Error Impact Analysis Research Articles

A novel simulation-based framework for sensor error impact analysis in smart building systems: A case study for a demand-controlled ventilation system

Sensors are one of the fundamental components for sensor-rich controls in buildings but are prone to different errors. Existing studies show that sensor errors hold a place among top-priority faults in building systems. Before we take countermeasures to mitigate the sensor errors, it is vital to prioritize key sensors and quantify the collective impacts of concurrent sensor errors. In response to this, a simulation-based methodology is introduced to conduct a comprehensive sensor error impact analysis in building systems, which adds a stochastic sensor prioritization through a sensitivity analysis on top of a commonly used deterministic sensor error quantification. The synergies of these two parts help better interpret the sensor error impacts on building energy consumption, ventilation performance, thermal comfort, etc. A sensor-rich CO2-based Demand-Controlled Ventilation system is used as a case study to demonstrate the viability of the methodology as a proof-of-the-concept. The results show that the energy savings potential and ventilation performance are mostly influenced by the accuracy of the AHU outdoor airflow sensors. The accuracy of zone level airflow sensors has a negligible impact on both energy savings and ventilation performance. The accuracy of zone CO2 sensors has more influence on the ventilation performance compared with the accuracy of zone airflow sensors. Compared with the baseline case with zero errors, the largest deviation percentages could reach 16.90% and 94.32%, respectively, in terms of the Heating, Ventilation, and Air-Conditioning (HVAC) annual energy consumption and the Outdoor Air Ratio (OAR) when multiple key sensors suffer from normal error intensities simultaneously.

A high-precision measurement of small roll angular displacements based on AOMs and its error impact analysis

A novel roll angular displacement measurement method based on acousto-optic modulators (AOMs) is presented, where the AOMs are adopted to reduce the frequency-difference to overcome the phase fluctuation. The novel method improves the resolution and simplifies the system configuration by reducing the optical components in the measuring light path. A mathematical model is established, and the impacts of the optical components’ error on measurement errors and magnification are analyzed in detail based on the model. The analysis results can then be used to optimize the system configuration. Experiments are carried out to validate the presented method, which show that a resolution of 0.016 arcsec has eventually been achieved.

Calibration of a camera–projector measurement system and error impact analysis

In the camera–projector measurement system, calibration is a key to the measurement accuracy; especially, it is more difficult to obtain the same calibration accuracy for projector than camera due to the inaccurate corresponding relationship between its calibration points and imaging points. Thus, based on stereo vision measurement models of the camera and the projector, a calibration method with direct linear transformation (DLT) and bundle adjustment (BA) is introduced to adjust the corresponding relationships for better optimization purpose in this paper, which minimize the effect of inaccurate calibration points. And an integral method is presented to improve the precision of projection patterns to compensate the projector resolution limitation. Moreover impacts of system parameter and calibration points errors are evaluated when the calibration points positions change, which not only provides theoretical guidance for the rational layout of the calibration points, but also can be used for the optimization of system structure. Finally, the calibration of the system is carried out and the experiment results show that better precision can be achieved with those processes.

Design of a preliminary error impact analysis model for spatial safety assessment of earthmoving operations

Regardless of technology benefits, safety planners still face difficulties explaining errors related to the use of different technologies and evaluating how the errors impact the performance of safety decision making. This paper presents a preliminary error impact analysis testbed to model object identification and tracking errors caused by image-based devices and algorithms and to analyze the impact of the errors for spatial safety assessment of earthmoving and surface mining activities. More specifically, this research designed a testbed to model workspaces for earthmoving operations, to simulate safety-related violations, and to apply different object identification and tracking errors on the data collected and processed for spatial safety assessment. Three different cases were analyzed based on actual earthmoving operations conducted at a limestone quarry. Using the testbed, the impacts of the errors were investigated for the safety planning purpose. ► This manuscript presents an error impact analysis testbed. ► It models object identification and tracking errors of devices and algorithms. ► The testbed was used to model three different earthmoving operations. ► It detected speed limit, dangerous access, and close proximity violations. ► Interviews and case studies were used for validation.

LMS Markov model and its use for power control error impact analysis on system capacity

We present a wideband land mobile satellite channel model based on a three-state Markov chain model valid for any kind of satellite constellation and for L, S, and Ka bands. Data from measurement campaigns was used to extract the parameters for the statistical distributions involved in the model. We also present a methodology describing how to use the proposed channel model to interface with system-level analysis. We use the time series generated by the model to parameterize power control (PC) imperfection as a function of the environment and user speed by acting upon the time series through a seven-level PC algorithm. We then apply the obtained parameterization to the analysis of a direct sequence-code division multiple-access scenario with users requiring different quality-of-service (QoS). It is shown that request of different QoS produces an unbalance in the users power distribution and less users can be served with the most demanding QoS. PC error worsens this effect and considerably reduces capacity efficiency which is highly dependent on the environment and mobile speed. Bit-error rate statistics are also investigated through the log-normal characterization obtained by using the channel model obtaining results on the effect of required E/sub b//(N/sub o/+I/sub o/) of a particular user.