Hitachi, Ltd.

Hitachi Metals, Ltd.

Hitachi Construction Machinery Co., Ltd.

Hitachi Advanced Systems Corporation

Munetoshi Unuma

Shinya Yuda

Junsuke Fujiwara

Hideaki Suzuki

Kozo Nakamura

Hideki Inoue

Takayuki Uchida

Takashi Saeki

Ryozo Takeuchi

Toshimi Yokota

Shiro Nonaka

Ryosuke Shigemi

Tomoaki Hiruta

Shigeru Oho

Yoshiaki Usami

Fumitaka Otsu

Ryota Arai

Kohji Maki

Tomoyuki Miyata

Katsuaki Tanaka

Norio Takeda

Kenji Araki

Hiroaki Takatsuki

Tomotoshi Ishida

Yasunori Abe

Yoshitaka Takahashi

Hiroshi Ogura

Tsuneya Kurihara

Masakatsu Saitoh

Kenichiro Kurata

Tetsuji Kato

Yasuki Kita

Akio Yajima

Kenichi Anjyo

Toshiaki Yoshinaga

Mitsuo Aihara

Yoshiko Tanaka

Masao Yanaka

Joji Nishiyama

Takeshi Horie

Teruo Nakamura

Nobuyoshi Hirowatari

Yasunori Nagaoka

Reika Kin

Shinobu Satou

So Higuchi

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.

Abnormality diagnosis system that reconfigures a diagnostic program based on an optimal diagnosis procedure found by comparing a plurality of diagnosis procedures

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.

Failure diagnosis system

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.

Diagnostic apparatus, diagnostic method, and diagnostic program

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.

Diagnostic device and diagnostic method for rotary machine

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.

Equipment life diagnostic device

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.

Method and device displaying material fatigue of machine

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. In order to achieve this objective, this damage estimation device is provided with: a component status classification processing unit that classifies the operating status of a device; a component status characteristic amount storage unit that stores a characteristic amount for classification processing by the component status classification processing unit; and a damage degree storage unit for each component status, said damage degree storage unit storing the degree of damage to various regions of a device for each component status, wherein the degree of damage is measured in advance for each component status or is calculated using a simulation. The damage estimation device is characterized by collecting sensor/control data required for device status classification, classifying component status using the component status classification processing unit, calculating the classified result and the degree of damage corresponding to said result using the damage degree storage unit for each component status, and outputting the degree of damage.

Damage estimation device

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.

Analysis method for time series data and device therefor

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.

Device degradation cause estimation method and device

The maintenance management deviceincludes an error status diagnosis unit, a grace period estimation unit, a maintenance cost estimation unit, and a screen display unit. When the error status diagnosis unithas diagnosed the occurrence of an anomaly, the grace period estimation unitestimates a first grace period leading up to the occurrence of a failure. The maintenance cost estimation unitestimates the cost of corrective maintenance incurred when the failure occurs after the elapse of the first grace period. The screen display unitdisplays a combination of the first grace period and the cost of corrective maintenance. Alternatively, the grace period estimation unitestimates a second grace period over which preventive maintenance may be postponed without a failure.

Maintenance management device for operating machinery

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. This determination as to whether the machine will run out of available memory capacity before the completion of sending the amount of sensor data required for the causal analysis for the machine, is made as follows: (1) first, the machine predicts the run-out date on which the machine will run out of memory capacity for storing sensor data generated in the machine, and sends a notification of the predicted run-out date to the management center for the machine; and (2) next, from the amount of sensor data required for the causal analysis and the reception rate of sensor data, the management center calculates the number of days required to retrieve the necessary data for the causal analysis and determines whether the management center can retrieve the data by the predicted run-out date.

Abnormality diagnosis method and device therefor

In the cabling work aiding system, the RFID reader reads the RFID attached to at least one of the terminal, its terminal block, and cable member. A cabling work terminal device is connected to the RFID reader. The device is comprised of: a data base that records a template connection diagram containing the terminal-side RFID region constituted by RFID data as to the terminal and a cable-side RFID region constituted by RFID data as to the cable member; a relating part that relates the RFID read by the RFID reader to the terminal-side RIFD region and the cable-side RIFD region defined in the template connection diagram; a terminal-cable member correspondence table preparing part that prepares a correspondence table for leading correspondence between the RFID data as to the terminal and RFID data as to cable member from correspondence between the terminal-side RIFD region and the cable-side RFID related by the RFID read by the RFID reader.

Cabling work aiding system and work aiding method

A RFID registration system is provided with a reader for reading an ID of an object to be identified by an RFID, an RFID existence position indicating the position of the RFID, and the RFID; an associating apparatus for associating the read RFID with the ID of the object to be identified by the RFID, a position information generation apparatus for obtaining the read position at the same time the position has been read, and a collation apparatus for obtaining an ID of the object to be identified by the RFID based on the read position and the RFID existence position. The RFID registration system can be avoid making the mistaken association between the RFID and the object to which the identification ID is attached.

RFID registration system and method thereof

A cable connection support apparatus has a structure in which a master apparatus and a slave apparatus are connected to both ends of a plurality of cables, and each apparatus is connected to each cable by a connecting terminal. The master apparatus and the slave apparatus are grounded. The master apparatus makes, for each connected cable, an inquiry about a position of a terminal of the slave apparatus to which the cable is connected, and inspects for inter-continuity, grounded connection, and unintentional disconnection. The connection destinations and inspection results are displayed on a display apparatus. Consequently, the connection condition for each cable wire in a cable can be confirmed.

Cable connection support apparatus and method of supporting cable connection

A behavior of a walker is detected according to combination of detection of the walking behavior on a level and an altitude variation of the walker to more accurately detect the behavior of the walker. A burned calorie can be obtained according to the type of the walking behavior. An altitude variation can be obtained more accurately by integrating altitude variation only at sections with vertical movement during walking. A stride is estimated according to the behavior of the walker in consideration of the vertical movement. Obtained position and traveling direction are used for compensating values in inertial navigation system. The behavior with and without vertical movement is used in a walker navigator and a worker observing system including a worker terminal carried by the walker for detecting the behavior of the worker and a worker observing terminal for providing the detected position and behavior of the walker.

Walker behavior detection apparatus

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Tokyo, Japan

Munetoshi Unuma