Abstract: Provided is a machine state detecting device capable of easily detecting the state of a machine, regardless of whether an unknown operation that is not expected to cause damage is performed. A state detecting device 100 includes a collection device 1a that collects, at a plurality of times, state information if indicating the state of the machine that changes chronologically, and an arithmetic processing device 1b that processes a plurality of pieces of the state information if collected at the plurality of times to detect the state of the machine.

Abstract: Provided is a machine state detecting device capable of easily detecting the state of a machine, regardless of whether an unknown operation that is not expected to cause damage is performed. A state detecting device 100 includes a collection device 1a that collects, at a plurality of times, state information if indicating the state of the machine that changes chronologically, and an arithmetic processing device 1b that processes a plurality of pieces of the state information if collected at the plurality of times to detect the state of the machine.

Abstract: An action recognition system includes a controller that computes, in a time division manner, a plurality of feature vectors using as feature quantities information of a machine with respect to running that varies in a time sequence, generates a classification model by classifying the feature vectors into a plurality of clusters and allocating identification IDs to the clusters, generates an ID pattern model by allocating the identification IDs to the feature vectors computed in the time division manner on the basis of the classification model and associating a pattern of the identification IDs that vary in a time sequence according to a predetermined action of the machine with identification information of the predetermined action, generates output information for recognizing the predetermined action on the basis of changes in the identification IDs in the time sequence and the ID pattern model, and controls the display device to output the output information.

Abstract: The abnormality diagnosis system detects a failure sign of a device to be diagnosed. The abnormality diagnosis system includes: a diagnosis process search unit which searches for a suitable diagnosis processing procedure by comparing a plurality of diagnosis processing procedures, and outputs reconfiguration information corresponding to the suitable diagnosis processing procedure; and a diagnosis processing unit which has a reconfigurable processing unit and which uses the suitable diagnosis processing procedure found by the diagnosis process search unit to detect a failure sign of the device to be diagnosed by reconfiguring the processing unit on the basis of the reconfiguration information.

Abstract: A failure diagnosis system flexibly responds to a change in a diagnosis target by using a difference in measurement data before and after maintenance in predictive failure diagnosis. A pre-maintenance data DB stores measurement data before maintenance, and a post-maintenance data DB stores measurement data after maintenance. A feature detection algorithm group DB is provided where a plurality of feature detection algorithms are stored. A first feature is detected based on the measurement data by using each of the plurality of feature detection algorithms read from the feature detection algorithm group DB. An algorithm search unit selects one of the plurality of algorithms based on the feature thus detected. A second feature is detected from the measurement data by using the feature detection algorithm, and a sign predictive of failure of diagnosis of target equipment is diagnosed using the detected second feature.

Abstract: A diagnostic apparatus determines, at a reference time, whether a device is normal or abnormal, and in which operation state the device is at the time. A reference data creation unit repeats a process of storing sensor values acquired from the device while changing the operation state at the reference time in association with each of the determined operation states until there is no non-corresponding operation state with which the acquired sensor value is not yet associated. At a diagnosis time at which it is not known whether the device is normal or abnormal, an operation state and a sensor value of the device at the time is acquired. The stored sensor value associated with the acquired operation state is read to compare the sensor value acquired at the diagnosis time with the read sensor value to display a result of determination on whether the device is normal or abnormal.

Abstract: A rotary machine diagnostic device has a current acquisition unit that acquires current from a sensor, which measures the driving current of a rotary machine driving a machine to be driven; a sampling unit that performs sampling of the acquired driving current; a frequency range conversion unit that converts data concerning the time range subjected to sampling into a frequency range; a sideband detection unit that sets the driving current as a carrier wave in the frequency range, and detects, as a sideband, the spectrum appearing on each side of the carrier wave subjected to amplitude modulation; and an abnormality detection unit that detects whether or not there are abnormalities in the rotary machine and the machine to be driven on the basis of the difference in frequency between the sideband frequency detected by the sideband detection unit and the frequency of the carrier wave.

Abstract: Provided are a feature amount extraction device, a failure sign diagnosis device, a design assistance device, and a failure sign diagnosis operation method which are suitable for predictively diagnosing equipment failure.

Abstract: Provided is an equipment life diagnostic device which assists in estimating operating conditions that are factors in determining the remaining life of equipment. This equipment life diagnostic device is provided with: an actual life consumption calculation unit which calculates the actual life consumption of equipment when the equipment is operating; an assumed life consumption setting unit which sets an assumed life consumption on the basis of the useful life of the equipment; a comparison unit which compares the actual life consumption calculated by the actual life consumption calculation unit with the assumed life consumption set by the assumed life consumption setting unit; and an output unit which, on the basis of the comparison result obtained from the comparison unit, displays information relating to the amount by which the actual life consumption is greater or less than the assumed life consumption.

Abstract: To associate condition information, such as (a) a location in a movement section at which fatigue occurred, (b) a type of work or operation during which fatigue occurred, and (c) a type of natural phenomenon experienced when fatigue occurred, a device for displaying the material fatigue of a machine is configured to observe stress variation in a time series using a sensor correlated with the stress variation or stress of a machine. Stress variation in a single cycle and the time when the stress variation occurred are detected, and the stress variation value and time of occurrence are output and displayed.

Abstract: A failure diagnosis system flexibly responds to a change in a diagnosis target by using a difference in measurement data before and after maintenance in predictive failure diagnosis. A pre-maintenance data DB stores measurement data before maintenance, and a post-maintenance data DB stores measurement data after maintenance. A feature detection algorithm group DB is provided where a plurality of feature detection algorithms are stored. A first feature is detected based on the measurement data by using each of the plurality of feature detection algorithms read from the feature detection algorithm group DB. An algorithm search unit selects one of the plurality of algorithms based on the feature thus detected. A second feature is detected from the measurement data by using the feature detection algorithm, and a sign predictive of failure of diagnosis of target equipment is diagnosed using the detected second feature.

Abstract: The abnormality diagnosis system detects a failure sign of a device to be diagnosed. The abnormality diagnosis system includes: a diagnosis process search unit which searches for a suitable diagnosis processing procedure by comparing a plurality of diagnosis processing procedures, and outputs reconfiguration information corresponding to the suitable diagnosis processing procedure; and a diagnosis processing unit which has a reconfigurable processing unit and which uses the suitable diagnosis processing procedure found by the diagnosis process search unit to detect a failure sign of the device to be diagnosed by reconfiguring the processing unit on the basis of the reconfiguration information.

Abstract: According to the present invention, the work status at an actual site is represented using a combination of component statuses. A degree of damage that takes into account the manner of use at the actual site is predicted by associating test data collected in a component status test. The objective of the present invention is to estimate, with high accuracy, the degree of damage to a device operating in an actual environment.

Abstract: An analysis device for time series data from an apparatus to be diagnosed is provided with an accumulation device which accumulates sensor data, operation data, or control data, obtained from the apparatus, while accumulating time information, an algorithm accumulation unit which accumulates algorithms for recognizing behavior of the apparatus, a behavior recognition unit which recognizes behavior of the apparatus by using a recognition algorithm, and a specification unit which specifies a behavioral item to be recognized. A behavior recognition algorithm corresponding to the specified behavioral item is selected from the algorithm accumulation unit; sensor data, operation data, or control data is selected from the accumulation device; start and end times of a selected behavior are recognized by the behavior recognition unit; and the recognized start and end times are associated with time information about data accumulated in the accumulation device.

Abstract: A diagnostic apparatus determines, at a reference time, whether a device is normal or abnormal, and in which operation state the device is at the time. A reference data creation unit repeats a process of storing sensor values acquired from the device while changing the operation state at the reference time in association with each of the determined operation states until there is no non-corresponding operation state with which the acquired sensor value is not yet associated. At a diagnosis time at which it is not known whether the device is normal or abnormal, an operation state and a sensor value of the device at the time is acquired. The stored sensor value associated with the acquired operation state is read to compare the sensor value acquired at the diagnosis time with the read sensor value to display a result of determination on whether the device is normal or abnormal.

Abstract: A degradation cause estimation device is provided with a degradation detector for detecting the amount of degradation undergone by a device, a state observation device for detecting observation values for internal portions, values observed from outside, or device control and operation information, a degradation section detector for detecting a section undergoing degradation using the output values of the degradation detector, and a cause estimator for estimating the cause of the degradation using the device state observations for the degradation section, and outputs the cause for the degradation section.

Abstract: The maintenance management device 3 includes an error status diagnosis unit 11, a grace period estimation unit 14, a maintenance cost estimation unit 15, and a screen display unit 17. When the error status diagnosis unit 11 has diagnosed the occurrence of an anomaly, the grace period estimation unit 14 estimates a first grace period leading up to the occurrence of a failure. The maintenance cost estimation unit 15 estimates the cost of corrective maintenance incurred when the failure occurs after the elapse of the first grace period. The screen display unit 17 displays a combination of the first grace period and the cost of corrective maintenance. Alternatively, the grace period estimation unit 14 estimates a second grace period over which preventive maintenance may be postponed without a failure.

Abstract: A rotary machine diagnostic device has a current acquisition unit that acquires current from a sensor, which measures the driving current of a rotary machine driving a machine to be driven; a sampling unit that performs sampling of the acquired driving current; a frequency range conversion unit that converts data concerning the time range subjected to sampling into a frequency range; a sideband detection unit that sets the driving current as a carrier wave in the frequency range, and detects, as a sideband, the spectrum appearing on each side of the carrier wave subjected to amplitude modulation; and an abnormality detection unit that detects whether or not there are abnormalities in the rotary machine and the machine to be driven on the basis of the difference in frequency between the sideband frequency detected by the sideband detection unit and the frequency of the carrier wave.

Abstract: In industrial machine abnormality diagnosis, if the machine is diagnosed to have abnormality, then sensor data from the machine needs to be sent to a management center for causal analysis. However, since machines operated at a remote site cannot always communicate with a management center, it has been found that, in some cases, sensor data that has failed to be sent from a machine remains in the memory of the machine, resulting in lack of available memory capacity. In view of this, the present invention determines beforehand whether the diagnosed machine will run out of available memory capacity before the completion of sending the amount of sensor data required for causal analysis for the machine, and instructs a maintenance person to recover memory.

Abstract: Provided is an equipment life diagnostic device which assists in estimating operating conditions that are factors in determining the remaining life of equipment. This equipment life diagnostic device is provided with: an actual life consumption calculation unit which calculates the actual life consumption of equipment when the equipment is operating; an assumed life consumption setting unit which sets an assumed life consumption on the basis of the useful life of the equipment; a comparison unit which compares the actual life consumption calculated by the actual life consumption calculation unit with the assumed life consumption set by the assumed life consumption setting unit; and an output unit which, on the basis of the comparison result obtained from the comparison unit, displays information relating to the amount by which the actual life consumption is greater or less than the assumed life consumption.