纺织品氨纶纤维质量含量检测数据
收藏浙江省数据知识产权登记平台2024-04-05 更新2024-05-08 收录
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随着社会的高速发展,人们对于生活质量方面要求不断的提高,对于工业产品的质量要求也在提高。在工业产品生产中,纺织品是人们生产生活的必需品,所以必须加强纺织品纤维含量检测,提高数据精度,保护人们的生命安全,促进社会稳定的发展。1.数据采集,采用显微放大后别各类纤维测维直径或截面面,结合测得的各类纤维根数,按需分别计算纤维质量含量;2.数据计算,对横截面形纤维,根据FZ/T 01101-2008 纺织品 纤维含量的测定 物理法计算纤维质量含量,计算结果按GB/T 8170 修约至0.1,计算公式:P=(N*d²*ρ)/Σ(N*d²*ρ)*100;3.数据说明:P—纤维的质量含量,%;N—纤维的计数测量根数;d²—纤维的直平方的平均值,单位为平方微米(um²);ρ=纤维的密度(棉的密度值为1.54)单位为克每立方米(g/cm³)。4.数据应用:将检测的数据与标准值比对,若纤维质量含量≥合格标准值,则该产品纤维质量含量合格,反之则不合格。
With the rapid development of society, people's requirements for quality of life continue to improve, and so do the quality requirements for industrial products. Textiles are necessities in people's production and daily lives, so it is necessary to strengthen the detection of textile fiber content, improve data accuracy, protect people's lives and safety, and promote the stable development of society.
1. Data Collection: Measure the diameter or cross-sectional area of various fibers after microscopic magnification, combine with the measured number of each type of fiber, and calculate the mass content of fibers separately as needed.
2. Data Calculation: For cross-sectional fibers, calculate the mass content of fibers in accordance with FZ/T 01101-2008 Textiles - Determination of Fiber Content - Physical Method, round the calculation result to 0.1 in accordance with GB/T 8170, with the calculation formula: P=(N×d²×ρ)/Σ(N×d²×ρ)×100;
3. Data Explanation: P—mass content of fiber, %; N—counted and measured number of fibers; d²—average value of the square of fiber diameter, unit: square micrometers (μm²); ρ—density of fiber (the density value of cotton is 1.54), unit: grams per cubic centimeter (g/cm³).
4. Data Application: Compare the detected data with the standard value. If the fiber mass content is ≥ the qualified standard value, the fiber mass content of this product is qualified; otherwise, it is unqualified.
提供机构:
绍兴市乙谷袜业有限公司
创建时间:
2023-11-20
搜集汇总
数据集介绍

特点
该数据集包含350条纺织品氨纶纤维质量含量检测记录,每年更新一次,详细记录了样品的各项检测指标和判定依据,主要用于纺织品纤维含量检测,以提高产品质量和安全性。
以上内容由遇见数据集搜集并总结生成



