Abstract: According to one embodiment, a condition monitoring apparatus includes a processing circuitry. The processing circuitry is configured to collect a sensor signal output from a sensor that monitors a condition of a mechanical device that is at least partially mobile. The processing circuitry is configured to diagnose a presence or absence of an anomaly in the mechanical device based on the sensor signal. The processing circuitry is configured to cut out the sensor signal in a time width according to any one or more of a speed, an acceleration, and a jerk of the mechanical device. The processing circuitry is configured to determine the presence or absence of an anomaly based on the cut out sensor signal.

Abstract: According to one embodiment, a state diagnosis apparatus includes a processing circuit. The processing circuit executes a model receiving, as an input, first data relating to a state of a device at each of a plurality of stages along a time series and outputting a first numerical value quantitatively indicating the first data for each of the stages. The processing circuit determines whether or not first numerical values output from the model monotonously change along the time series.

Abstract: According to one embodiment, a monitoring system includes a processor. The processor accepts first data output from a first detector. The first detector detects a signal caused by equipment. The processor performs a first determination when a first value is in a first state. The first value indicates a state of the first detector or an environment where the equipment is provided. The first determination determines a condition of the equipment by using a first model and the first data. The processor performs a second determination when the first value is in a second state different from the first state. The second determination determines the condition of the equipment by using a second model and the first data. The second model is different from the first model.

Abstract: According to one embodiment, a condition monitoring device includes a processor. The processor is configured to acquire a time-series signal about a condition of a monitor target from a first sensor, acquire operation timing information indicating start of operation of the monitor target, detect a first operation segment signal from the time-series signal based on the operation timing information, detect a second operation segment signal from the first operation segment signal based on a waveform feature of the first operation segment signal, and determine the condition of the monitor target based on the second operation segment signal.

Abstract: According to one embodiment, a learning apparatus includes a memory and a hardware processor connected to the memory which learns a transformation function to extract a feature value of an input signal. The hardware processor updates the transformation function based on a signal indicative of a first condition and a signal indicative of a second condition which is different from the first condition, using a first loss function on the signal indicative of the first condition and a second loss function on the signal indicative of the second condition. The second loss function is designed such that the second condition becomes distant from the first condition.

Abstract: According to one embodiment, a learning apparatus includes a processor. The processor acquires data with a label indicating whether the data is normal data or anomalous data. The processor calculates an anomaly degree indicating a degree to which the data is the anomalous data using an output of a model for the data. The processor calculates a loss value related to the anomaly degree using a loss function based on an adjustment parameter based on a previously calculated loss value and the label. The processor updates a parameter of the model so as to minimize the loss value.

Abstract: According to one embodiment, a state diagnosis apparatus includes a processing circuit. The processing circuit executes a model receiving, as an input, first data relating to a state of a device at each of a plurality of stages along a time series and outputting a first numerical value quantitatively indicating the first data for each of the stages. The processing circuit determines whether or not first numerical values output from the model monotonously change along the time series.

Abstract: According to one embodiment, a condition monitoring device includes a processor. The processor is configured to acquire a time-series signal about a condition of a monitor target from a first sensor, acquire operation timing information indicating start of operation of the monitor target, detect a first operation segment signal from the time-series signal based on the operation timing information, detect a second operation segment signal from the first operation segment signal based on a waveform feature of the first operation segment signal, and determine the condition of the monitor target based on the second operation segment signal.

Abstract: According to one embodiment, a learning apparatus includes a memory and a hardware processor connected to the memory which learns a transformation function to extract a feature value of an input signal. The hardware processor updates the transformation function based on a signal indicative of a first condition and a signal indicative of a second condition which is different from the first condition, using a first loss function on the signal indicative of the first condition and a second loss function on the signal indicative of the second condition. The second loss function is designed such that the second condition becomes distant from the first condition.

Abstract: According to one embodiment, a monitoring system includes a processor. The processor accepts first data output from a first detector. The first detector detects a signal caused by equipment. The processor performs a first determination when a first value is in a first state. The first value indicates a state of the first detector or an environment where the equipment is provided. The first determination determines a condition of the equipment by using a first model and the first data. The processor performs a second determination when the first value is in a second state different from the first state. The second determination determines the condition of the equipment by using a second model and the first data. The second model is different from the first model.

Abstract: According to one embodiment, an electronic apparatus detects an abnormality of at least one of a first fan for a first device in a first housing and a second fan for a second device in a second housing, and includes a receiver and circuitry. The receiver receives a first signal of a first sound collected by a first microphone and a second signal of a second sound collected by a second microphone. The first sound includes a sound produced by a shaft or a bearing of the first fan. The second sound includes a sound produced by a shaft or a bearing of the second fan. The circuitry detects an abnormality of one of the first and second fans by at least using the first sound and the second sound included in the first and second signals.