Mitsubishi Electric Corporation

Satoshi Namematsu

Daiki Ata

Daisuke Ammi

Takayuki Sawada

Tomo Ikuyama

A learning device and other techniques allow accurate diagnosis of a production facility. A learning device () includes a data acquirer that acquires data for learning, and a model generator that generates a learning model for inferring a condition of a workpiece () handled in a production facility () on the basis of the data for learning. The data for learning includes setting data indicating a setting of the production facility (), image data indicating an image of the production facility () captured by a camera (), temperature data indicating a surface temperature of the production facility () measured by a temperature sensor (), distance data indicating a distance from a range sensor () to the production facility () measured by the range sensor (), and condition data indicating the condition of the workpiece () handled in the production facility ().

Learning device, diagnostic system, and model generation method to diagnose abnormality based on temperature measurement in a production facility

An article image data acquirer acquires article image data as a target of optical character recognition (OCR). An inference result data generator generates first inference result data and second inference result data by inputting the article image data as the target of the OCR into a trained model. An inference result data outputter outputs the first inference result data and the second inference result data. An image filter generator generates a first image filter based on the first inference result data and a second image filter based on the second inference result data. An image filter outputter outputs the first image filter and the second image filter.

Inference device, inference method, and recording medium

A training data acquirer acquires training data including article image data, image-filter-related data indicating a combination of a plurality of image filters used for image processing of the article image data and a value of a parameter for each of the plurality of image filters, and optical character recognition (OCR) score data indicating a score of character recognition output through OCR when image processing is performed on the article image data using the image filters based on the image-filter-related data. A trained model generator generates a trained model indicating a relationship between the article image data, the image-filter-related data, and the OCR score data through machine learning using the training data.

Image-filter generation system, image-filter generation device, learning device, and learning method

A communication device communicates, in a first cycle, with sensors connected through a network to acquire, from the sensors, measurement data measured by the sensors in data acquisition cycles longer than or equal to the first cycle and store the data in a storage. The communication device includes a grouping section to classify the sensors into groups based on the data acquisition cycles and acquire the measurement data from the classified sensors, and reclassify one of the sensors into a different group when determining that a maximum size of data to be received per first cycle exceeds a threshold for a communication band of the network, and a memory map generator to calculate a timing and an address to store the measurement data based on the data acquisition cycles and the groups resulting from the classification.

Communication device, communication method, and recording medium

A parameter adjustment device () adjusts a parameter relating to control of laser light emitted from a measurement sensor () onto an object. A parameter calculator () calculates the parameter by applying, to a trained model generated through machine learning using training data sets each including waveform data of an amount of light received by the measurement sensor () and data indicating the parameter used to acquire the waveform data, waveform data newly acquired in a new state. The parameter calculated by the parameter calculator () enables measurement of the object using the measurement sensor () in the new state. A parameter outputter () outputs data indicating the parameter calculated by the parameter calculator ().

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Tokyo, Japan

Satoshi Namematsu