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The purpose of this paper is to understand the effect of engine operating conditions and lubricant friction modifier on direct acting tappet rotation. In this research work, novel method of measuring engine tappet rotation speed has been developed. The technique is so novel. It allows the measurement on real production engine with no modification to the engine tappet bore. Also, In this paper, the effect of engine operating conditions and the effectiveness of friction modifier on tappet rotation is reported.

For the very first time, for the purpose of measuring follower rotation in a real production engine, a 4 × 6 mm2 electronic chip called Gradiometer is mounted outside the tappet housing, allowing the monitoring of tappet rotation speed without the need to machine a hole in the tappet bore. This novel technique is adopted on Mercedes Benz OM464 engine to study the effect of engine conditions and lubricant chemistry on tappet performance.

The main outcome of this research work is the development of novel method of measuring tappet rotation. Also, during the experiments, it was revealed that although friction modifiers help in reducing friction at the cam/tappet interface, they can also adversely affect the tappet rotation speed.

The novel technique developed in the research work is one of the most cost effective and simple to use. Researches can adopt the technique to study the tribological performance of direct acting tappet on real production engine. Researches acknowledge the effectiveness of friction modifiers in valve train but its effect on rotation which plays a key role in the component durability has not been the focus of most of the researches mainly due to lack of effective techniques.

Presents the kinematic calibration of an H4 parallel prototype robot using a vision‐based measuring device. Calibration is performed according to the inverse kinematic model method, using first the design model then a model developed for calibration purpose. To do so, the end‐effector pose (i.e. position and orientation) has to be measured with the utmost accuracy. Thus, first the practical accuracy of the low‐cost vision‐based measuring system is evaluated to have a precision in the order of magnitude of 10μ_it;m and 10^−3° for a 1,024×768 pixel CCD camera. Second, the prototype is calibrated using the easy‐to‐install vision system, yielding a final positioning accuracy of the end‐effector reduced from more than 1cm down to less than 0.5mm. Also provides a discussion on the use of such a method on commercial systems.

Science and technology innovation policy has important strategic significance with respect to the promotion of an innovation orientation in our country, and the classification and measurement of regional science and technology innovation policy urgently require research attention.

In this paper, we use text mining and principal component analysis to analyze the classification and measurement of technology innovation policy based on data obtained from Zhongguancun Science Park.

The empirical results indicate that regional science and technology innovation policy can be divided into four types: authoritative, guiding, urgent and periodical. The key measurements are function type, intensity, resource supply, funding level and funding effectiveness.

A comparative analysis is performed to investigate the different types of regional science and technology innovation policy measurement. Additionally, the study’s limitations are discussed, and future research directions are proposed.

The purpose of this paper is to find the best way to obtain the Sagnac phase shift in the output signal of open loop interferometric fiber optic gyroscopes (IFOGs). Also, the utilized digital filtering based on FIR kaiser window for implementing the digital signal processing part is evaluated.

The approach is based on implementing four kaiser FIR filters, the coefficients of which have been obtained from SPtool. They were simulated with SPtool in the Matlab 7.1.

The results show that the chosen computational method has reliable accuracy. On the other hand, it could require low‐computational effort, and it is a simple way which is important for the signal processors.

The limitation in this paper is that the designed filters have high order and they require much time; therefore, a high‐speed device is needed. For solving this problem, it is proposed to perform some estimation by experiments.

IFOGs are used in aircraft, missiles, and new civil fields such as automobile navigation, antenna stabilization, crane control, unmanned vehicle control, wind, and renewable energy platform stabilization.

There is no other paper which has explained mathematics of IFOG implementation in the signal processing part as completely as is done here.

As a means of data acquisition for the situation awareness, computer vision-based motion capture technologies have increased the potential to observe and assess manual activities for the prevention of accidents and injuries in construction. This study thus aims to present a computationally efficient and robust method of human motion data capture for the on-site motion sensing and analysis.

This study investigated a tracking approach to three-dimensional (3D) human skeleton extraction from stereo video streams. Instead of detecting body joints on each image, the proposed method tracks locations of the body joints over all the successive frames by learning from the initialized body posture. The corresponding body joints to the ones tracked are then identified and matched on the image sequences from the other lens and reconstructed in a 3D space through triangulation to build 3D skeleton models. For validation, a lab test is conducted to evaluate the accuracy and working ranges of the proposed method, respectively.

Results of the test reveal that the tracking approach produces accurate outcomes at a distance, with nearly real-time computational processing, and can be potentially used for site data collection. Thus, the proposed approach has a potential for various field analyses for construction workers’ safety and ergonomics.

Recently, motion capture technologies have rapidly been developed and studied in construction. However, existing sensing technologies are not yet readily applicable to construction environments. This study explores two smartphones as stereo cameras as a potentially suitable means of data collection in construction for the less operational constrains (e.g. no on-body sensor required, less sensitivity to sunlight, and flexible ranges of operations).

Product performance measurements have been used to explain other business performance variables. The purpose of this paper is to propose that, regarding Mexican consumers, the “comparison-based perceived attribute performance” (CAP) approach is a better predictor of outcomes, such as satisfaction, value and loyalty, compared with the traditional measurement of “non-comparison-based perceived attribute performance” (NCAP). These two forms of assessing attribute-level performance may be considered as different constructs.

Using these two approaches, empirical tests were performed to attribute performance measurement and were conducted on products from two different categories: tequila and liquid dishwashing detergent. Regression analyses were performed using Mexican consumer samples of n=295 and n=239, respectively.

As opposed to NCAP, CAP measurements yielded higher statistical levels of satisfaction, value and loyalty for both product categories. In the case of tequila, factor analysis indicated a clear separation between the two types of measurements, suggesting that they should be considered distinct constructs. However, this was not found for the other product category.

CAP, which has better potential to predict outcomes than NCAP, could have relevant implications in brand positioning assessment and importance-performance analyses.

A multi-laser sensors-based measurement instrument is proposed for the measurement of geometry errors of a differential body and quality evaluation. This paper aims to discuss the aforementioned idea.

First, the differential body is set on a rotation platform before measuring. Then one laser sensor called as “primary sensor”, is installed on the intern of the differential body. The spherical surface and four holes on the differential body are sampled by the primary sensor when the rotation platform rotates one revolution. Another sensor called as “secondary sensor”, is installed above to sample the external cylinder surface and the planar surface on the top of the differential body, and the external cylinder surface and the planar surface are high in manufacturing precision, which are used as datum surfaces to compute the errors caused by the motion of the rotation platform. Finally, the sampled points from the primary sensor are compensated to improve the measurement accuracy.

A multi-laser sensors-based measurement instrument is proposed for the measurement of geometry errors of a differential body. Based on the characteristics of the measurement data, a gradient image-based method is proposed to distinguish different objects from laser measurement data. A case study is presented to validate the measurement principle and data processing approach.

The study investigates the possibility of correction of sensor data by the measurement results of multiple sensors to improving measurement accuracy. The proposed technique enables the error analysis and compensation by the geometric correlation relationship of various features on the measurand.

The proposed error compensation principle by using multiple sensors proved to be useful for the design of new measurement device for special part inspection. The proposed approach to describe the measuring data by image also is proved to be useful to simplify the measurement data processing.

The swivel construction method is a specially designed process used to build bridges that cross rivers, valleys, railroads and other obstacles. To carry out this construction method safely, real-time monitoring of the bridge rotation process is required to ensure a smooth swivel operation without collisions. However, the traditional means of monitoring using Electronic Total Station tools cannot realize real-time monitoring, and monitoring using motion sensors or GPS is cumbersome to use.

This study proposes a monitoring method based on a series of computer vision (CV) technologies, which can monitor the rotation angle, velocity and inclination angle of the swivel construction in real-time. First, three proposed CV algorithms was developed in a laboratory environment. The experimental tests were carried out on a bridge scale model to select the outperformed algorithms for rotation, velocity and inclination monitor, respectively, as the final monitoring method in proposed method. Then, the selected method was implemented to monitor an actual bridge during its swivel construction to verify the applicability.

In the laboratory study, the monitoring data measured with the selected monitoring algorithms was compared with those measured by an Electronic Total Station and the errors in terms of rotation angle, velocity and inclination angle, were 0.040%, 0.040%, and −0.454%, respectively, thus validating the accuracy of the proposed method. In the pilot actual application, the method was shown to be feasible in a real construction application.

In a well-controlled laboratory the optimal algorithms for bridge swivel construction are identified and in an actual project the proposed method is verified. The proposed CV method is complementary to the use of Electronic Total Station tools, motion sensors, and GPS for safety monitoring of swivel construction of bridges. It also contributes to being a possible approach without data-driven model training. Its principal advantages are that it both provides real-time monitoring and is easy to deploy in real construction applications.

This paper aims to propose a method for measuring the rotation of moving body during parabolic flight using camera.

An orthogonal matrix used to calculate the Euler angles of rotation is solved by means of singular value decomposition. The translation velocity and position of moving body are measured by a binocular camera system.

The experiment is executed in a jet aircraft to simulate micro-gravity during parabolic flight. And the human moving body is regarded as a rigid body. The results show that this method can calculate the angles effectively.

This work is useful for calculation and monitoring body’s motion in space.

The paper gives a method which measures the rotation of a rigid body under the microgravity by a binocular camera to modify the measurement error of the interferometer.

The purpose of this paper is to develop a means of the kinematic calibration of a parallel manipulator with full-circle rotation.

An error-mapping model based on the space vector chain is formulated and parameter identification is proposed based on double ball-bar (DBB) measurements. The measurement trajectory is determined by the motion characteristics of this mechanism and whether the error sources can be identified. Error compensation is proposed by modifying the inputs, and a two-step kinematic calibration method is implemented.

The simulation and experiment results show that this kinematic calibration method is effective. The DBB length errors and the position errors in the end-effector of the parallel manipulator with full-circle rotation are greatly reduced after error compensation.

By establishing the mapping relationship between measured error data and geometric error sources, the error parameters of this mechanism are identified; thus, the pose errors are unnecessary to be measured directly. The effectiveness of the kinematic calibration method is verified by computer simulation and experiment. This proposed calibration method can help the novel parallel manipulator with full-circle rotation and other similar parallel mechanisms to improve their accuracy.