Machine learning device and thermal displacement compensation device

A machine learning device that optimizes, by machine learning, a calculation formula used for estimating the thermal displacement of a machine element to be thermally expanded in a machine tool based on a measured data group containing temperature data about the machine element and its surroundings and/or operating state data about the machine element, the machine learning device comprising:

• a measured data acquisition unit that acquires the measured data group;
• a thermal displacement acquisition unit that acquires a thermal displacement actual measured value about the machine element;
• a storage unit that uses the measured data group acquired by the measured data acquisition unit as input data, uses the thermal displacement actual measured value about the machine element acquired by the thermal displacement acquisition unit as a label, and stores the input data and the label in association with each other as teaching data;
• and
• a calculation formula learning unit that performs machine learning based on the measured data group and the thermal displacement actual measured value about the machine element, thereby setting a thermal displacement estimation calculation formula used for calculating the thermal displacement of the machine element based on the measured data group, wherein
• the thermal displacement estimation calculation formula uses a time lag element in measured data, and
• the calculation formula learning unit comprises:
• a first learning unit that, based on a difference between a thermal displacement estimated value about the machine element calculated by substituting the measured data group stored as the teaching data in the storage unit into the thermal displacement estimation calculation formula and the thermal displacement actual measured value about the machine element stored as the label in the storage unit, sets a coefficient relating to the time lag element in the thermal displacement estimation calculation formula by machine learning while making a coefficient relating to the measured data constant, without making the coefficient relating to the time lag element constant;
• a second learning unit that sets the coefficient relating to the measured data, without changing the coefficient relating to the time lag element in the thermal displacement estimation calculation formula by machine learning based on the difference while treating the coefficient relating to the time lag element as constant;
• and
• a repetition unit that repeats machine learning by the first learning unit and machine learning by the second learning unit in such a manner that the second learning unit performs the machine learning while treating the coefficient relating to the time lag element as constant in the thermal displacement estimation calculation formula set by the machine learning by the first learning unit, and that the first learning unit performs the machine learning while treating the coefficient relating to the measured data as constant, without changing the coefficient relating to the time lag element in the thermal displacement estimation calculation formula set by the machine learning by the second learning unit.