An electronic device includes a first housing, a second housing connected to at least a portion of the first housing and movable with respect to the first housing, at least one display coupled with at least one of the first housing or the second housing, at least one microphone, at least one sensor and at least one processor. The at least one processor is configured to: obtain first audio data using the at least one microphone; identify that a form of the electronic device is changed according to relative movement of the first housing and the second housing, using the at least one sensor while the first audio data is obtained, identify noise data based on identifying that the form of the electronic device is changed, and obtain second audio data from the first audio data based on the identified noise data. The second audio data may include data in which at least a portion of noise, which is generated based on a change of the form of the electronic device and included in the first audio data, is reduced.

An electronic device includes a first housing, a second housing connected to at least a portion of the first housing and movable with respect to the first housing, at least one display coupled with at least one of the first housing or the second housing, at least one microphone, at least one sensor and at least one processor. The at least one processor is configured to: obtain first audio data using the at least one microphone; identify that a form of the electronic device is changed according to relative movement of the first housing and the second housing, using the at least one sensor while the first audio data is obtained, identify noise data based on identifying that the form of the electronic device is changed, and obtain second audio data from the first audio data based on the identified noise data. The second audio data may include data in which at least a portion of noise, which is generated based on a change of the form of the electronic device and included in the first audio data, is reduced.

A road surface state determination device includes a tire-side device and a vehicle-body-side system. The tire-side device is attached to a back surface of a tread of each of a plurality of tires included in a vehicle. The vehicle-body-side system is included in a body of the vehicle. The tire-side device outputs a detection signal corresponding to a magnitude of vibration applied to the tire. The tire-side device generates road surface data indicative of a road surface state appearing in a waveform of the detection signal. The tire-side device transmits the road surface data. The vehicle-body-side system performs bidirectional communication with the tire-side device and receives the road surface data. The vehicle-body-side system determines the road surface state of a road surface on which the vehicle is traveling based on the road surface data.

A road surface state determination device includes a tire-side device and a vehicle-body-side system. The tire-side device is attached to a back surface of a tread of each of a plurality of tires included in a vehicle. The vehicle-body-side system is included in a body of the vehicle. The tire-side device outputs a detection signal corresponding to a magnitude of vibration applied to the tire. The tire-side device generates road surface data indicative of a road surface state appearing in a waveform of the detection signal. The tire-side device transmits the road surface data. The vehicle-body-side system performs bidirectional communication with the tire-side device and receives the road surface data. The vehicle-body-side system determines the road surface state of a road surface on which the vehicle is traveling based on the road surface data.

A detection device (100) for detecting damage to a conduit (300) buried in ground includes: a sensor (10) for detecting breaking sound at the time of conduit damage; a processing unit (20) for determining a relation of magnitude between a characteristic value of the breaking sound and a threshold; and an indication unit (30) for indicating that the conduit is damaged when the relation of magnitude satisfies a predetermined condition.

The present disclosure discloses a dynamic identification method of bridge scour based on health monitoring data, including: collecting an acceleration-time curve of a bridge foundation structure when vibrating: collecting the acceleration-time curve of each bridge foundation structure in a scour state by a health monitoring system when each bridge foundation structure vibrates; obtaining a warning control threshold of abnormal warning of a time-frequency change of a first-time scour bridge evaluation reference mode by calculation; identifying an abnormal segment in frequency segments of a scoured bridge to be identified; identifying an abnormal time-frequency sequence in the time-frequency abnormal segment: updating a warning control threshold of its own random fluctuation of time-frequency characteristics of a bridge scour reference mode after completing scour early warning of the abnormal sequence, so as to prepare for next anomaly identification and scour early warning. The present disclosure provides a method for dynamically identifying a foundation scour depth by performing dynamic characteristic analysis of a structural system, and the identification method can realize the technical features of long-term dynamic scour monitoring and early warning of underwater foundations.

The present disclosure discloses a dynamic identification method of bridge scour based on health monitoring data, including: collecting an acceleration-time curve of a bridge foundation structure when vibrating: collecting the acceleration-time curve of each bridge foundation structure in a scour state by a health monitoring system when each bridge foundation structure vibrates; obtaining a warning control threshold of abnormal warning of a time-frequency change of a first-time scour bridge evaluation reference mode by calculation; identifying an abnormal segment in frequency segments of a scoured bridge to be identified; identifying an abnormal time-frequency sequence in the time-frequency abnormal segment: updating a warning control threshold of its own random fluctuation of time-frequency characteristics of a bridge scour reference mode after completing scour early warning of the abnormal sequence, so as to prepare for next anomaly identification and scour early warning. The present disclosure provides a method for dynamically identifying a foundation scour depth by performing dynamic characteristic analysis of a structural system, and the identification method can realize the technical features of long-term dynamic scour monitoring and early warning of underwater foundations.

An abnormality predicting system includes a processor and a memory having instructions. The instructions, when executed by the at least one processor, cause the at least one processor to execute operations including: inputting processing target data acquired from a target device; storing information related to an abnormality prediction of the processing target data; calculating an abnormality degree of the processing target data; executing processing related to the abnormality prediction including a failure occurrence prediction using a latest abnormality degree transition and a past abnormality degree transition of the processing target data; and generating a display screen for displaying a processing result including an abnormality degree transition and a result of the failure occurrence prediction.

An abnormality predicting system includes a processor and a memory having instructions. The instructions, when executed by the at least one processor, cause the at least one processor to execute operations including: inputting processing target data acquired from a target device; storing information related to an abnormality prediction of the processing target data; calculating an abnormality degree of the processing target data; executing processing related to the abnormality prediction including a failure occurrence prediction using a latest abnormality degree transition and a past abnormality degree transition of the processing target data; and generating a display screen for displaying a processing result including an abnormality degree transition and a result of the failure occurrence prediction.

The present disclosure relates to a thermal-acoustic-vibration three-parameter integrated in-situ sensor and system with a high-temperature-resistant and high-pressure-resistant structure. The provided thermal-acoustic-vibration three-parameter integrated in-situ sensor with a high-temperature-resistant and high-pressure-resistant structure comprises a heat detection device, a sound detection device and a vibration detection device; and the sound detection device and the vibration detection device are distributed on two sides of the heat detection device. When heat, sound and vibration need to be detected, only spectra of light signals emitted by the heat detection device, the sound detection device and the vibration detection device need to be obtained, and heat information, sound information and vibration information to be detected are obtained through the corresponding relation between the spectra of the optical signals emitted by the heat detection device, the sound detection device and the vibration detection device and heat information, sound information and vibration information to be detected.