Modes of Occurrence and Cleaning Potential of Trace Elements in Coals from the Northern Ordos Basin and Shanxi Province, China

Based on the analyses of 43 elements in 16 samples of the raw coal and feed coal collected from the northern Ordos basin and Shanxi Province, the modes of occurrence of these elements were studied using the method of cluster analysis and factor analysis, and the cleaning potential of the hazardous elements relatively enriched in the coals was discussed by analyzing six samples of the cleaned coal from the coal-washing plants and coal cleaning simulation experiments. The results shows that the elements Br and Ba show a strong affinity to the organic matter, Cs, Cd, Pb, Zn and Hg partly to the organic matter, and the other trace elements are mainly associated with the mineral matter. Cs, Mo, P, Pb, Zn and S have positive correlations with the two principal factors, reflecting the complexity of their modes of occurrence. Some elements that were thought to show a faint relationship (Be with S and Sb with carbonates) in other rocks are found to have a strong interrelation in the coals. Clay minerals (mainly kaolinite) dominate in the coals, and Ta, Th, Ti, Sc, REE, Hf, U, Se, W, V, Nb, Mo, Al, P, Cr, Pb and Zn are distributed mostly in kaolinite, while K, Rb, Cs, and Na have much to do with illite. Conventional cleaning can reduce the concentrations of most hazardous elements in various degrees. The hazardous elements S, As, Sb, Se, Mo, Pb, Cd and Hg relatively enriched in some coals from the area studied have a relatively high potential of environmental risks. However, by physical coal cleaning processes, more than 60% of As and Hg were removed, showing a high degree of removal, more than 30% of Sb, as well as S, Pb and Cd partly associated with the inorganic matter were removed. Se and Mo showing a relatively low degree of removal could be further removed by deep crushing of the coal during physical cleaning processes, and the concentrations of S, Pb, Cd and Hg with a partial association with the organic matter could be decreased in such ways as the coal blending. Cluster analysis together with factor analysis is a rapid and effective way to deduce the mode of occurrence of an element from bulk samples, and the removability data of most hazardous elements are basically consistent with their modes of occurrence suggested, which indicates that the statistical analysis could predict the cleaning potential of hazardous elements during the physical coal cleaning.

Geochemistry and Modes of Occurrence of Hazardous Trace Elements in the No.11 Coal Seam,Antaibao Surface Mine,Shanxi Province

Concentrations of seventeen hazardous trace elements including As, Pb, Hg, Se, Cd, Cr, Co, Mo, Mn, Ni, U, V, Th, Be, Sb, Br and Zn in the No.ll coal seam, Antaibao surface mine, Shanxi Province were determined using Instrumental Neutron Activation Analysis （INAA）, Inductively Coupled Plasma Atomic Emission Spectrometry （ICP-AES）, Cold-Vapor Atomic Absorption Spectrometry （CV-AAS） and Graphite Furnace Atomic Absorption Spectrometry （GF-AAS）. Comparisons with average concentrations of trace elements in Chinese coal show that the concentrations of Hg and Cd in the No. 11 coal seam, Antaibao surface mine are much higher. They may be harmful to the environment in the process of utilization. The variations of the trace elements contents and pyritic suffur in vertical section indicated that： （a） the concentrations of As, Pb, Mn, and pyritic sulfur decrease from roof to floor; （b） the concentrations of Cr, Zn and Mo are higher in roof, floor and lower in coal seam; （c） the concentration of Br, Sb, and Hg are higher in coal seam and lower in roof and floor; （d） the concentrations of Mo, V, Th and AI vary consistently with the ash yield. Cluster analysis of trace elements, pyritic sulfur, ash yield and major elements, such as AI, Fe, P, Ca shows that： （a） pyritic sulfur, Fe, As, Mn, Ni, Be are closely associated and reflect the influence of pyrite; （b） Mo, Se, Pb, Cr, Th, Co, Ca and A! are related to clay mineral, which is the main source of ash; （c） U, Zn, V, Na, P maybe controlled by phosphate or halite; （d） Hg, Br, Sb and Cd may be mainly organic-associated elements which fall outside the three main groups. The concentration distribution characteristics of trace elements in coal seam and the cluster analysis of major and trace elements showed that the contents of trace elements in the No. 11 coal seam, Antaibao surface mine, are mainly controlled by detrital input and migration from roof and floor.

Effect of occurrence mode of heavy metal elements in a low rank coal on volatility during pyrolysis

The harmful trace elements will be released during coal utilization, which can cause environment pollution and further endangering human health, especially for heavy metal elements. Compared to combustion, the release of heavy metal elements during coal pyrolysis process, as a critical initial reaction stage of combustion, has not received sufficient attention. In the present paper, a low rank coal, from Xinjiang province in China, was pyrolyzed in a fixed bed reactor from room temperature, at atmospheric pressure, with the heating rate of 10 °C/min, and the final pyrolysis temperature was from 400 to 800℃ with the interval of 100℃. The volatility of heavy metal elements (including As, Hg, Cd and Pb) during pyrolysis process was investigated. The results showed the volatility of all heavy metal elements increased obviously with increasing temperature, and followed the sequence as Hg > Cd > As > Pb, which was mainly caused by their thermodynamic property and occurrence modes in coal. The occurrence modes of heavy metals were studied by sink-andfloat test and sequential chemical extraction procedure, and it can be found that the heavy metal elements were mainly in the organic and residual states (clay minerals) in the raw coal. And most of the organic heavy metals escaped during the pyrolysis process, the remaining elements were mainly in the residual state, and the elements in Fe-Mn state also tended to remain in the char.

Distribution, modes of occurrence, and main factors influencing lead enrichment in Chinese coals

Lead is a potentially harmful element that has caused serious environmental pollution during its mining and use along with serious human health problems.This study assessed lead in Chinese coals based on published literature,with a particular focus on data reported since 2004.The analysis included 9447 individual samples from 103 coalfields or mines in 28 provinces in China.The arithmetic mean content of lead in the studied coals was 15.0μg/g.Considering the coal reserves,the weighted-average lead concentration in Chinese coals was calculated to be 19.6μg/g.Lead was significantly enriched in the coals from Henan Province and enriched in the coals from the Tibet Autonomous Region.The coals from Tibet–Western Yunnan and the southern areas of China had elevated lead concentrations.Sulfides are the primary hosts of lead in Chinese coals,although other hosts include silicates,organic matter,carbonates,and other minerals.Source rocks in the sediment-source region and marine environments may be the most significant factors contributing to lead enrichment in Chinese coals.Hydrothermal fluids and peat-forming plants also contribute to lead enrichment in some Chinese coals.

Modes of Occurrence and Geological Origin of Beryllium in Coals from the Pu'an Coalfield, Guizhou, Southwest China

The concentration, modes of occurrence and geological origin of beryllium in five workable coal beds from the Pu＇an Coalfield of Guizhou were studied using the inductively coupled-plasma mass spectrometry （ICP-MS）, floating and sinking experiments （FSE） and sequential chemical extraction procedures （SCEP）. The results show that the average concentration of beryllium in coals from the Pu＇an Coalfield is 1.54 μg/g, much lower than that in most Chinese and worldwide coals. Beryllium in the Pu＇an coals was not significantly enriched. However, it should be noted that the No. 8 coal bed from the study area has a high concentration of beryllium, 6.89 μg/g, three times higher than the background value of beryllium in coal. Beryllium in coal mainly occurs as organic association and has predominantly originated from coal-forming plants when its concentration is relatively low. The concentration of beryllium occurring as organic association is close to that distributed in inorganic matter when beryllium concentration of coal is similar to its background value, and in addition to coal-forming plants, beryllium is mainly derived from detrital materials of terrigenous origin. When beryllium is anomalously enriched in coal, it mainly occurs as organic association and is derived from volcanic tonsteins leached for a long geological time and then adsorbed by organic matter in peat mire.

Mineralogy and Mode of Occurrence of Gold, Silver and Bismuth of the Caijiaying Lead-Zine-Silver Deposit, Hebei Province

The deposit under study is a hydrothermal filling-metasomatic vein type lead-zinc-silver deposit, in whichgold and silver can be recovered as by-products. These metals mainly occur as microgranular native gold,electrum, stephanite, acanthite, pyraragyrite, freibergite, and native silver. Gold minerals tend to be associatedwith galenobismutite, native bismuth and unnamed Bi_2Te. They are either enclosed in pyrite, marmatite,iron-bearing sphalerite and galens or fill the microfissures of these minerals. Silver minerals usually occur incleavages or fissures of galena, marmatite and pyrite, but are not associated with gold and bismuth minerals.Gold and silver mineralizations occurred later than lead and zinc, while the silver mineralization was precededby that of gold.

煤系中关键金属元素的成矿作用研究进展与展望

煤系中关键金属元素的赋存状态、分布规律、成矿机制以及有效提取和综合利用的研究是近10年来煤地质学等相关领域的研究前沿和热点问题,国内外学者在煤系中关键金属矿床的发现,关键金属元素赋存状态,成矿物质来源、迁移、富集和保存,开发利用潜力评价,精细勘查技术研发,关键元素的分离提取等方面取得了重要研究进展,为煤系关键金属矿产资源的开发利用奠定了坚实的理论和技术基础,同时在揭示与煤系关键金属相关重大地球科学问题方面取得了长足进展。本文结合国内外近些年来的进展,对煤系中关键金属元素(主要是锗、镓、锂、铌、锆等)的成矿作用进行了总结和凝练,指出了存在的问题及其解决方案和思路。

深部煤层气游离气饱和度计算模型及其应用

近几年全国深部煤层气基于精细地质研究和水平井多段加砂压裂取得重大突破,部分井日产气量高达十万方,给煤层气产业重新树立了信心。但是,由于深部煤储层处于高地应力、高地温、高孔隙压力、低渗透率的复杂地质环境,不同深度煤储层典型参数和煤层气赋存方式的分布特征以及对储量和产量的影响亟需揭示。基于Langmuir等温吸附式、亨利定律及物质平衡原理,考虑吸附层和溶解气的影响,建立了深部煤层气游离气饱和度计算模型;以国内鄂尔多斯盆地大宁-吉县区块深部煤层气藏为例,分析不同深度深部煤层气赋存方式及分布特征,并评价游离气饱和度对深部煤层气储量、产量与合理配产的影响。研究认为:当煤层埋深大于溶解饱和对应的深度,游离气才会出现,且随着埋深的增加,游离气饱和度先快速增加后缓慢增加,目标区块埋深1875 m处才出现游离气,在埋深2800 m处游离气饱和度高达90%,游离气的占比高达17.3%。游离气饱和度对深部煤层气储量计算、产气特征和合理配产影响很大,随着游离气饱和度的增大,煤层气储量线性增大,累产气量持续上升但后期上升幅度逐渐变缓,深部煤层气井最优配产增加,井底流压下降速度加快,压裂改造区的内外压差降低,未改造区动用程度增加。目标区块主力开发煤层埋深位于2100~2300 m,游离气饱和度介于48%~68%,游离气占比介于10%~13%,建议气井合理配产介于(4~10)×10^(4)m^(3)/d。研究结果可为深部煤层气进一步开发提供理论依据和方法支撑。

原位微区分析华北典型富锂煤中关键金属赋存规律

煤是特殊的沉积有机岩石,在其形成过程的特定地质条件下,可以富集战略性金属,并在煤系中形成大型或超大型金属矿床。目前已经在华北聚煤区多处煤田发现煤系锂矿化现象,为了查明锂的载体及其赋存规律,本文在矿物组成分析的基础上,采用微区原位分析的方法研究了不同矿物和显微组分中关键金属的赋存特征,为煤系关键金属的富集成因和勘查提供了新的思路。研究结果表明:高岭石是煤中锂的最重要载体,表现为Li-Ga、Li-Zr-Nb-Hf-Ta和Li-Y-Sr不同的元素组合特征,分别代表碎屑物源控制型、火山灰输入型和流体活动参与型三种不同的关键金属富集成因类型。镜质结构体中富集Zr-Hf-Th元素组合,胶质结构体表现为轻度的Li富集;脉状含钠黏土矿物富集Ga-Ba-Tl,脉状磷灰石表现为Ba-Sr-Y富集特征,这些脉体矿物元素的富集是成煤后期流体活动的产物。

不同单节理产状岩石力学性质数值模拟与强度预测模型

节理岩石力学性质对于各类岩体工程长期稳定具有重要意义,而岩石的力学性质受节理产状影响极大,甚至起决定作用。为研究节理产状对岩石强度和破坏模式的影响机制,基于节理产状参数准确预测岩石的单轴抗压强度,采用PFC软件建立了不同单节理产状的岩石数值模型,开展了一系列单轴压缩数值模拟试验,得到了节理尺寸和倾角对岩石力学特性的影响规律:随着节理尺寸增大,岩石破坏模式逐渐由沿一定角度的剪切破坏变为节理端部裂纹扩展破坏,单轴抗压强度逐渐减小;随节理倾角增大,当节理倾角小于内摩擦角时,岩石的单轴抗压强度逐渐减小,破坏模式主要是节理端部翼裂纹扩展破坏;当节理倾角超过内摩擦角继续增大时,岩石的单轴抗压强度则逐渐增大,破坏模式主要是沿一定角度穿切岩石或次生裂纹扩展的剪切破坏。在此基础上,结合损伤力学和断裂力学理论提出了单节理岩石单轴抗压强度预测模型,充分考虑了由单节理产状差异导致的不同破坏模式对岩石强度的影响,模型参数易于获取。经算例验证,模型具有较高精度,能够满足工程现场需求。

山西大同塔山井田煤中Sr的赋存特征

大同煤田石炭-二叠系煤层中广泛分布有印支期和燕山期火成岩,使煤层发生接触变质作用。以往的研究表明塔山井田5222巷煤中微量元素Sr异常富集,接触变质煤和正常煤中Sr含量最大值分别为3067μg/g和2729μg/g,平均含量为1165μg/g,是世界煤中Sr平均含量的10.6倍,但其赋存特征尚不清楚。通过对塔山井田5222巷煤和辉绿岩岩墙进行系统采样,综合运用电感耦合等离子体质谱(ICP-MS)、X射线荧光光谱(XRF)、带能谱的扫描电子显微镜(SEM-EDS)对样品进行Sr元素和主量元素含量测定及矿物学分析,结合元素相关性分析和逐级化学提取等方法,研究了煤中Sr的赋存状态。煤中Sr与P_(2)O_(5)的显著相关性和逐级化学提取试验得出,Sr可能主要与含磷矿物(磷灰石)和硅酸盐矿物(黏土)结合;扫描电镜分析得出这2类矿物紧密交互共生,磷灰石的种类包括呈六方柱形的氟磷灰石和嵌入在黏土矿物中呈细小分散粒状的羟基磷灰石。

基于煤矸石中锂、镓元素赋存状态的高梯度磁选预富集试验

我国山西、内蒙古部分矿区煤矸石中蕴藏着锂、镓等战略性关键金属,其锂、镓元素富集逐渐成为研究热点。然而煤矸石中锂、镓含量很低,直接浸出需消耗大量化学药剂,高效、经济的富集锂、镓元素仍存在很大挑战。为提高煤矸石中锂、镓富集效率,针对山西朔州地区煤矸石中锂、镓元素赋存状态和预富集方法展开研究。采用逐级化学提取法、矿物物相组成、矿物解离分析、电感耦合等离子体质谱法、扫描电子显微镜和能量色散光谱,研究了煤矸石中锂、镓元素的赋存状态,利用高梯度磁选探究通过抛除黄铁矿对煤矸石中锂、镓元素预富集的可行性。结果表明,煤矸石主要由高岭土、黄铁矿、石英、方解石、白云母等矿物组成,锂、镓元素主要赋存于硅酸盐类矿物中,黄铁矿中含量较少。原矿中锂质量分数146.37μg/g,镓质量分数25.04μg/g。通过磁选方法抛除黄铁矿可对煤矸石中锂、镓元素预富集,1000 mT时,预富集效果最佳,磁选尾矿中锂质量分数210.63μg/g,为原矿中锂含量的1.45倍,锂回收率88.00%。镓质量分数31.88μg/g,高于原矿中镓元素,镓回收率80.07%。

中国煤中钪地球化学特征的研究进展

钪(Sc)具有较高熔点、较小密度,是最好的阻挡金属,广泛应用于照明、合金、陶瓷、催化剂等工业领域。在特定地质条件下,部分煤富集钪,可成为战略金属资源予以利用,因此,钪地球化学是煤地质学研究领域的热点问题之一。为阐明我国煤中钪的地球化学特征,在全面收集我国煤中钪测试数据的基础上,并结合安徽淮南煤、重庆南桐煤、四川宝鼎煤和云南勐托煤等实例,系统总结了我国煤中钪的含量水平、时空分布、赋存状态和富集成因,并初步评价了我国的煤系钪资源。结果表明:我国大多煤中钪含量正常,钪的平均含量为4.02 mg/kg,仅略高于世界硬煤。贵州、重庆、安徽、广西、内蒙古、山西、云南等局地煤中钪含量较高,最高达139 mg/kg。煤层顶、底板围岩及夹矸岩石较煤富集钪。我国富钪煤大多为二叠纪烟煤,晚侏罗–早白垩世煤中钪含量普遍较低。一般而言,高灰煤和腐泥煤因具较高的矿物质含量,常富集钪。钪为亲石元素,在煤中主要与矿物质结合,多赋存于高岭石等硅酸盐矿物和磷钇矿等自生矿物中,部分与有机质结合,与腐植质有关。我国煤中钪的主要富集成因类型包括:①基性源岩贡献型,钪为相容元素,基性岩中钪含量高于中酸性岩,因此,物源区基性源岩风化可导致部分煤中钪富集;②海陆过渡沉积环境贡献型,海水入侵导致泥炭沼泽的pH值增大,从而利于钪的迁移,此外,在泥炭沼泽的还原环境中,大量腐植酸生成,钪易与有机质结合而富集;③地下水淋滤贡献型,地下水淋滤围岩的含钪矿物导致煤层中钪局部富集;④热液贡献型,热液与围岩发生交代反应使钪迁移,改变煤的矿物质组成导致煤富集钪;⑤岩浆及变质贡献型,岩浆侵入导致煤阶提升,从而减少有机质结合态的钪,同时,伴随灰分的升高,煤中矿物结合态的钪相应增加;⑥同沉积火山灰贡献型,煤系基性凝灰岩层(蚀变黏土岩夹矸,Tonsteins)可为煤提供钪。

宁东煤田横城矿区太原组煤中关键金属的物质来源和富集机理

对宁东煤田横城矿区太原组9号煤层进行了矿物学和地球化学研究,以便查明煤中关键金属的分布、赋存和富集特征,并评价其综合利用前景。研究结果表明:①横城矿区9号煤以高的镜质组含量、特低—低灰分产率和中—高硫含量为特征。②煤中矿物主要由高岭石组成,以细胞充填状、透镜状和薄层状等形式存在。煤层底板中矿物主要由石英、高岭石和白云母组成,其主要为碎屑成因。③煤层中常量元素主要由SiO_(2)和Al_(2)O_(3)组成,煤中Li、Zr、Nb、Hf、Pb和Th的含量达到轻度富集—富集程度,其中Li、Pb和Th主要赋存于高岭石,Zr和Hf赋存于锆石,Nb赋存于高岭石和锐钛矿。矿区9号煤层形成于受海水影响的潮坪-潟湖环境,煤层下部形成于铁源供给不足的低位沼泽环境,煤层上部形成于铁源严重不足的高位沼泽环境,故下部煤层中硫以黄铁矿硫为主而上部以有机硫为主。煤中碎屑物质主要来源于阴山古陆和阿拉善地块,阴山古陆主要提供了元古宙的陆源碎屑物质,阿拉善地块主要供给了早石炭世的碎屑物质,此外也有少量的火山灰和奥陶系灰岩风化残积物进入到含煤盆地。煤中的Li、Zr、Nb等关键金属的富集主要受控于长英质的碱性—过碱性物质输入量的多少,同时水/岩作用过程也导致了关键金属的活化、迁移和重新分配。煤灰中Li_(2)O含量超过其边界品位,REO、Ga、Zr和REY接近相应边界品位,故可考虑Li-Ga-Zr-REY等的综合开发利用。

石煤中稀土元素地球化学研究

在全面收集石煤中稀土元素含量资料的基础上,探讨了石煤中稀土元素的赋存状态,剖析了石煤中稀土元素的富集成因。结果表明:不同地区石煤中稀土元素含量的差异较大,但均高于中国煤和世界煤中稀土元素的背景值,稀土元素相对富集。石煤中稀土元素的赋存状态多样,但以无机结合态或残渣态为主,部分石煤中稀土元素与有机质有关,部分兼具有机态和无机态。石煤中稀土元素富集的主要因素包括海相沉积环境、沉积物源区供给、热液流体(酸性、碱性、高温岩浆热液和海底喷流等)的侵入和地下水淋滤作用等。L/H、LaN/YbN、δCe、δEu等地球化学参数和稀土元素配分模式可推断石煤形成的物质来源和成矿条件等信息,具重要的地学示踪理论意义。

煤系锂资源的分布赋存特征与提取分离研究进展

锂是一种战略性金属,应用领域广泛,对国家安全、国民经济和科技发展具有极其重要的意义。目的目前,我国锂资源面临着供需不平衡的困境,急需寻找新的锂来源。我国煤中锂含量较高、分布广泛,煤系副产品煤矸石及粉煤灰中锂含量高,有望成为传统资源的替代物。从煤矸石和粉煤灰中回收锂可拓宽现有锂的生产渠道,并实现煤矸石和粉煤灰的资源化高值利用。方法本文综述了煤系锂元素分布特征、赋存状态和燃烧过程中迁移规律的最新研究进展,并对煤系锂元素的浸出提纯回收方法进行了总结,可为从煤系副产品中提取回收锂资源提供参考。结果我国华北与华南赋煤区内锂含量较高,主要载锂矿物是高岭石、伊利石等黏土矿物,部分矿区内煤层夹矸和顶底板中锂含量高于煤层;煤经燃烧后实现了锂元素的二次富集,锂主要与铝硅酸盐结合,赋存于玻璃相内,并倾向于富集在细粒飞灰中;浸出和分离是实现煤系锂资源回收利用的必要步骤,但现有工艺复杂,浸出液中锂浓度低,杂质离子对分离纯化环节干扰严重。结论未来煤系锂资源开发应在采选过程中强化矸石与煤中锂元素差异性富集,着重探明燃烧过程中锂的迁移转化规律,重视浸出的高效性和分离纯化过程的选择性。煤系锂资源的开发回收有助于煤炭资源高值化利用,促进绿色可持续发展。

两种危重症病人肠内营养不耐受风险预测模型的应用价值比较

目的:探究现有的危重症病人肠内营养不耐受风险预测模型的应用性能及应用价值。方法:采用Meta分析方法查找现有的危重症病人肠内营养不耐受的风险预测模型。选取2023年3月至2023年8月入住东部战区总医院重症医学科及各ICU符合纳排标准的病人应用于模型。采用受试者工作特征曲线下面积(AUROC)和Hosmer-Lemeshow拟合优度检验(H-L检验)评价模型区分度和校准度。结果:共纳入两种模型,收集了395例病人,161例发生不耐受(40.8%)。模型1 AUROC为0.838(95%CI:0.798~0.873),模型2 AUROC为0.744(95%CI:0.698~0.786),采用Delong法比较两种模型的AUROC值,差异有统计学意义(P=0.0043),模型1 AUROC值优于模型2。模型1的H-L检验结果一般(χ^(2)=61.116,P<0.001),模型2的H-L检验结果较好(χ^(2)=3.659,P=0.887)。结论:模型1的区分能力优于模型2,模型2的校准度优于模型1。模型1适用于病人病情变化时动态预测,模型2适用于病人进行肠内营养后初始预测。医护人员可根据临床具体情况联合使用两种模型,提高预测效能,也可开展高质量研究,构建新的风险预测模型。

我国煤系铀矿形成条件及成矿模式研究

我国铀资源对外依存度高达78%,供应安全不容乐观,煤系铀是一种非常规铀资源,对其开发能为我国铀资源安全供给提供保障。近年来随着煤铀协同勘查的推进,在我国北方地区发现了多个大型煤系砂岩型铀矿,对今后煤系铀矿勘探提供了大量可借鉴的参考资料。煤系铀矿成矿是一个复杂的过程,目前关于煤系铀成矿的研究还比较分散,尤其是对其赋存和成矿规律还不够明确。综合国内外最新研究成果,对煤系地层中铀矿床成因类型、铀的赋存状态、成矿有利条件和成矿模式进行了较为全面的阐述。并进一步提出了我国煤系铀矿的研究仍很不充足,特别亟需加强铀的微观地质选择过程、铀矿的矿化时间和期次等方面的研究,以便深入了解和阐释煤系铀矿的成矿机理,同时在今后研究中也需更加关注煤岩铀和砂岩铀的成因联系。

失效模式与效应分析联合PDCA管理对手术室护理质量及风险发生率的影响

目的探究在手术室护理管理的过程中开展失效模式与效应分析联合PDCA管理对手术室护理质量以及风险发生率的影响。方法在2022年5月至2023年10月本院进行手术治疗患者中选择88例作为研究对象,按照随机数字表法分为对照组(44例,开展常规手术护理管理)和观察组(44例,开展失效模式与效应分析联合PDCA循环管理)。对比两组手术护理质量以及风险事件发生率。结果两组手术期间护理质量比较,观察组手术室管理、服务规范、护理文书、护理安全以及急救药械等方面评分均高于对照组(P<0.05)。护理缺陷、护理投诉发生率比较,观察组低于对照组(P<0.05)。两组手术期间RPN值比较,观察组安全评估、手术部位标识、术中感染、术中低体温以及术中压疮值方面均低于对照组(P<0.05)。两组手术期间不良事件发生率比较,观察组低于对照组(P<0.05)。结论在进行手术室护理管理过程中开展失效模式与效应分析联合PDCA管理,可以有效提升手术室护理质量,降低风险事件发生率,对于保障手术顺利性,提升手术质量存在重要意义。

基于两步降维的单相接地故障发生时刻估计算法

为准确估计单相接地故障发生时刻,本文提出一种基于两步降维的配电网单相接地故障发生时刻估计算法。该算法利用经验模态分解构建滤波器,根据馈线零序电流建立高维特征数据集,经过主成分分析法及希尔伯特变换映射算法将高维数据两次降维后得到二维特征数据集。利用基于密度的聚类方法自适应地将数据分为故障数据和非故障数据两类,从而估计故障发生时刻。文中设计了包含7种常见高阻接地介质的11组实验,对该算法的故障时刻辨识精度进行验证,结果表明,该算法精度在7.3 ms以内,对瞬时性故障能够有效识别故障时段。