Abstract: Provided are a vibration object monitoring method and apparatus, a computer device, and a storage medium. The method includes: in response to detecting that a vibration object exists in a monitoring video picture for a target monitoring region, a vibration object region in the monitoring video picture is determined, where the vibration object region is a region where the vibration object is located in the monitoring video picture; displacement information of a key point of the vibration object in the vibration object region is recorded; vibration information of the vibration object in the monitoring video picture is determined based on the displacement information; and a vibration object monitoring result for the target monitoring region is generated according to the vibration information. The abnormal vibration monitoring can be performed on the vibration object in the target monitoring region in time according to this method.

Abstract: Provided are a vibration object monitoring method and apparatus, a computer device, and a storage medium. The method includes: in response to detecting that a vibration object exists in a monitoring video picture for a target monitoring region, a vibration object region in the monitoring video picture is determined, where the vibration object region is a region where the vibration object is located in the monitoring video picture; displacement information of a key point of the vibration object in the vibration object region is recorded; vibration information of the vibration object in the monitoring video picture is determined based on the displacement information; and a vibration object monitoring result for the target monitoring region is generated according to the vibration information. The abnormal vibration monitoring can be performed on the vibration object in the target monitoring region in time according to this method.

Abstract: Provided is a method for determining insulation thermomechanical deterioration of a VPI wire rod of a pumped storage power generator motor. The method includes: periodically performing a cold-heat cycling test on a wire rod, and performing an insulation dielectric dissipation factor testing and a result interpretation of the insulation dielectric dissipation factor testing before and after each period to obtain corresponding data; in response to determining the interpretation result as the data being qualified, continuing to perform the cold-heat cycling test; and in response to determining the interpretation result as the data being unqualified, striking the wire rod with a copper hammer, and using an acoustic acquisition and analysis system to perform signal processing to determine spectral characteristics in a thermomechanical deterioration state as a deterioration criterion.

Abstract: Provided is a method for determining insulation thermomechanical deterioration of a VPI wire rod of a pumped storage power generator motor. The method includes: periodically performing a cold-heat cycling test on a wire rod, and performing an insulation dielectric dissipation factor testing and a result interpretation of the insulation dielectric dissipation factor testing before and after each period to obtain corresponding data; in response to determining the interpretation result as the data being qualified, continuing to perform the cold-heat cycling test; and in response to determining the interpretation result as the data being unqualified, striking the wire rod with a copper hammer, and using an acoustic acquisition and analysis system to perform signal processing to determine spectral characteristics in a thermomechanical deterioration state as a deterioration criterion.

Abstract: A method and device for smoke or fire recognition, a computer device and a storage medium are disclosed. The method includes: acquiring a to-be-recognized image in a smoke or fire monitoring region; recognizing a smoke or fire suspected region in the to-be-recognized image according to the to-be-recognized image, including recognizing a smoke or fire suspected region in a visible light image on the basis of colors, and recognizing a smoke or fire suspected region in an infrared image on the basis of brightness; and inputting the to-be-recognized image including the smoke or fire suspected region into a preset model, and recognizing a smoke or fire state in the to-be-recognized image according to an output result of the preset model, the preset model being obtained by training based on the visible light image pre-marked with a smoke or fire state or the infrared image pre-marked with a smoke or fire state.

Abstract: The present disclosure provides a self-adaption faster-than-real-time method for estimating a working condition start-up state of a unit. Firstly, an event recording sequence, an analog measurement point ID, an analog measurement point first-level alarm value and a history scatter point distribution record are read from a time sequence event record table, an analog measurement point table, an alarm threshold table and a historical scatter record table. A measured value slope of the analog measurement point is calculated according to an event recording relative time. Then, an abnormal state estimated value is calculated based on the history scatter point distribution record, the analog measurement point first-level alarm value and the measured value slope of the analog measurement point. Finally, a pre-warning is sent to remind a watchman to perform a preventive operation when the abnormal state estimated value is above the threshold.

Abstract: The present disclosure provides a self-adaption faster-than-real-time method for estimating a working condition start-up state of a unit. Firstly, an event recording sequence, an analog measurement point ID, an analog measurement point first-level alarm value and a history scatter point distribution record are read from a time sequence event record table, an analog measurement point table, an alarm threshold table and a historical scatter record table. A measured value slope of the analog measurement point is calculated according to an event recording relative time. Then, an abnormal state estimated value is calculated based on the history scatter point distribution record, the analog measurement point first-level alarm value and the measured value slope of the analog measurement point. Finally, a pre-warning is sent to remind a watchman to perform a preventive operation when the abnormal state estimated value is above the threshold.

Abstract: The present disclosure provides a self-adaptive test method for an intelligent prediction algorithm of analog measured values. Firstly, an event recording sequence, an analog measurement point ID and an analog measurement point alarm value are read from a time sequence event record table, an analog measurement point table and an alarm threshold table. Next, operation records of a normal operation state of a unit within a statistical cycle are acquired to form historical statistics of measured values of the analog measurement point based on switching value signals. Then, simulated measured values of the analog measurement point with time scales are calculated based on the historical statistics, the analog measurement point alarm value and an analog measurement point current measured value. Finally, sensitivity is calculated; and an alarm is sent to remind a technician to adjust the algorithm when the sensitivity is greater than a threshold.