This invention provides a non-invasive method for diagnosing performance of a vehicle. The method comprises using a 3-axis accelerometer to perform diagnosis of the performance of an internal combustion engine, the performance of the engine including an engine power loss and one or more flaws associated with the engine mount. The method is also usable for diagnosing deterioration of a suspension system of said vehicle. An apparatus comprising a 3-axis accelerometer for diagnosing performance of a vehicle is also provided. In one embodiment, the 3-axis accelerometer is embedded in a smart phone.

This invention provides a non-invasive method for diagnosing performance of a vehicle. The method comprises using a 3-axis accelerometer to perform diagnosis of the performance of an internal combustion engine, the performance of the engine including an engine power loss and one or more flaws associated with the engine mount. The method is also usable for diagnosing deterioration of a suspension system of said vehicle. An apparatus comprising a 3-axis accelerometer for diagnosing performance of a vehicle is also provided. In one embodiment, the 3-axis accelerometer is embedded in a smart phone.

Methods and systems are provided for detecting cylinder misfire in a vehicle engine via a plurality of sensors, based on dual mass flywheel (DMF) operating frequency. In response to detection of a misfire event, the misfiring cylinders may be deactivated and upon confirmation of DMF operation out of a resonant frequency range, the deactivated cylinder(s) may be sequentially reactivated.

Methods and systems are provided for detecting cylinder misfire in a vehicle engine via a plurality of sensors, based on dual mass flywheel (DMF) operating frequency. In response to detection of a misfire event, the misfiring cylinders may be deactivated and upon confirmation of DMF operation out of a resonant frequency range, the deactivated cylinder(s) may be sequentially reactivated.

Various embodiments include a fault diagnosis method for a rotating motor. The method may include: obtaining a time-domain acceleration signal of the rotating motor along a vibration direction and a rotation period of the rotating motor; converting the time-domain acceleration signal into a time-domain velocity signal, cutting off a plurality of velocity signal segments along the time-domain velocity signal by taking the rotation period as a step size, and arranging the plurality of velocity signal segments in sequence to obtain a velocity signal matrix; converting the velocity signal matrix into an image; and inputting the image into a trained neural network model to obtain a fault diagnosis result.

A sampling device receives, from a transducer computing device located within a predefined proximity to an equipment in an operating environment, a vibration sample from the operating environment. The sampling device predicts, using a model, (1) an anomalous designation or a non-anomalous designation for the vibration sample and (2) a cluster assignment, to a particular cluster of a set of clusters, for the vibration sample when the model predicts the non-anomalous designation for the vibration sample. The sampling device transmits, to a computing device of the equipment, instructions to cease to perform the operation responsive to predicting the anomalous designation.

A motor noise detecting device according to an embodiment of the present disclosure includes a signal sensing part for sensing an acoustic signal generated from an object to be tested, a data acquisition part for receiving the acoustic signal sensed by the signal sensing part and converting it into an acoustic digital signal, and a data analysis part for receiving and analyzing the acoustic digital signal to perform a detection on whether the object to be tested is abnormal. In addition, the signal sensing part includes an AE (Acoustic Emission) sensor for sensing an elastic wave included in the acoustic signal, and the data analysis part generates result data of analyzing the acoustic digital signal, analyzes the generated result data through a pre-learned model, and detects whether the object to be tested is abnormal.

A motor noise detecting device according to an embodiment of the present disclosure includes a signal sensing part for sensing an acoustic signal generated from an object to be tested, a data acquisition part for receiving the acoustic signal sensed by the signal sensing part and converting it into an acoustic digital signal, and a data analysis part for receiving and analyzing the acoustic digital signal to perform a detection on whether the object to be tested is abnormal. In addition, the signal sensing part includes an AE (Acoustic Emission) sensor for sensing an elastic wave included in the acoustic signal, and the data analysis part generates result data of analyzing the acoustic digital signal, analyzes the generated result data through a pre-learned model, and detects whether the object to be tested is abnormal.

An object of the present invention is to provide a technology that enables an abnormal combustion detection apparatus for a spark ignition internal combustion engine having a plurality of cylinders to detect abnormal combustion such as pre-ignition and knocking with improved accuracy. To achieve the object, according to the present invention, in an abnormal combustion detection apparatus for a spark-ignition internal combustion engine that determines or detects the occurrence of abnormal combustion by comparing a vibration intensity obtained from a measurement signal of a knock sensor and a determination threshold, when the occurrence of abnormal combustion is detected, the apparatus corrects a determination threshold for the next cylinder using as parameters the peak value of the vibration intensity at the time of the occurrence of abnormal combustion and the engine speed.

An object of the present invention is to provide a technology that enables an abnormal combustion detection apparatus for a spark ignition internal combustion engine having a plurality of cylinders to detect abnormal combustion such as pre-ignition and knocking with improved accuracy. To achieve the object, according to the present invention, in an abnormal combustion detection apparatus for a spark-ignition internal combustion engine that determines or detects the occurrence of abnormal combustion by comparing a vibration intensity obtained from a measurement signal of a knock sensor and a determination threshold, when the occurrence of abnormal combustion is detected, the apparatus corrects a determination threshold for the next cylinder using as parameters the peak value of the vibration intensity at the time of the occurrence of abnormal combustion and the engine speed.