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US 12,276,566 B2Granted
Equipment malfunction diagnosis apparatus using sound spectrogram image, and method therefor
AssigneeWi.Plat Co., Ltd.
InventorSang Hoon Cha
Life of this patent
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Abstract
Disclosed are an equipment malfunction diagnosis apparatus using a sound spectrogram image, and a method therefor. In other words, the present invention collects sound data through a sensor unit provided at one side of equipment, converts the collected sound data into a spectrogram image, and determines malfunction of the equipment and classifies a cause of the malfunction by performing machine learning using the spectrogram image as an input value, thereby quickly and accurately identifying the cause of the malfunction when it is identified that there is the malfunction in the equipment, and providing a counterplan in response thereto.
Claims7
An apparatus for diagnosing an equipment failure using a sound spectrogram image, the apparatus comprising:
- a sensor unit having a fixing gear including a magnet or ring detachable from an equipment, and configured to collect sound data and collection position information of the sound data from one side of the equipment;
- and
- a controller configured to convert the collected sound data into a spectrogram image, perform machine learning based on the converted spectrogram image, a type of the equipment, and the collected collection position information of the sound data, and determine whether a failure occurs in the equipment related to the collected sound data based on a machine learning result,
- wherein the controller performs data classification for training by classifying each of a plurality of pieces of previously collected equipment-specific sound data into any one type of normal sound, shaft failure sound, bearing damage sound, cavitation sound, impeller failure sound, and motor bearing sound, converts the plurality of pieces of classified equipment-specific sound data into spectrogram images, divides the plurality of converted equipment-specific spectrogram images into a train set and a test set, and then performs a training and test function for a preset failure diagnosis and failure cause determination model using the divided train set and test set,
- the controller performs machine learning using the converted spectrogram image, the type of the equipment, and the collected collection position information of the sound data as input values of the failure diagnosis and failure cause determination model and determines whether the failure occurs in the equipment related to the collected sound data based on a machine learning result, and
- when it is determined that the failure occurs in the equipment related to the collected sound data, the controller classifies a cause of the failure as any one of a shaft failure, bearing damage, cavitation, an impeller failure, and a motor bearing failure based on the machine learning result.
3 more elements
A method of diagnosing an equipment failure using a sound spectrogram image, the method comprising:
- classifying, by a controller, each of a plurality of pieces of previously collected equipment-specific sound data into any one type of normal sound, shaft failure sound, bearing damage sound, cavitation sound, impeller failure sound, and motor bearing sound to perform data classification for training;
- converting, by the controller, the plurality of pieces of classified equipment-specific sound data into spectrogram images and dividing the plurality of converted equipment-specific spectrogram images into a train set and a test set at a preset ratio;
- performing, by the controller, a training and test function for a preset failure diagnosis and failure cause determination model using the divided train set and test set;
- collecting, by a sensor unit, sound data and collection position information of the sound data from one side of an equipment;
- converting, by the controller, the collected sound data into a spectrogram image;
- performing, by the controller, machine learning based on the converted spectrogram image, a type of the equipment, and the collected collection position information of the sound data and determining whether a failure occurs in the equipment related to the collected sound data based on a machine learning result;
- and
- when it is determined that the failure occurs in the equipment related to the collected sound data, classifying, by the controller, a cause of the failure as any one of a shaft failure, bearing damage, cavitation, an impeller failure, and a motor bearing failure based on the machine learning result,
- wherein the sensor unit has a fixing gear including a magnet or ring detachable from the equipment, and
- the determining of whether the failure occurs in the equipment related to the collected sound data comprises performing machine learning using the converted spectrogram image, the type of the equipment, and the collected collection position information of the sound data as input values of the failure diagnosis and failure cause determination model, and determining whether the failure occurs in the equipment related to the collected sound data based on a machine learning result.
7 more elements
Dependencies are inferred from the claim text.