The effect of technique and shaft configuration in snow shoveling on physiologic,kinematic, kinetic and productivity variables

A repeated measures 2 x 2 factorial design using a psychophysical experimental methodology was performed to quantify the effect of shaft design (straight and bent shaft) and shoveling technique (forward and backward progression) on heart rate, perceived exertion, productivity, trunk kinematics and load kinetics. Ten male subjects performed four 8-min trials of snow shoveling on a paved asphalt surface. The most notable finding was significantly less trunk flexion with the bent shaft (41.4 degrees ) than with the straight shaft design (49.2 degrees ). The study results led to a recommendation of a bent-shaft shovel for the purpose of reducing trunk flexion. In the absence of any strong positive evidence and due to poor subjective response to backward progression while shoveling, this technique was not recommended.     

Kinematic evaluation of two snow-shovel designs

The objective of this study was to determine how different shovel designs affect trunk motion during snow shoveling. A shovel having a straight shaft and a shovel having a bent shaft were evaluated across three levels of task asymmetry. The primary dependent variables were measures of lumbar kinematics in three directions with respect to the spine (sagittal, rotational, and frontal) recorded with a lumbar motion monitor. Ratings of perceived discomfort and measures of heart rate were also collected. In a laboratory experiment, 12 participants were required to stimulate snow shoveling in three different directions with each shovel. Results showed that the bent shovel significantly reduced the lumbar velocity and acceleration in the sagittal plane without affecting motion in the rotational or frontal planes. Most sagittal and rotational motion parameters increased significantly as throwing direction became more asymmetric. The discomfort ratings indicated that the low back, arms, and wrist were the body regions most severely affected by the task, with some evidence of differences between the two shovel designs.

Relevance to industry

The use of a bent-handled shovel will reduce lumbar sagittal flexion without increasing side bending and twisting during snow-shoveling work. However, the use of multiple shovel designs during snow removal may be needed to reduce discomfort of the upper extremities.     

Physiological and subjective measures of workload when shovelling with a conventional and two-handled (‘levered’) shovel

Previous studies have suggested that the two-handled (levered) shovel is advantageous over the conventional spade from a biomechanical point of view. The aim of this experiment was to determine whether less energy was consumed while shovelling a load of sand with this shovel compared to a conventional tool. Accordingly, an experiment was designed in which subjects (n = 10) shovelled 1815 kg sand under laboratory conditions using either a conventional or a levered shovel. Heart rate and oxygen consumption were measured continuously during the trial and subjective data on perceived exertion, general fatigue and body discomfort were recorded after the trial. Although total energy expenditure was similar under both conditions (120±20 and 125±25 kcal; conventional versus two-handled spade), average heart rate was 4% higher when the two-handled &lt;. shovel was used (p<0 05). In addition, the mass of sand per scoop was 4% less &lt;. with the two-handled shovel (p<0 05). In conclusion, subjects used similar energy expenditure to shovel 1815 kg sand with the conventional shovel and the twohandled tool despite lower mass of sand per scoop with the latter. This can be explained by the fact that the increased mass of the additional handle compensated for the lower mass of sand per scoop. The higher average heart rate while shovelling with the two-handled shovel can be explained by the more erect posture.     

Modeling Truck–Shovel Systems as Closed Queueing Network with Multiple Job Classes

In this paper an analytical method is proposed to model the truck–shovel system as a closed queueing network with multiple job classes. This approach would provide the capability of estimating system performance measures (mine throughput, mean number of trucks, mean waiting time etc.) for planning purposes when the truck fleet is not necessarily composed of identical trucks. A computational study is presented to show how choosing different types of trucks affect the production level in a truck–shovel system. Mean Value Analysis (MVA) approach is used to compute all performance measures of the truck–shovel system.     

Research on unmanned electric shovel autonomous driving path tracking control based on improved pure tracking and fuzzy control

This paper proposes a path tracking control method combining pure tracking algorithms and self-adaptive fuzzy control for autonomous driving of an unmanned electric shovel. An improved pure tracking controller was designed based on the kinematic model of heavy crawler taking both the value of deviation and its variation as inputs with the crawler speed on each side as output. The proposed controller and MPC algorithm were simulated using MATLAB for comparison. The results show that the proposed controller has more anthropomorphic characteristics than the MPC method. To verify the actual control effect of the controller, experiments were carried out using a prototype electric shovel for different working conditions. The experimental results proved that the controller is able to meet the control requirements for unmanned electric shovel path tracking.     

A comparative study of two shovel designs

In the present study a modified shovel design with two perpendicular shafts is presented. This modified, two-shaft shovel was compared with a regular shovel. The modified shovel was evaluated and tested in a controlled laboratory environment using surface electromyography recorded from the lumbar paraspinal muscles. The new shovel design was also tested in a field study using ratings of perceived exertion. The results indicate that there was a significant reduction in EMG values of the lumbar paraspinal muscles and a consistent reduction in perceived exertion ratings while the modified shovel was being used for removing dirt in digging trenches up to 90 cm in depth.     

模糊参数自整定PID控制技术在推土机自动控制系统中的应用

本文应用模糊数学理论，以推土机工作装置为对象建立数学模型和试验系统，完成在线ＰＩＤ控制器参数模型自整定的理论实现、计算机仿真和应用研究，为实现推广土机的自动控制提供理论的和试验依据。     

Influence of snow shovel shaft configuration on lumbosacral biomechanics during a load-lifting task

Lower-back injury from snow shovelling may be related to excessive joint loading. Bent-shaft snow shovels are commonly available for purchase; however, their influence on lower back-joint loading is currently not known. Therefore, the purpose of this study was to compare L5/S1 extension angular impulses between a bent-shaft and a standard straight-shaft snow shovel. Eight healthy subjects participated in this study. Each completed a simulated snow-lifting task in a biomechanics laboratory with each shovel design. A standard motion analysis procedure was used to determine L5/S1 angular impulses during each trial, as well as peak L5/S1 extension moments and peak upper body flexion angle. Paired-samples t-tests (α = 0.05) were used to compare variables between shovel designs. Correlation was used to determine the relationship between peak flexion and peak moments. Results of this study show that the bent-shaft snow shovel reduced L5/S1 extension angular impulses by 16.5% (p = 0.022), decreased peak moments by 11.8% (p = 0.044), and peak flexion by 13.0% (p = 0.002) compared to the straight-shaft shovel. Peak L5/S1 extension moment magnitude was correlated with peak upper body flexion angle (r = 0.70). Based on these results, it is concluded that the bent-shaft snow shovel can likely reduce lower-back joint loading during snow shovelling, and thus may have a role in snow shovelling injury prevention.     

Robust outdoor stereo vision SLAM for heavy machine rotation sensing

The paper presents a robust outdoor stereo vision simultaneous localization and mapping (SLAM) algorithm. It estimates camera pose reliably in outdoor environments with directional sunlight illumination causing shadows and non-uniform scene lighting. The algorithm has been developed to measure a mining rope shovel’s rotation angle about its vertical axis (“swing” axis). A stereo camera is mounted externally to the shovel house (upper revolvable portion of the shovel), with a clear view of the shovel’s lower carbody. As the shovel house swings, the camera revolves with the shovel house in a planar circular orbit, seeing differing views of the carbody top. During the swing, the SLAM algorithm builds a map of observed 3D features on the carbody and simultaneously using these landmarks to estimate the camera position. This estimated camera position is then used to compute the shovel swing angle. Two novel techniques are employed to improve the SLAM algorithm’s robustness in outdoor environments. First, a “Locally Maximal” feature selection technique for Harris corners is used to select features more consistently in non-uniformly illuminated scenes. Another novel technique is the use of 3D “Feature Clusters” as SLAM landmarks rather than individual single features. The Feature Cluster landmarks improve the robustness of the landmark matching and allow significant reduction of the SLAM filter computational cost. This approach of estimating the shovel swing angle has a maximum error of ±1° upon SLAM map convergence. Results demonstrate the improvements of using the novel techniques compared to previous methods.     

大型矿用挖掘机工作装置仿真

对大型电铲矿用挖掘机的工作装置进行仿真,结合其实际作业特点应用MSC Adams建立其工作装置模型,并对作业过程进行动力学和运动学仿真研究,详细分析各部件在工作过程中受力状况. 论文的建模及分析方法对于其它机械系统的仿真分析具有理论参考意义.     

电铲工作装置EDEM-Adams-Simulink联合动态仿真

针对电铲工作装置驱动力设计问题,使用EDEM计算挖掘阻力,计算结果与理论值一致。在Adams中建立电铲工作装置动力学模型,利用Simulink生成接近实际的提升和推压位移曲线,并将EDEM输出的挖掘阻力转化为挖掘阻力曲线,实现Adams-Simulink联合仿真。挖掘轨迹、驱动力仿真结果与理论计算结果一致。该方法可克服传统计算只取个别位姿的不足,为后续设计提供依据。     

Ergonomics study on the handle length and lift angle for the culinary spatula

The culinary spatula (turning shovel) is one of the most common cooking tools used in the kitchen in Asia. However, the culinary spatula has seldom been ergonomically investigated. When a person uses a spatula to cook food, the operations involve repetitive bent-wrist motions, such as dorsiflexion, palmary flexion, and radial and ulnar deviations. These movements may cause cumulative trauma disorders in the upper extremities, and in particular carpal tunnel syndrome. A poorly designed culinary spatula will be ergonomically inefficient and cause injury to the hand and wrist. The purpose of this study was to investigate the effects of spatula handle length and lift angle on food-frying, food-turning, and food-shoveling performance. Eight female subjects were tested using 16 different culinary spatulas, with four different handle lengths (20, 25, 30 and 35 cm) and four different lift angles (15 degrees, 25 degrees, 35 degrees and 45 ). The criterion measures included cooking performance, and rating of perceived exertion. The subjects ranked their preference after all of the tasks in the tests were completed. The results showed that: (1) The handle length had a significant influence on the cooking performance, and rating of perceived exertion. The optimal handle lengths for frying food, turning food, and shoveling food were 20, 25 and 25 cm, respectively. (2) The lift angle significantly affected the cooking performance, and rating of perceived exertion. The optimal lift angles for frying food, turning food, and shoveling food were 15 degrees, 15 degrees and 25 degrees, respectively. (3) Both the handle length and lift angle had significant effects on subjective preference. For the handle length, the 20 cm length was the best. For the lift angle, the 25 angle was the best. (4) In general, a spatula with a 20 cm handle length and 25 degrees lift angle was the best. A spatula with a 25 cm handle length and 15 lift angle was the second most preferred. (5) However, to prevent subjects from touching the edge of a hot pan, a spatula with a 25 cm handle length and 25 lift angle is suggested.     

基于微震监测技术的地下田野文物监控系统设计与实现

针对地下田野文物被盗过程中洛阳铲、爆炸等行为特点,提出基于微震监测技术的地下田野文物监控系统.通过埋藏于地表的多个地震检波器,建立检波监测网,识别多种人为行为特点,区分是否是洛阳铲、爆炸等盗窃及损坏地下田野文物的行为,从而向控制中心发出报警信号,实现对地下田野文物监控的目的.     

The optimum lift angle for the culinary spatula (turning shovel)

A culinary spatula (turning shovel) is one of the common cooking tools used in the Oriental kitchen. Since the use of a turning shovel may cause cumulative trauma to the wrist, the spatula angle for food frying, food turning, and food shovelling was investigated. The subjects were eight female students who were experienced cooks. Handle angle significantly affected both performance and subjective rating. The optimum angle is 25°.     

电铲履带系统Adams ATV动态仿真

针对重型履带系统复杂的车辆 地面力学问题，使用Adams ATV模块建立电铲整机模型，准确计算在软地面爬坡、转弯和越障等工况下履带系统的驱动力矩和支重轮受力。爬坡工况下履带系统驱动力矩仿真结果与理论值基本一致，转弯工况下驱动力矩理论值与仿真结果的相对误差在2.5%～26.2%区间；原地转弯所需驱动力矩与12.5°坡角爬坡所需驱动力矩接近。在硬地面越障时，支重轮受力最大值占整机总重力的41.8%。与实际使用值对比结果表明，仿真结果和理论计算值可作为方案设计的参考，且理论计算值偏于保守；各工况计算结果可为动力配置和后继强度设计提供依据。     

镁铁质―超镁铁质岩全谱段遥感识别模型

镁铁质―超镁铁质岩的遥感岩性识别研究一直是遥感岩石学领域的热点之一,其岩石信息对于岩浆型铜镍硫化物矿床的预测十分重要。提出一种综合利用Landsat 8、ASTER和PALSAR-2数据的镁铁质―超镁铁质岩石全谱段遥感识别模型：通过对野外采集岩石样品及光谱库中相关岩石矿物的可见光―热红外谱域的光谱测试与特性分析,结合岩石表面微波散射特性,应用特征空间,贝叶斯线性判别分析、逐步偏最小二乘回归分析等方法,创建镁铁质―超镁铁质岩性指数,并利用提出的岩性指数进行镁铁质―超镁铁质岩的初步提取,再经过基于贝叶斯决策理论的融合处理得到最终的镁铁质―超镁铁质岩石信息。结果表明:该模型能够对镁铁质―超镁铁质岩进行精准定位,识别精度达到94%以上。此外,根据遥感岩性、构造特征的解译与区内已知铜镍硫化物矿床的成矿岩体比较,推断出位于赤石山―小长山―中坡山一带以及小青山附近岩体具有一定的成矿潜力。     

镁铁质―超镁铁质岩全谱段遥感识别模型

镁铁质―超镁铁质岩的遥感岩性识别研究一直是遥感岩石学领域的热点之一，其岩石信息对于岩浆型铜镍硫化物矿床的预测十分重要。提出一种综合利用Landsat 8、ASTER和PALSAR-2数据的镁铁质―超镁铁质岩石全谱段遥感识别模型：通过对野外采集岩石样品及光谱库中相关岩石矿物的可见光―热红外谱域的光谱测试与特性分析，结合岩石表面微波散射特性，应用特征空间，贝叶斯线性判别分析、逐步偏最小二乘回归分析等方法，创建镁铁质―超镁铁质岩性指数，并利用提出的岩性指数进行镁铁质―超镁铁质岩的初步提取，再经过基于贝叶斯决策理论的融合处理得到最终的镁铁质―超镁铁质岩石信息。结果表明:该模型能够对镁铁质―超镁铁质岩进行精准定位，识别精度达到94%以上。此外，根据遥感岩性、构造特征的解译与区内已知铜镍硫化物矿床的成矿岩体比较，推断出位于赤石山―小长山―中坡山一带以及小青山附近岩体具有一定的成矿潜力。     

An intelligent approach to predict unconfined compressive strength of rock surrounding access tunnels in longwall coal mining

Unconfined compressive strength (UCS) of rocks is one of the most important parameters in rock engineering, engineering geology, and mining projects. In the laboratory determination of UCS, high-quality samples are necessary; in which preparing of core samples has several limits, as it is difficult, expensive, and time-consuming. For this, development of predictive models to determine the UCS of rocks seems to be an attractive research. In this study, an intelligent approach based on the Mamdani fuzzy model was utilized to predict UCS of rock surrounding access tunnels in longwall coal mining. To approve the capability of this approach, the obtained results are compared to the results of statistical model. A database containing 93 rock sample records, ranging from weak to very strong rock types, was used to develop and test the models. For the evaluation of models performance, determination coefficient (R ²), root mean square error, and variance account for indices were used. Based on this comparison, it was concluded that performance of fuzzy model is considerably better than statistical model. Also, the fuzzy model results indicate very close agreement for the UCS with the laboratory measurements. Furthermore, the fuzzy model sensitivity analysis shows that Schmidt hardness and porosity are the most and least effective parameters on the UCS, respectively.     

装载机工作装置CAD系统

本文论述了装载要工作装置ＣＡＤ软件（Ｓｈｏｖｅｌ Ｌｏａｄｅｒ Ｗｏｒｋｉｎｇ Ａｔｔａｃｈｍｅｔ ＣＡＤ Ｓｙｓｔｅｍ，简称ＳＬＷＡＡＤＳ）开发和研究的一般方法；担子 连杆机构动态模拟设计的方法；应用矩阵分析法建立了机构静力学分析系统；对循环分割法自适应网格生成技术进行了探讨，在此基础上建立了二维自动网格生成系统。ＳＬＷＡＣＡＤ系统是一个对装载机工作装置进行设计和分析的专业软件，该系统是通过综合     

Blade size and weight effects in shovel design

The shovel is a basic tool that has undergone only nominal systematic design changes. Although previous studies found shovel-weight and blade-size effects of shovelling, the exact trade-off between the two has not been quantified. Energy expenditure, heart rate, ratings of perceived exertion and shovelling performance were measured on five subjects using five shovels with varying blade sizes and weights to move sand. Energy expenditure, normalised to subject weight and load handled, varied quadratically with the blade-size/shovel-weight (B/W) ratio. Minimum energy cost was at B/W = 0.0676 m2/kg, which for an average subject and average load would require an acceptable 5.16 kcal/min of energy expenditure. Subjects, through the ratings of perceived exertion, also strongly preferred the lighter shovels without regard to blade size. Too large a blade or too heavy a shovel increased energy expenditure beyond acceptable levels, while too small a blade reduced efficiency of the shovelling.