Abstract: Provided an apparatus configured to calculate a periodicity of time series data, generate a plurality of subsequences, from the time series data, a length of each subsequence set to the periodicity, calculate feature values of the plurality of subsequences; categorize the plurality of subsequences, based on the feature values thereof, into one or more groups, find a periodicity of the subsequences belonging in common to one group, based on an occurrence order of the subsequences belonging in common to the one group and perform missing event detection by identifying the subsequence, occurrence of which is expected according to the periodicity of the subsequences belonging in common to the one group, but not found.

Abstract: Provided an apparatus that receives time series data from a data storage unit storing time series of sample data or feature values calculated from the sample data, computes a measure indicating change and repetition characteristics of the time series data, based on sample value distribution thereof, selects a state model structure to be used for model learning and estimation, from state models including a fully connected state model and a one way direction state model, based on the measure and stores the selected state model in a model storage unit.

Abstract: A feature transformation apparatus includes at least a combination storage part that stores a combination with respect to a set of features, wherein data is approximately represented as a sum of the combination of the features; and a transformation part that transforms at least the combination so as not to change the sum of the combination of the set of features.

Abstract: There are provided a repair determination section that determines, based on failure information on the facility for manufacturing a product, a repair time required to repair the facility, and a recovery plan creation section that creates a recovery plan in accordance with a predetermined production evaluation indicator, based on the repair time and production information on a line with the failed facility, one or more other facilities, and on one or more other lines.

Abstract: A state estimation apparatus is configured to extract a time interval to be analyzed from a time series of a first signal based on a second signal acquired in conjunction with the first signal relating to the operation of the facility, and estimate a change in a state of the facility based on waveform data of the time interval of the first signal.

Abstract: An anomaly determination apparatus, an anomaly determination method, and a program, capable of easily determining whether or not an anomaly has occurred are provided. An anomaly determination apparatus (1) includes a transformation unit (2) and an anomaly determination unit (3). The transformation unit (2) performs a transformation process using a transform function for transforming an anomaly level of a signal into a probability variable value, the probability variable value being a variable value in accordance with a predetermined probability distribution. Note that the transform function is a monotone function. The anomaly determination unit (3) determines presence/absence of an anomaly of a sample of the anomaly level by using a result of the transformation by the transformation unit (2).

Abstract: Provided a method including applying a Fourier Transform to an AC current waveform measured to perform conversion thereof to a frequency domain; adjusting entire phase components of frequency spectra obtained as a result of the Fourier Transform, such that a phase component of an AC power supply frequency becomes zero; and applying an inverse Fourier Transform to the frequency spectra with the entire phase components thereof adjusted to obtain a current waveform in a time domain.

Abstract: A measurement apparatus that measures a facility of a measurement target and that is able to transmit measurement data as intermittent data and an analysis apparatus. An analysis apparatus includes: a communication part that receives the intermittent data from the measurement apparatus; and an analysis part that estimates a standard data pattern serving as a reference, based on a common portion between a pair of the data in a set of the intermittent data received and determines presence of an anomaly for intermittent data of a determination target received from the measurement apparatus by referring to the standard data pattern.

Abstract: A maintenance monitoring apparatus includes: a maintenance management part that manages, based on a monitoring result of a current or power of a vending machine that provides a beverage by extracting the beverage from a raw material, whether an operation performed on the vending machine is a predetermined maintenance operation and whether the maintenance has been executed at an appropriate time interval and as many times as necessary; and a notification part that notifies that a maintenance has been executed or not.

Abstract: A state change feature value relating to power supply current waveform data is extracted, and a transition state is detected, for a section of the waveform data, based on a magnitude of a state change feature value extracted.

Abstract: An anomaly detection apparatus estimates time series data of a first signal of each appliance by disaggregating an aggregate signal that is a sum of first signals of a plurality of appliances into each first signal of an individual appliance, calculates a residual by subtracting sum of the estimated first signals of the plurality of appliances from the aggregate signal, and obtains value of the second signal at a time point at which the residual indicates presence of anomaly, and checks if there is match of pair of value of the estimated first signal and estimated state of the appliance, with any one of the one or more pairs of value of the first signal and state of the appliance, stored in a table, in association with the value of the second signal at the time point at which the residual indicates presence of anomaly to identify appliance with anomaly.

Abstract: Provided an apparatus configured to calculate a periodicity of the time series data using at least one of a periodogram of the time series data and an autocorrelation of the time series data; generate a plurality of subsequences from the time series data, a length of each subsequence set to the periodicity, calculate feature values of the plurality of subsequences, and categorize the plurality of subsequences, based on the features values thereof, into one or more groups; and execute analysis of the time series data, based on the categorization result.

Abstract: Provided an apparatus configured to calculate a periodicity of time series data, generate a plurality of subsequences, from the time series data, a length of each subsequence set to the periodicity, calculate feature values of the plurality of subsequences; categorize the plurality of subsequences, based on the feature values thereof, into one or more groups, find a periodicity of the subsequences belonging in common to one group, based on an occurrence order of the subsequences belonging in common to the one group and perform missing event detection by identifying the subsequence, occurrence of which is expected according to the periodicity of the subsequences belonging in common to the one group, but not found.

Abstract: Provided a method including applying a Fourier Transform to an AC current waveform measured to perform conversion thereof to a frequency domain; adjusting entire phase components of frequency spectra obtained as a result of the Fourier Transform, such that a phase component of an AC power supply frequency becomes zero; and applying an inverse Fourier Transform to the frequency spectra with the entire phase components thereof adjusted to obtain a current waveform in a time domain.

Abstract: A maintenance plan formulation device includes: a failure sign detection unit that acquires a state of at least an apparatus and detects an abnormality indicating a sign that appears before a failure of the apparatus occurs; a maintenance limit timing calculation unit that calculates a maintenance limit timing that indicates a limit of a maintenance timing of the apparatus with the abnormality thereof being detected; a maintenance timing calculation unit that calculates a maintenance timing of the apparatus based on the maintenance limit timing of the apparatus; and a maintenance timing output part that outputs the maintenance timing to a display apparatus.

Abstract: An anomaly detection apparatus estimates time series data of a first signal of each appliance by disaggregating an aggregate signal that is a sum of first signals of a plurality of appliances into each first signal of an individual appliance, calculates a residual by subtracting sum of the estimated first signals of the plurality of appliances from the aggregate signal, and obtains value of the second signal at a time point at which the residual indicates presence of anomaly, and checks if there is match of pair of value of the estimated first signal and estimated state of the appliance, with any one of the one or more pairs of value of the first signal and state of the appliance, stored in a table, in association with the value of the second signal at the time point at which the residual indicates presence of anomaly to identify appliance with anomaly.

Abstract: Provided an apparatus that receives time series data from a data storage unit storing time series of sample data or feature values calculated from the sample data, computes a measure indicating change and repetition characteristics of the time series data, based on sample value distribution thereof, selects a state model structure to be used for model learning and estimation, from state models including a fully connected state model and a one way direction state model, based on the measure and stores the selected state model in a model storage unit.

Abstract: A maintenance monitoring apparatus includes: a maintenance management part that manages, based on a monitoring result of a current or power of a vending machine that provides a beverage by extracting the beverage from a raw material, whether an operation performed on the vending machine is a predetermined maintenance operation and whether the maintenance has been executed at an appropriate time interval and as many times as necessary; and a notification part that notifies that a maintenance has been executed or not.

Abstract: A determination part of the data storage apparatus performs control such that when at least a part of a first data block stored in a first storage part satisfies a first criterion, the first data block and a predetermined number of data blocks after the first data block in the first storage part are forwarded to the second storage part for storage, and when there is data that satisfies a second criterion from the first to the predetermined number data blocks, the first storage part continue to store data blocks following the data block corresponding to the predetermined number and stored in the first storage part in the second storage part, while when there is no data that satisfies the predetermined second criterion, the first storage part is caused to stop storing a data block stored in the first storage part in the second storage part.

Abstract: An anomaly determination apparatus, an anomaly determination method, and a program, capable of easily determining whether or not an anomaly has occurred are provided. An anomaly determination apparatus (1) includes a transformation unit (2) and an anomaly determination unit (3). The transformation unit (2) performs a transformation process using a transform function for transforming an anomaly level of a signal into a probability variable value, the probability variable value being a variable value in accordance with a predetermined probability distribution. Note that the transform function is a monotone function. The anomaly determination unit (3) determines presence/absence of an anomaly of a sample of the anomaly level by using a result of the transformation by the transformation unit (2).