城市立交桥交通噪声变化规律与影响的研究

针对目前我国城市立交桥交通噪声影响的状况,环评预测结果偏差过大的问题,应用大量的环保验收实测数据,对城市立交桥交通噪声的变化规律与影响进行了分析研究.城市立交桥的交通噪声昼间变化幅度小于夜间变化幅度,一定时期的昼间噪声等效声级Ld与夜间噪声等效声级Ln的变化幅度不大于1.0dB(A),昼间噪声等效声级Ld高于夜间噪声等效声级Ln,其差值(Ld-Ln)多在2.5dB(A)之内.立交桥交通噪声主要是由大型车辆行驶噪声贡献的,车辆的行驶噪声夜间普遍高于昼间,对周围敏感点影响的噪声一楼最低,在桥路面以上六层楼的噪声最高,比桥面平层楼房平均高2.4～3.0dB(A),桥面下的楼房的噪声低于桥面平层楼噪声2～3dB(A).其结果对于城市立交桥交通噪声的管理与治理提供相应的参考.     

北京地铁岛式站台噪声的初步研究

为研究北京岛式站台噪声水平及噪声特点,选取了北京地铁2号线和5号线的10个岛式站台进行了实地的测量,从噪声级以及频谱角度对测量结果进行了分析。结果显示,测量时间内的LAeq,max都高于标准限值80dB(A)。使用独立样本t检验的结果得出,2号线与5号线在LAeq以及LAeq,max上不存在显著差异(P>0.05),说明2号线和5号线噪声在相近的水平上。通过噪声频谱的时程曲线也直观的得出列车在进出站过程中噪声级大于80dB(A),无列车通过且不受相反轨道列车影响时的背景噪声在65dB(A)左右,受影响时在70dB(A)左右。倍频程频谱分析得出,地铁站台噪声具有明显的中频特征。进一步分析,2号线和5号线站台都存在若干的主频,其基频和谐频分别为63、250和1kHz。     

传声器的佩戴方式对噪声测量结果的影响分析

为准确测量作业场所的噪声对作业工人的影响情况,本文通过现场实验的方法分析传声器不同的佩戴方式对噪声测量结果的影响程度。研究结果表明,在稳态噪声作业环境中,将传声器佩戴于耳部、肩部和胸前三个位置其对噪声测量结果的影响较小,等效声级的差异(Max-Min)不大于1dB(A),噪声最大值差异不大于5dB(A);而在非稳态噪声作业环境中,三个位置测量的等效声级差值小于2dB(A),而噪声最大值差异接近6dB(A)。     

某大型机加车间数控机床减噪工程测试与分析研究

为研究大型机加车间噪声减噪工程现状效果和特点,选取某大型机加车间数控机床为研究对象,对其进行减噪工程治理,现场实测了治理前和治理后的噪声数据,并对噪声测量结果进行分析。研究结果表明:数控机床操作人员8 h连续等效A声级从治理前的89.2 dB(A),降到治理后的74.3 dB(A),降低了16.7%.;数控机床操作岗位位置测点,在加工1个机件的测量时间段里,噪声值从治理前的85.9 dB(A),降到治理后的55.1 dB(A),降低了33.85%;对机加车间现场布置了67个测点,在加工1个机件的测量时间段里进行测量,得到该车间噪声治理前和治理后噪声分布图;对数控机床减噪工程治理前和治理后的频谱进行了分析,得出治理前和治理后各自的最大声级所在频段不随距离的改变而改变,高频减噪效果显著。     

冲床噪声治理途径

一、冲床噪声分析冲床是广泛应用于金属制品业和机械制造业中的重型加工机械.它是一种高噪声设备.机旁1米处的噪声级最高的可超过115dB(A).严重危害操作工人健康和周围居民的休息.根据1986年福建省有关部门对福州、厦门等五个地市52个机械制造工厂调查结果表明,在被调查的52个厂家中.共有各类冲床535台.按照噪声级分布.噪声级超过90dB(A)的冲床有431台,占冲床总数的80.6%.福建省调查企业冲床噪声级分布情况见表1一1.从表1—1得知.噪声级在90～100dB(A)之间的冲床数有365台.占调查冲床总数68.2%.大于10OdB(A)的冲床数有66台,占冲床总数12.3%,小于90dB(A)的冲床数有104台,占19.4%.由此可见,福建省调查冲床的噪声级分市主要在90～100dB(A)之间,说明冲床噪声危害是很严重的.     

赤马山矿空压机站噪声控制

空气压缩机是工矿企业生产中普遍使用的设备。空压机站一般都设在厂区或车间内,噪声级大多超过国家卫生标准,职工们深受其害。为了改善劳动环境,1983年,冶金部安全技术研究所与大冶有色金属公司赤马山矿协作,对坑口空压机站进行了噪声综合控制的研究与治理。治理后,进气口噪声由94dB(A)降至70dB(A),机房内由90dB(A)降至84dB(A),值班室内由     

噪声对安全注意力影响实验研究

为了研究作业环境中噪声因素对人的安全注意力的影响,对安全注意力类型及品质特征进行分析,建立安全注意力水平模型。设计噪声条件下的安全注意力水平测量实验,通过实验中不同噪声环境下人的安全注意力水平变化,分析噪声对人的安全注意力的影响作用。结果表明,噪声对人的安全注意力具有较为显著的影响作用;安全注意力的广度、稳定性、分配、转移均受噪声影响,安全注意力的稳定性及转移随噪声的增大而降低;当噪声值大于60 dB、70 dB时,噪声对安全注意力的广度及分配的影响较为显著。     

《工业企业噪声检测规范》(草案)

一、测量仪器 (一)噪声测量使用声级计,声级计应符合国家标准。 (二)声级计和声级校准器每年应送交计量单位校准。 (三)声级计使用前后应进行校准。 二、测量的量和读数方法 (一)测量的量 1.稳定噪声,测量A声级,测量值后应标记 dBA,如 80dBA。 2.不稳定噪声,测量等效连续A声级;或测量不同 A声级下的暴露时间,计算等效连续A声级。 (二)读数方法 测量时使用慢档,取平均读数。 三、测点选择 测量时,应将传声器放置在操作人员的耳朵位置(人离开)。 (一)若车间内各处A声级差别不大(小于3分贝),则只需在车间内选择1—3个测点。 (二)若车间内各…     

城市轨道交通站台噪声测量研究

为研究城市轨道交通高架和地下站台噪声的规律和特点,选取某条线路中的3个高架站台以及3条线路中的7个地下站台进行实地测量,并对测量结果进行分析。研究结果表明:地下站台LAeq值都低于标准限值80 dB(A);站台的中心测点列车进站LAeq值和列车出站LAeq值都非常接近,使用T检验结果得出各站台中心测点列车进站LAeq值和列车出站LAeq值不存在显著差异（P>0.05）;站台测量时要考虑大客流带来的喧闹声;站台最大噪声值是列车出站时,位于站台列车车头停止位置。     

基于数值模拟的公交车火灾发展过程及特性研究

采用数值模拟方法研究典型型号公交车的火灾发展过程,探讨车门打开对火情发展和人员逃生的影响.通过描述火源、公交车的结构及其内饰物的属性,研究车厢内关键位置的温度分布、能见度及CO和O2体积分数的变化规律,以揭示公交车的火灾发展、烟气运动过程及对人员安全逃生的影响.结果表明:车门打开后由于供氧充足,明显加速了火势的蔓延和烟气扩散,并使得燃烧温度显著提高;打开车门后20 s内,车门附近能见度和O2体积分数显著增高,CO体积分数有所降低,是乘客逃生的关键时间.     

Severity of passenger injuries on public buses: A comparative analysis of collision injuries and non-collision injuries

Introduction: Although public buses have been demonstrated as a relatively safe mode of transport, the number of injuries to public bus passengers is far from negligible. Existing studies of public bus safety have focused primarily on injuries caused by collisions. Surprisingly, limited effort has been devoted to identifying factors that increase the severity of passenger injuries in non-collision incidents. Method: Our study therefore investigated the injury risk of public bus passengers involved in collision incidents and non-collision incidents comparatively, based on a police-reported dataset of 17,383 passengers injured on franchised public buses over a 10-year period in Hong Kong. A random parameters logistic model was established to estimate the likelihood of fatal and severe injuries to passengers as a function of various factors. Results: Our results indicated substantial inconsistences in the effects of risk factors between models of non-collision injuries and collision injuries. The severity of passenger injuries tended to increase significantly when non-collision incidents occurred due to excessive speed of bus drivers, on double-decker buses, in less urbanized areas, in winter, in heavy rains, during daytime, and at night without street lighting. Elderly female passengers were also found more likely to be fatally or severely injured in non-collision incidents if they lost their balance while boarding, alighting from, or standing on a bus. In comparison, the following factors were associated with a greater likelihood of fatal or severe injuries in collision incidents: elderly female passengers, standing passengers who lost balance, buses out of driver control, double-decker buses, collisions with vehicles or objects, and less urbanized areas. Practical Applications: Based on our comparative analysis, more targeted countermeasures, namely “4E” (engineering, enforcement, emergency, and education) and “3A” (awareness, appreciation, and assistance), were recommended to mitigate collision injuries and non-collision injuries to public bus passengers, respectively.     

Banging heads onboard buses: Assessment scheme to improve injury mitigation for bus passengers

Abstract

Objective: Although bus travel is one of the safest modes of transport, a substantial number of bus passengers in London are still injured in collision and harsh maneuver incidents, in particular emergency braking. It is not well understood how these passengers are injured. The objective was to better understand the injury mechanisms and develop countermeasures with a test and assessment procedure to prevent or mitigate these injuries.

Methods: The UK national STATS19 data were used to determine the size of the problem. Data, including CCTV footage, in combination with inspection of current buses, were used to determine injury mechanisms and identify features and areas in buses associated with more injuries.

An assessment system based on visual inspection was developed to encourage a reduction in the number of features associated with injury.

Results: The STATS19 analysis showed that three quarters of all injured casualties occurred in incidents where there was no impact, with this proportion rising for seriously injured casualties. Overrepresentation of older females was also seen.

The CCTV analysis and bus examinations highlighted issues with poorly positioned handrails, lack of compartmentalization (restraint), and objects with sharp edges and corners. It also showed that a much higher proportion of passengers seated in the area close to the middle doors and wheelchair area were injured compared to other areas of the bus. Factors contributing to this result were that this area contained more features associated with injury and that persons with reduced mobility have greater exposure in this area; that is, more vulnerable passengers currently sit in the less safe areas of the bus.

Conclusions: A novel analysis of CCTV footage has enabled a better understanding of injury mechanisms for bus passengers to be developed. In combination with inspection of current buses, this has been used to develop an assessment system to improve the safety of buses in London.     

典型直升机噪声特点及其防护需求分析

直升机工作时,旋翼、尾桨及发动机传动系统可产生90dB （A）以上的噪声。本文从听感知角度分析了典型直升机噪声的声压级、特征频率及能量分布等特点及其防护需求。     

Effects of passengers on bus driver celeration behavior and incident prediction

PROBLEM: Driver celeration (speed change) behavior of bus drivers has previously been found to predict their traffic incident involvement, but it has also been ascertained that the level of celeration is influenced by the number of passengers carried as well as other traffic density variables. This means that the individual level of celeration is not as well estimated as could be the case. Another hypothesized influence of the number of passengers is that of differential quality of measurements, where high passenger density circumstances are supposed to yield better estimates of the individual driver component of celeration behavior. METHOD: Comparisons were made between different variants of the celeration as predictor of traffic incidents of bus drivers. The number of bus passengers was held constant, and cases identified by their number of passengers per kilometer during measurement were excluded (in 12 samples of repeated measurements). RESULTS: After holding passengers constant, the correlations between celeration behavior and incident record increased very slightly. Also, the selective prediction of incident record of those drivers who had had many passengers when measured increased the correlations even more. CONCLUSIONS: The influence of traffic density variables like the number of passengers have little direct influence on the predictive power of celeration behavior, despite the impact upon absolute celeration level. Selective prediction on the other hand increased correlations substantially. This unusual effect was probably due to how the individual propensity for high or low celeration driving was affected by the number of stops made and general traffic density; differences between drivers in this respect were probably enhanced by the denser traffic, thus creating a better estimate of the theoretical celeration behavior parameter C. The new concept of selective prediction was discussed in terms of making estimates of the systematic differences in quality of the individual driver data.     

Using event-triggered naturalistic data to examine the prevalence of teen driver distractions in rear-end crashes

IntroductionWhile teen driver distraction is cited as a leading cause of crashes, especially rear-end crashes, little information is available regarding its true prevalence. The majority of distraction studies rely on data derived from police reports, which provide limited information regarding driver distraction.MethodThis study examined over 400 teen driver rear-end crashes captured by in-vehicle event recorders. A secondary data analysis was conducted, paying specific attention to driver behaviors, eyes-off-road time, and response times to lead-vehicle braking.ResultsAmong teens in moderate to severe rear-end crashes, over 75% of drivers were observed engaging in a potentially distracting behavior. The most frequently seen driver behaviors were cell phone use, attending to a location outside the vehicle, and attending to passengers. Drivers using a cell phone had a significantly longer response time than drivers not engaged in any behaviors, while those attending to passengers did not. Additionally, in about 50% of the rear-end crashes where the driver was operating/looking at a phone (e.g., texting), the driver showed no driver response (i.e., braking or steering input) before impact, compared to 10% of crashes where the driver was attending to a passenger.ConclusionsThe high frequency of attending to passengers and use of a cell phone leading up to a crash, compounded with the associated risks, underlines the importance of continued investigation in these areas.Practical applicationsParents and teens must be educated regarding the frequency of and the potential effects of distractions. Additional enforcement may be necessary if Graduated Driver Licensing (GDL) programs are to be effective. Systems that alert distracted teens could also be especially helpful in reducing rear-end collisions.     

Data mining approach to model bus crash severity in Australia

Introduction: Buses are different vehicles in terms of dimensions, maneuverability, and driver's vision. Although bus traveling is a safe mode to travel, the number of annual bus crashes cannot be neglected. Moreover, limited studies have been conducted on the bus involved in fatal crashes. Therefore, identification of the contributing factors in the bus involved fatal crashes can reduce the risk of fatality. Method: Data set of bus involved crashes in the State of Victoria, Australia was analyzed over the period of 2006–2019. Clustering of crash data was accomplished by dividing them into homogeneous categories, and by implementing association rules discovery on the clusters, the factors affecting fatality in bus involved crashes were extracted. Results: Clustering results show bus crashes with all vehicles except motor vehicles and weekend crashes have a high rate of fatality. According to the association rule discovery findings, the factors that increase the risk of bus crashes with non-motor vehicles are: old bus driver, collision with pedestrians at signalized intersections, and the presence of vulnerable road users. Likewise, factors that increase the risk of fatality in bus involved crashes on weekends are: darkness of roads in high-speed zones, pedestrian presence at highways, bus crashes with passenger car by a female bus driver, and the occurrence of multi-vehicle crashes in high-speed zones. Practical Applications: The study provides a sequential pattern of factors, named rules that lead to fatality in bus involved crashes. By eliminating or improving one or all of the factors involved in rules, fatal bus crashes may be prevented. The recommendations to reduce fatality in bus crashes are: observing safe distances with the buses, using road safety campaigns to reduce pedestrians’ distracted behavior, improving the lighting conditions, implementing speed bumps and rumble strips in high-speed zones, installing pedestrian detection systems on buses and setting special bus lanes in crowded areas.     

Aggregation of driver celeration behavior data: Effects on stability and accident prediction

Predictions about effects of aggregating driver celeration data were tested in a set of data where bus drivers’ behavior had been measured repeatedly over three years in a city environment. For drivers with many measurements, this data was correlated with the drivers’ accident record at various levels of aggregation over measurements. A single measurement (one sample) was seldom a significant predictor, but for each drive added to a mean, the variation explained in accident record was increased by about 1%. Also, correlations between measurements increased when these were aggregated, and the association with number of passengers (a proxy for traffic density) decreased somewhat, all as predicted. These results show that although driver celeration behavior is only semi-stable across time and environments, aggregating measurements increases both stability and predictive power versus accidents considerably. The celeration variable is therefore promising as a tool for identifying dangerous drivers, if these can be measured repeatedly, or, even better, continuously.     

大客车侧翻过程中约束系统对乘客安全影响*

为研究约束系统对客车侧翻过程中乘客安全的影响,在经过试验验证的某客车侧翻碰撞有限元模型上截取部分车身截段,建立“车身截段-约束系统-乘员”侧翻仿真模型,开展不同约束条件下乘员运动响应和损伤的综合分析及评价。结果表明:满足《客车上部结构强度要求及试验方法》（GB 17578—2013）法规要求的客车在侧翻过程中仍然可能对乘员造成较严重的头部损伤风险;主动预紧安全带能够在侧翻碰撞过程中,有效缓解乘员的头部和颈部损伤程度;胸部损伤值受不同约束系统影响较小。     

下沉式地铁车辆段环境噪声特性试验研究*

针对下沉式地铁车辆段环境噪声问题,采用问卷调查与现场实测相结合的方法,对下沉式地铁车辆段环境噪声特性开展研究。结果表明:通风噪声是下沉式地铁车辆段主要噪声源,其次为列车噪声;办公区域噪声强度超出标准限值3~5 dB（A）,其中1 000 Hz左右中频段噪声带给人的烦恼度最高;检修库内存在严重低频噪声,尽管各测点均未超过标准限值,但由于风机长期24 h运行,仍会引起员工不舒适感;上盖司机公寓内二次结构噪声强度不满足环境标准限值要求,对公寓居民睡眠产生不良影响;结构振动噪声具有明显的低频特征,主要对16~250 Hz起作用,其中250 Hz频段超标最严重。