machinery using the data from each of the above databases. A rotating equipment abnormality diagnosis device comprising the diagnostic processing unit which maintains a diagnostic model for each type of rotating equipment and performs the diagnosis.

Claims

1. A vibration sensor that measures vibrations in rotating machinery, An operating database that collects and stores measurement data from the vibration sensor, A rotary equipment information database that records at least the model, specifications, and performance information of rotating equipment, A maintenance work history database that records the maintenance work history of rotating machinery, A diagnostic processing unit that diagnoses abnormalities in rotating machinery using data from the above databases, A rotating equipment abnormality diagnosis device equipped with, The aforementioned diagnostic processing unit maintains a diagnostic model for each model and performs the diagnosis accordingly. This diagnostic model outputs an anomaly score as numerical information calculated using acceleration RMS and frequency data, along with parameters α and β obtained through machine learning, with the formula: Anomaly score = α × acceleration RMS + β × peak frequency. The diagnostic model stores α and β as an array. The diagnostic processing unit has the function of extracting maintenance work for rotating equipment failures from the maintenance work history database, identifying the time and type of failure, and training the diagnostic model by machine learning the change patterns of diagnostic data before the failure occurred. A diagnostic device for detecting abnormalities in rotating machinery.

2. The rotating equipment abnormality diagnosis device according to claim 1, wherein each of the aforementioned databases is capable of identifying individual rotating equipment using a common identification code.

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