Rapid dataset generation methods for stacked construction solid waste based on machine vision and deep learning.

The development of urbanization has brought convenience to people, but it has also brought a lot of harmful construction solid waste. The machine vision detection algorithm is the crucial technology for finely sorting solid waste, which is faster and more stable than traditional methods. However, accurate identification relies on large datasets, while the datasets from the field working conditions are scarce, and the manual annotation cost of datasets is high.

An arc fault diagnosis algorithm using multiinformation fusion and support vector machines.

Arc faults in low-voltage electrical circuits are the main hidden cause of electric fires. Accurate identification of arc faults is essential for safe power consumption. In this paper, a detection algorithm for arc faults is tested in a low-voltage circuit.

An experimental study on the thermal characteristics and heating effect of arc-fault from Cu core in residential electrical wiring fires.

The characteristics of a series direct current (DC) arc-fault including both electrical and thermal parameters were investigated based on an arc-fault simulator to provide references for multi-parameter electrical fire detection method. Tests on arc fault behavior with three different initial circuit voltages, resistances and arc gaps were conducted, respectively. The influences of circuit conditions on arc dynamic image, voltage, current or power were interpreted.

[Research on process character information in early fire based on Fourier transform infrared spectrum detection].

CO was chosen as an early fire detection factor through analyzing all kinds of characters in the process of fires, and an experiment system was established based on Fourier transform infrared spectrometer. Through this system, lots of early fire experiments were carried out, and the authors got the CO concentrations of all kinds of materials. Using the concentration of CO, an autoregressive integrated model was established by time series analysis, then the process characters phi1 and phi2 were extracted from them.

[Research on early fire detection with CO-CO2 FTIR-spectroscopy].

A new fire detection method is put forward based on the theory of FTIR spectroscopy through analyzing all kinds of detection methods, in which CO and CO2 are chosen as early fire detection objects, and an early fire experiment system has been set up. The concentration characters of CO and CO2 were obtained through early fire experiments including real alarm sources and nuisance alarm sources. In real alarm sources there are abundant CO and CO2 which change regularly.