Study On The Effects Of Fabric Structure On Flame Retardancy Of Firefighter-clothing

The firefighter-clothing,as the equipment exposed to fire directly,is the first line of defense to protect firefighters,it must have superior flame retardancy.So research on flame retardancy of firefighter-clothing frbric has gain more attention.Study has shown that fabric flame retardancy influenced by many factors,and the fabric structure is theimportant factor.In this paper which is based on the domestic and international research on flame-retardant fabrics,the yarn with better single yarn strength and flame retardant property is selected from two kinds of yarn-A(fineness of 15tex*2,twist 710 twist/m)and B(fineness of 16tex*2,twist750 twist/m)-as raw material.Yarn B is selected for subsequent weaving.It also designs and weaves 15 standard fabrics suitable for the outermost layer of fire clothing according to the industry standard GA10-2014"firemans protective clothing for firefighting".The fabric weave is designed as 2/2 basket twill,2/1 twill weave,2/2 twill weave,3/1 twill weave and twill reinforcement.The meridional density is 320 yarns/10cm and the zonal density is 248 yarns/10cm,264 yarns/10cm and 280 yarns/10cm.The mechanical properties of the fabric(breaking strength,tear strength),surface moisture resistance,color fastness and thermal properties(thermal stability,flame retardant properties)of the above 15 kinds of fabrics were tested.Experiments showed that all the properties were in compliance with the requirements of industry standards.The fabric whose fabric weave is 2/1twill,warp density is 320 yarns/10cm,weft density is 280 yarns/10cm,thickness is 0.520mm,mass per unit area is 207 g/m~2,mass per unit volume is 0.398 g/cm~3,cover factor is 90.6%,has the best flame retardancy in the 15 fabrics.The damage area index is introduced,and the two methods of damage area test-weighing method and image method-are discussed.Two methods can effectively characterize the flame retardancy of fabrics,and the smaller the damage area is,the better the flame retardancy is,and the damaged area measured by the image method is slightly larger than the damaged area measured by the weighing method.Grey relational analysis is used to explore the influence of five indexes of fabric organization coefficient,thickness,mass per unit area,mass per unit volume and coverage factor on damage length and damage area.The results of grey relational analysis shows that the coverage coefficient has the most significant influence on the flame retardancy of fabric,followed by the thickness and the quality of unit area,and then the unit volume mass.The fabric structure has the least significant effect on the flame retardancy of fabrics.Using artificial neural network technology,fabric structure as the input layer,fabric damage length and damaged area as the output layer,through the BP neural network and extreme learning machine to establish fabric structure and flame retardant performance prediction model,and compare the two models.The results show that both prediction models can effectively predict the flame retardant performance,and the extreme learning machine model prediction error is less time-consuming and shorter.The flame retardant outer layer of the firefighter-clothing will be exposed to the harsh fire environment directly,and an excellent flame retardancy can protect the inner fabric and the human body.Therefore,it is of profound significance to dig into the flame retardant outer layer of the firefighter uniform for the better protection of firemen and the timely and effective disaster relief.