Digital twin-based analysis of volumetric error mapping procedures

The evaluation of the volumetric accuracy of a machine tool is an open challenge in the industry, and a wide variety of technical solutions are available in the market and at research level. All solutions have advantages and disadvantages concerning which errors can be measured, the achievable uncertainty, the ease of implementation, possibility of machine integration and automation, the equipment cost and the machine occupation time, and it is not always straightforward which option to choose for each application. The need to ensure accuracy during the whole lifetime of the machine and the availability of monitoring systems developed following the Industry 4.0 trend are pushing the development of measurement systems that can be integrated in the machine to perform semi-automatic verification procedures that can be performed frequently by the machine user to monitor the condition of the machine. Calibrated artefact based calibration and verification solutions have an advantage in this field over laser based solutions in terms of cost and feasibility of machine integration, but they need to be optimized for each machine and customer requirements to achieve the required calibration uncertainty and minimize machine occupation time.This paper introduces a digital twin-based methodology to simulate all relevant effects in an artefact-based machine tool calibration procedure, from the machine itself with its expected error ranges, to the artefact geometry and uncertainty, artefact positions in the workspace, probe uncertainty, compensation model, etc. By parameterizing all relevant variables in the design of the calibration procedure, this simulation methodology can be used to analyse the effect of each design variable on the error mapping uncertainty, which is of great help in adapting the procedure to each specific machine and user requirements. The simulation methodology and the analysis possibilities are illustrated by applying it on a 3-axis milling machine tool.     

Pre-compensation of servo tracking errors through data-based reference trajectory modification

This paper presents a new dynamic error compensation approach with novel data-based closed-loop tuning scheme to enhance tracking accuracy of machine tool feed-drives. Both servo dynamics and friction disturbance induced positioning errors are pre-compensated by modifying the reference trajectory. Velocity and acceleration profiles of reference trajectory are modulated to achieve perfect tracking. Reference position profile is modified based on the pre-sliding friction regime to eliminate quadrant glitches. Optimal error compensation is achieved by a digital trajectory pre-filter whose parameters are tuned automatically by making on-the-fly iterative adjustments. Effectiveness of proposed compensation approach is validated experimentally in multi-axis feed-drive systems.     

Recognition of occupational therapy exercises and detection of compensation mistakes for Cerebral Palsy

Depth camera-based virtual rehabilitation systems are gaining attention in occupational therapy for cerebral palsy patients. When developing such a system, domain-specific exercise recognition is vital. To design such a gesture recognition method, some obstacles need to be overcome: detection of gestures not related to the defined exercise set and recognition of incorrect exercises performed by the patients to compensate for their lack of ability. We propose a framework based on hidden Markov models for the recognition of upper extremity functional exercises. We determine critical compensation mistakes together with restrictions for classifying these mistakes with the help of occupational therapists. We first eliminate undefined gestures by evaluating two models that produce adaptive threshold values. Then we utilize specific negative models based on feature thresholding and train them for each exercise to detect compensation mistakes. We perform various tests using our method in a laboratory environment under the supervision of occupational therapists.     

Thermal error compensation of a 5-axis machine tool using indigenous temperature sensors and CNC integrated Python code validated with a machined test piece

Achieving high workpiece accuracy is the long-term goal of machine tool designers. There are many causes for workpiece inaccuracy, with thermal errors being the most common. Indirect compensation (using prediction models for thermal errors) is a promising strategy to reduce thermal errors without increasing machine tool costs. The modelling approach uses transfer functions to deal with this issue; it is an established dynamic method with a physical basis, and its modelling and calculation speed are suitable for real-time applications. This research presents compensation for the main internal and external heat sources affecting the 5-axis machine tool structure including spindle rotation, three linear axes movements, rotary C axis and time-varying environmental temperature influence, save for the cutting process. A mathematical model using transfer functions is implemented directly into the control system of a milling centre to compensate for thermal errors in real time using Python programming language. The inputs of the compensation algorithm are indigenous temperature sensors used primarily for diagnostic purposes in the machine. Therefore, no additional temperature sensors are necessary. This achieved a significant reduction in thermal errors in three machine directions X, Y and Z during verification testing lasting over 60 h. Moreover, a thermal test piece was machined to verify the industrial applicability of the introduced approach. The results of the transfer function model compared with the machine tool's multiple linear regression compensation model are discussed.     

Comparison of OWAS,RULA and REBA for assessing potential work-related musculoskeletal disorders

This study compared three representative observational methods for assessing musculoskeletal loadings: Ovako Working Posture Analysis System (OWAS), Rapid Upper Limb Assessment (RULA), and Rapid Entire Body Assessment (REBA). The comparison was based on 209 cases of upper-body musculoskeletal disorders (MSDs) diagnosed by medical doctors. The most awkward/stressful posture in each participant's tasks was assessed using these techniques. Postural loadings were rated more highly by the RULA than by the OWAS and REBA (p < 0.01). The chi-square test and logistic regression analysis showed that only RULA grand score and action level, and REBA action level were associated with MSD work-relatedness (p < 0.01, p < 0.05, and p < 0.05, respectively). The percentage concordant values of the logistic model for the RULA grand score and action level were 52.4% and 44.8%, respectively, while the percentage concordant value for the REBA action level was 22.1%. Therefore, the RULA may be the best system for estimating the postural loads and work-relatedness of MSDs.Relevance to industryWork-related musculoskeletal disorders are the leading cause of workplace disability in the developed countries. For preventing the disorders, quantification of musculoskeletal loads is required.     

红外一氧化碳检测中干扰因素分析及补偿方法研究

不同气体对红外光有着不同的吸收光谱。某种气体的特征光谱吸收强度与该气体的浓度相关，利用这一原理可以测量气体浓度。利用红外光谱吸收原理检测一氧化碳（CO）是一种先进的检测手段，目前国内外用于精确测量和标定气体浓度的传感器基本上都是采用红外技术。这种传感器可采用敞开式气室结构，不进行气体预处理，直接进行在线测量，容易实现自动连续监测。然而在传感器的实际研制中，必须考虑如下这些干扰因素的影响，     

矿用电压补偿器的智能控制

针对电压补偿问题,研究以嵌入式微处理器为核心的智能电压补偿器,有效地控制了输出电压,提高了设备的可靠性。文章详细介绍了系统的硬件设计原理以及软件流程。     

通用智能积算仪

本文介绍一种采用单片计算机的集比例、开方、补偿三种积算仪功能于一体的通用智能流量积算仪。它具有结构简单、通用性强、精确度高、调校使用方便等优点。     

规范矿产资源补偿费征管促进依法征费

通过分析补偿费征收管理规范化过程中存在的问题,有针对性地实施了六大举措,促进了全市补偿费征管规范化.     

被动段扰动引力对闭路制导的影响及补偿方法研究

针对被动段扰动引力对弹道式飞行器落点精度的影响问题,提出闭路制导对被动段扰动引力的实时补偿方法。建立动坐标系下自由段运动模型,导出由被动段摄动量计算落点位置的计算公式;分析扰动引力对闭路制导精度的影响机理,得出被动段扰动引力对闭路制导的影响仅与关机点位置相关的结论;进一步利用均匀设计理论,将被动段摄动量拟合为关机点位置偏差的函数,提出将摄动量作为扰动引力修正项引入闭路制导回路的实时补偿方法。仿真结果表明:验证补偿后落点偏差小于5 m,满足制导精度要求。