Nissan Motor Company Limited

Nikon Corporation

Isuzu Motors Limited

Ebara Corporation

Other

Nissan North America, Inc.

Nippon Valqua Industries, Ltd.

Renault S.a.s.

Toru Takagi

Susumu Fujita

Satoru Hirose

Mamoru Nakasuji

Nobuharu Noji

Tohru Satake

Shoji Yoshikawa

Toshifumi Kimba

Tsutomu Karimata

Hirosi Sobukawa

Muneki Hamashima

Shin Oowada

Koichi Kuroda

Mutsumi Saito

Akihiro Goto

Ryoji Ando

Takeshi Murakami

Kinya Kato

Yoshiyuki Watanabe

Kazuya Okamoto

Yasuhiro Tanaka

Shigeru Matsumoto

Satoshi Chinomi

Kenji Watanabe

Seiichi Kobayashi

Masayasu Suzuki

Wataru Funamizu

Toshiro Muramatsu

Satoshi Nakayama

Norimasa Kishi

Hiroshi Ohki

Masahiro Juen

Atsushi Komai

Okihiko Nakayama

Vikram Krishnamurthy

Shigeru Aoki

Hiroshi Nishimura

Takuo Ishiwaka

Naoto Kihara

Keishi Hayashi

Takashi Seo

Yoshio Iwasaki

Shutaro Kato

Hiroto Wakasugi

Masao Yamane

Toshimichi Urakawa

Junji Ikeda

Sota Nakanishi

Akihiro Sugita

Takahiro Uematsu

Masaki Kuno

Tadashi Narui

Naoki Honda

Takanori Kojima

Satoru Odate

Osamu Saruwatari

Tomohisa Ishida

Minoru Tomikashi

Atsushi Kamashita

Yojiro Tezuka

Fumio Seto

Naoki Ohkouchi

Toshiyuki Shimizu

Kouichi Oomori

Yuki Horihata

Mitsumi Saito

Yohei Matsuoka

Toshirou Muramatsu

Nobuhisa Hirayama

Umeo Kawanishi

Takeshi Hamabe

Susumu Rikohaitsu 3-Gokan 302 Fujita

Vehicle data is acquired, and is linked with each vehicle component, first degree of abnormality is determined for each vehicle component. When detecting collision, vehicle data is acquired during self-travelling after the collision. If vehicle is not capable of self-travelling, by referring to post-collision vehicle data etc., second degree of abnormality after the collision is calculated. The first and second degrees of abnormality are compared, if the second degree of abnormality is greater than the first degree of abnormality by a predetermined value or more, vehicle component is identified as vehicle component which is outside an impact area, but has been affected in terms of deterioration etc., and necessary information is displayed. When there is an intentional driving characteristic change after the collision, vehicle component is not identified as vehicle component having been affected in terms of deterioration etc.

Vehicle data analysis method and device

An image sensor element includes: a first pixel having a first photoelectric conversion part, a first accumulation part which accumulates electric charge generated by the first photoelectric conversion part, and a first output part based on a voltage of the first accumulation part; a second pixel having a second photoelectric conversion part, a second accumulation part wherein electric charge generated by the second photoelectric conversion part, and a second output part which a second signal based on a voltage of the second accumulation part; an output line to which the first and the second output parts are connected and from which the first and second signals are output; and a control unit which is able to control the voltage of the first accumulation part to be a first voltage and ability to control the voltage of the second accumulation part to be a second voltage different from the first voltage.

Image sensor element and imaging device

An image processing apparatus includes a controller. The controller calculates a fundamental frequency component included in sound data and a harmonic component corresponding to the fundamental frequency component, converts the fundamental frequency component and the harmonic component into image data, and generates a sound image where the fundamental frequency component and the harmonic component converted into the image data are arranged adjacent each other.

Image processing apparatus and image processing method for generating a sound image

A malfunction detection device compares detected data on a condition at a predetermined part of an apparatus with a threshold so as to determine a malfunction of the apparatus. The malfunction detection device varies the threshold in accordance with a type of a lubricant used for movable parts of the apparatus.

Malfunction detection device and malfunction detection method

A driving force sensor detects a driving force in a rotating mechanism provided in an apparatus. A vibration sensor detects vibrations of the apparatus. A control unit determines a type of a malfunction of the apparatus in accordance with a combination of the detected driving force and the detected vibrations.

Malfunction-type determination device and malfunction-type determination method

An abnormality determination apparatus of the present invention acquires state data from work equipment provided with an attaching part to which a plural kinds of work parts are attached in a replaceable manner, identifies the kind of a work part attached to the attaching part, sets, corresponding to the identified kind of the work part, abnormality determination data for determining an abnormality of the work equipment, acquires, from among state data acquired from the work equipment, state data of a time when the identified kind of the work part was being attached, and compares the acquired state data with the set abnormality determination data to determine an abnormality of the work equipment.

Abnormality determination apparatus, abnormality determination system, and abnormality determination method

An image sensor includes: a first photoelectric conversion unit that photoelectrically converts light to generate an electric charge; a first output unit that outputs a first signal based on the electric charge generated by the first photoelectric conversion unit; a plurality of second photoelectric conversion units that photoelectrically convert light to generate electric charges; a plurality of second output units that output second signals based on the electric charges generated by the second photoelectric conversion units; an output line to which the first output unit and the plurality of second output units are connected, and from which at least one of the first signal and the second signals is output; a first control line for controlling the output of the first signal from the first output unit; and second control lines for controlling the outputs of the second signals from the plurality of second output units.

Image sensor and image-capturing device having pixels for focus detection and pixels for image generation

An abnormality detection apparatus detects an abnormality of equipment according to sensor data that is related to a vibration of the equipment and is obtained while a brake device for braking a motion of a movable part of the equipment is in operation.

Abnormality detection apparatus and abnormality detection method

An abnormality detection device of detecting an abnormality of a robot which executes an operation such as welding on a target object, includes a control unit including a signal input unit to which a detection signal is input, the detection signal being obtained when a state of the robot is detected by a sensor, so that the control unit detects an abnormality of the robot in accordance with the detection signal. The control unit outputs a control signal to the robot so as to execute an integrated action in which a necessary action necessary for detecting an abnormality is added to a predetermined action in which the operation is not executed on the target object. The control unit detects the abnormality of the robot in accordance with the detection signal detected when the integrated action is executed.

Abnormality detection device and abnormality detection method

A control unit causes a sensor to start sampling at a plurality of start timings different from each other. The control unit combines sampling signals obtained by the start of the sampling at the different start timings, and detects a malfunction of an apparatus in accordance with the combined sampling signal.

Systems and methods for predicting component failure in a vehicle and alerting a driver based thereon. In an embodiment, the method includes receiving sensor data from at least one vehicle sensor over a period of time, processing the sensor data using a predictive model to detect an anomaly indicative of an upcoming component failure, determining a severity of the upcoming component failure based on at least one operating characteristic of the vehicle, and providing an alert to the driver of the vehicle regarding the severity of the upcoming component failure.

System and method for predicting vehicle component failure and providing a customized alert to the driver

A first circuit layer including a first semiconductor substrate with photoelectric conversion unit that photoelectrically converts incident light and generates charge, and a first wiring layer with wiring that reads out signal based upon charge generated by the photoelectric conversion unit; second circuit layer including a second wiring layer with wiring connected to the wiring of the first wiring layer, and a second semiconductor substrate with a through electrode connected to the wiring of the second wiring layer; third circuit layer including a third semiconductor substrate with a through electrode connected to the through electrode of the second circuit layer, and third wiring layer with wiring connected to the through electrode of the third semiconductor substrate; and a fourth circuit layer including a fourth wiring layer with wiring connected to the wiring of the third wiring layer, and fourth semiconductor substrate connected to the wiring of the fourth wiring layer.

Image sensor and image capture device

A malfunction determination method for a production machine including a motor as a driving source of a rotating mechanism acquires sensor data of a sensor for detecting a condition of the production machine, determines whether the production machine has an operation stop period during which the production machine has stopped its operation for a predetermined period of time or longer in accordance with an operation history of the production machine, sets a malfunction determination suspension period for suspending a malfunction determination of the production machine when determined to have the operation stop period, in accordance with a length of the operation stop period, and determines whether the production machine has a malfunction in a period other than the malfunction determination suspension period.

Malfunction determination method and malfunction determination device

An abnormality determination device includes an input unit to which a device-condition signal output from an operating device is input, a first memory configured to store a determination algorithm for determining a predetermined abnormality of the operating device, an abnormality determination unit configured to determine the predetermined abnormality of the operating device in accordance with the device-condition signal and the determination algorithm, an output unit configured to output a determination result regarding the predetermined abnormality made by the abnormality determination unit to a user, an operation unit configured to receive an input of true-or-false information of whether the determination result is correct from the user, and an update unit configured to update the determination algorithm in accordance with the true-or-false information.

Abnormality determination device and abnormality determination method

An abnormality detecting device determines an abnormality in an apparatus by comparing data on vibration detected in the apparatus with a predetermined threshold. Moreover, the abnormality detecting device changes the threshold depending on a length of work time required for the apparatus to perform a certain work.

Abnormality detecting device and abnormality detecting method

Growing community of inventors

Fujisawa, Japan

Toru Takagi