Measuring moisture content of dead fine fuels based on the fusion of spectrum meteorological data

Dead fine fuel moisture content(DFFMC)is a key factor affecting the spread of forest fires,which plays an important role in evaluation of forest fire risk.In order to achieve high-precision real-time measurement of DFFMC,this study established a long short-term memory(LSTM)network based on particle swarm optimization(PSO)algorithm as a measurement model.A multi-point surface monitoring scheme combining near-infrared measurement method and meteorological measurement method is proposed.The near-infrared spectral information of dead fine fuels and the meteorological factors in the region are processed by data fusion technology to construct a spectral-meteorological data set.The surface fine dead fuel of Mongolian oak(Quercus mongolica Fisch.ex Ledeb.),white birch(Betula platyphylla Suk.),larch(Larix gmelinii(Rupr.)Kuzen.),and Manchurian walnut(Juglans mandshurica Maxim.)in the maoershan experimental forest farm of the Northeast Forestry University were investigated.We used the PSO-LSTM model for moisture content to compare the near-infrared spectroscopy,meteorological,and spectral meteorological fusion methods.The results show that the mean absolute error of the DFFMC of the four stands by spectral meteorological fusion method were 1.1%for Mongolian oak,1.3%for white birch,1.4%for larch,and 1.8%for Manchurian walnut,and these values were lower than those of the near-infrared method and the meteorological method.The spectral meteorological fusion method provides a new way for high-precision measurement of moisture content of fine dead fuel.

Smoldering charcoal detection in forest soil by multiple CO sensors

Cleaning up residual fires is an important part of forest fire management to avoid the loss of forest resources caused by the recurrence of a residual fire.Existing residual fire detection equipment is mainly infrared temperature detection and smoke identification.Due to the isolation of ground,temperature and smoke characteristics of medium and large smoldering charcoal in some forest soils are not obvious,making it difficult to identify by detection equipment.CO gas is an important detection index for indoor smoldering fire detection,and an important identification feature of hidden smoldering ground fires.However,there is no research on locating smoldering fires through CO detection.We studied the diffusion law of CO gas directly above covered smoldering charcoal as a criterion to design a detection device equipped with multiple CO sensors.According to the motion decomposition search algorithm,the detection device realizes the function of automatically searching for smoldering charcoal.Experimental data shows that the average CO concentration over the covered smoldering charcoal decreases exponentially with increasing height.The size of the search step is related to the reliability of the search algorithm.The detection success corresponding to the small step length is high but the search time is lengthy which can lead to search failure.The introduction of step and rotation factors in search algorithm improves the search efficiency.This study reveals that the average ground CO concentration directly above smoldering charcoal in forests changes with height.Based on this law,a CO gas sensor detection device for hidden smoldering fires has been designed,which enriches the technique of residual fire detection.

Distribution prediction of moisture content of dead fuel on the forest floor of Maoershan national forest, China using a LoRa wireless network

The moisture content of dead forest fuel is an important indicator of risk levels of forest fires and prediction of fire spread. Moisture distribution is important to determine wild fire rating. However, it is often difficult to predict moisture distribution because of a complex terrain, changeable environments and low cover of commercial communication signals inside the forest. This study proposes a moisture content prediction system composed of environmental data collected using a long range radio frequency band 433 MHz wireless sensor network and data processing for moisture prediction based on a BP (back-propagation) neural network. In the fall of 2019, twenty nodes for the collection of environmental data were placed in four forest stands of Maoershan National Forest for a month;7440 sets of data including temperature, humidity, wind speed and air pressure were obtained. Half the data were used as a training set, the other as a testing set for a BP neural network. The results show that the average absolute error between the predicted value and the real value of moisture content of fuels of Larix gmelini, Betula platyphylla, Juglans mandshurica, and Quercus mongolica stands was 0.94%, 0.21%, 0.86%, 0.97%, respectively. The prediction accuracy was relatively high. The proposed distributed moisture content prediction method has the advantages of wide coverage and good real-time performance;at the same time, it is not limited by commercial signals and so it is especially suitable for forest fire prediction in remote mountainous areas.

Prediction and Analysis of Surface Quality of Northeast China Ash Wood during Water-Jet Assisted CO_(2) Laser Cutting

As a natural and environmentally friendly renewable material,Northeast China ash wood(NCAW)(Fraxinus mandshurica Rupr.)was cut by water-jet assisted CO_(2) laser(WACL),the surface quality was evaluated by surface roughness of cut section.The surface roughness was measured by three-dimensional(3D)profilometry.Furthermore,the micromorphology of machined surface was observed by scanning electronic microscopy(SEM).Carbon content changes of machined surface were measured by energy dispersive spectrometer(EDS).A relationship between surface roughness and cutting parameters was established using response surface methodology(RSM).It is concluded that the cutting speed,laser power and water pressure played an important role in surface roughness of cut section.The surface roughness increased as an increase in laser power.It decreased caused by increasing of cutting speed and water pressure.Measurements revealed that the surface quality of NCAW part was improved using the optimized combination of cutting parameters.The established quadratic mathematical model of a good prediction is helpful for matching suitable cutting parameters to obtain expected surface quality.

Experimental Study on Inert Gas-assisted Laser Cut Veneer Based on LOM

Based on the LOM(Laminated Object Manufacturing)process,an inert gas-assisted laser method for wood cutting was proposed.The carbonization degree of wood surface was improved by the introduction of helium(He)gas,and the influence of process parameters on the carbonization layer of wood surface was solved,it was significance to reduce the post-processing of LOM and improve the quality of forming workpiece.The cherry wood veneer was used as the experimental material,under the condition of the same process parameters,the wood was cut with or without inert gas-assisted,and the influence factors of kerf quality were studied by variance analysis.The results showed that under the same condition,compared with traditional laser processing,the kerf width was obviously reduced in the inert gas-assisted cutting.Because the He gas had oxygen-isolation and flame retardant effect,which prevented heat accumulation and conduction.The micro morphology of the kerf surface showed that the flatness was better in the inert gas-assisted cutting.As the excess heat was blown out by the cooling and purging of the gas,the phenomenon of oxidation and burning was reduced,the range of HAZ(heat affected zone)was reduced,and the carbonization phenomenon was obviously improved.The surface quality of kerf was improved effectively.According to the analysis of variance,in addition to the effect of laser power,cutting speed and inert gas flow on the cutting width,the interaction between inert gas flow and laser power,laser power and cutting speed were also the main factors which affected the cutting width.The feasibility of the combined inert gas and laser processing to improve wood cutting quality has been verified through experimental research,which provided a certain reference for the followup research on improving the wood processing quality.