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Suggests that the arousability theory of intelligence and personality of Robinson (1996) lacks two important factors: the influence of neural transmission errors and of hemisphericity on intelligence and personality. It is considered that at least two factors contribute to intelligence. The first factor is the potential energetic level of Hebb’s engrams, which may be related to arousability. The second factor is the probability of neural transmission errors. It is suggested that the theory of H.J. Eysenck, that a neural message is sent repeatedly until it is accepted identically a certain number of times, which is smaller for more intelligent subjects, is correct.

Angular errors in the robot axes can make a significant contribution to robot positioning accuracy. This paper seeks to propose a new measuring method for measuring angular errors.

New techniques were devised for the detailed investigation of joint angular errors using a reference encoder together with a precision electronic level and autocollimator. This equipment enabled vertical and horizontally orientated joint axes to be measured with the robot located on‐site. Circle contouring measurements were also undertaken to assess the significance of multi‐axis movements on the accuracy of the end effector.

The technique, devised using a simulation program for the robot geometry with results from a circular test, enables robot errors to be characterised in terms of datum location error, backlash, gear transmission error, axes misalignments and joint encoder offset.

The paper describes the experimental and theoretical accuracy characteristics of an articulated industrial robot. Close correlation was obtained between the experimental and theoretical results. This paper offers the practical robot calibration method for industrial application.

Considers the thesis that intelligence differences and EEG‐intelligence correlations can both be explained in terms of differences in the frequency of neural transmission errors. Considers an alternative theory which holds that intelligence variance and correlated EEG variance are both caused by variation of cerebral arousability. Refers to technical and methodological problems that bedevil the EEG‐intelligence literature and measurement difficulties that have arisen through lack of adequate concepts. Concludes that the principal measurement problems derive from failure to appreciate the important distinction that must be made between “cerebral arousal” and “cerebral arousability”; and that any useful EEG‐intelligence concept must go beyond vague and general ideas such as “neural efficiency” or “neural transmission errors” to explain how EEG differences relate to differences in brain function that can account for the main facts recorded in the intelligence literature.

The purpose of this article is to present a method for the analysis of the quality of the bevel gear at the development level.

A non-commercial aircraft bevel gear design support system was developed. The system utilises matrix and vector calculi to model the technological machining systems and to analyse the contact of the designed pair. Both the technological model and the design model offer the possibility of manipulating the calculated parameters. This enables independent selection of the pinion/gear engagement, making it possible to achieved the desired contact pattern (its shape, position and size) and/or minimise motion transmission deviation. This article presents an analysis of the meshing of the aircraft transmission designed in two variants.

The newly developed non-commercial transmission design support system offers the capability to freely adjust mesh quality indicators. The first step is to perform automated technological calculations for a specific geometry of gear members, on the basis of which gear and pinion flanks are developed. Then, numerical models of tooth flanks are configured in the designed pair, and tooth mesh quality is verified. Quality indicators are provided in the form of summary contact pattern and the motion graph. In the subsequent step, changes are made to basic geometry of pinion tooth flank. After satisfactory mesh indicators have been reached, the transmission is tested for assembly errors and additional corrections are made to the geometry of the pinion tooth surface, as required. The above methodology guarantees that the assumed quality indicators are achieved on the physically cut transmission.

Fast preparation of the technology with guaranteed high mesh quality is a significant factor in the competitiveness of an industrial plant which implements a new bevel gear in its manufacturing activities.

The visualisation of the results of the use of the application allows the user to easily interpret the analysed contact pattern and take appropriate decisions as to the necessity of making corrections.

Irregular windy loads are loaded for a wind turbine. This paper aims to determine the form of gear failure and the working life of the gear system by assessing the dynamic strength of gears and dynamic stress distribution.

The helical planetary gear system of the wind turbine growth rate gearbox was investigated, and while a variety of clearance and friction gear meshing processes were considered in the planetary gear system, a finite element model was built based on the contact–impact dynamics theory, solved using the explicit algorithm. The impact stress of the sun gear of the planetary gear system was calculated under different loads. An integrated planetary gear meshing stiffness, and the error of system dynamic transmission error were investigated when the planetary gear meshes with the sun or ring gears.

The load has little effect on the sun gear of the impact stress which was known. The varying stiffness is different while the planetary gear meshes with the sun and ring gears. There were differences between the planetary gear system and the planetary gear, and with load, the planetary gear transmission error decreases.

This study will provide basis knowledge for the planetary gear system.

In traditional calibration methods of kinematics parameters of industrial robots, dozens of model parameters are identified together based on an optimization procedure. Due to different contributions of model parameter errors to the tool center point positioning error of industrial robots, obtaining good results for all model parameters is very difficult. Therefore, the purpose of this paper is to propose a sequential calibration method specifically for transmission ratio parameters, which includes reduction ratios and coupling ratios of industrial robot joints.

The ABB IRB 1410 industrial robot is considered as an example in this study. The transmission ratios for each joint of the robot are identified using the spatial circle fitting method based on spatial vectors, which fit the center and radius of joint rotation with the least squares optimization algorithm. In addition, a method based on the Rodrigues’ formula is designed and presented for identifying the actual coupling ratio of the robot. Subsequently, an experiment is carried out to verify the proposed sequential calibration method of transmission ratios.

In this experiment, the actual positions of the linkages before and after joint rotations are measured by a laser tracker. Accurate results of the reduction ratios and the coupling ratios are calculated, and the results are verified experimentally. The results show that by calibrating the reduction ratios and coupling ratios of the ABB robot, the rotation angle errors of the robot joints can be reduced.

The authors propose a sequential calibration method for transmission ratio parameters, including reduction ratios and coupling ratios of industrial robot joints. An experiment is carried out to verify this proposed sequential calibration method. This study may be beneficial for calibrating the kinematic parameters of industrial robots and improving their positioning accuracy.

Owing to the excellent performance, giant magnetostrictive materials (GMMs) are widely used in many engineering fields. The dynamic Jiles–Atherton (J-A) model, derived from physical mechanism, is often used to describe the hysteresis characteristics of GMM. However, this model, despite cited by many different literature studies, seems not to possess unique expressions, which may cause great trouble to the subsequent application. This paper aims to provide the rational expressions of the dynamic J-A model and propose a numerical computation scheme to obtain the model results with high accuracy and fast speed.

This paper analyzes different published papers and provides a reasonable form of the dynamic J-A model based on functional properties and physical explanations. Then, a numerical computation scheme, combining the Newton method and the explicit Adams method, is designed to solve the modified model. In addition, the error source and transmission path of the numerical solution are investigated, and the influence of model parameters on the calculation error is explored. Finally, some attempts are made to study the influence of numerical scheme parameters on the accuracy and time of the computation process. Subsequently, an optimization procedure is proposed.

A rational form of the dynamic J-A model is concluded in this paper. Using the proposed numerical calculation scheme, the maximum calculation error, while computing the modified model, can remain below 2 A/m under different model parameter combinations, and the computation time is always less than 0.5 s. After optimization, the calculation speed can be enhanced with the computation accuracy guaranteed.

To the best of the authors’ knowledge, this paper is the first one trying to provide a rational form of the dynamic J-A model among different citations. No other research studies focus on designing a detailed computation scheme targeting the fast and accurate calculation of this model as well. And the performance of the proposed calculation method is validated in different conditions.

Robinson and Behbehani (1997) contended against Fidelman (1996) and argued that neural transmission errors influence neither EEG nor intelligence. They also contended the suggestion of Fidelman (1996) that the mean hemisphericity of a sample may determine the sign of the correlation between IQ and the averaged evoked potentials (AEP) measures of string length and amplitude. These contentions are answered.

The purpose of this paper is to report the findings of a study that used measurements of shaft relative rotational position, made using inexpensive Hall Effect sensors and magnets mounted at the ends of a gearbox input and output shafts, to determine gear “transmission variance.” The transmission variance signals, as a function of gear/shaft rotational position, were then used to detect and diagnose gear faults.

Two sets of spur gears (one plastic and one steel) were used to experimentally determine the relative shaft rotational position between the input and the output gearbox shafts. Fault-free and faulted (damaged tooth faces and cracked tooth bases) gears were used to collect representative dynamic signals. Signal processing was used to extract transmission variance values as a function of shaft rotational position and then used to detect and diagnose gear faults.

The results show that variations in the relative rotational position of the output shaft relative to that of the input shaft (the transmission variance) can be used to reveal gear mesh characteristics, including faults, such as cracked or missing gear teeth and flattened gear tooth faces, in both plastic gears and steel gears under appropriate (realistic) loads and speeds.

The operational mode of the non-contact rotational position sensors and the dynamic accuracy limitations are explained along with the basic signal processing required to extract transmission variance values.

The results show that shaft rotational position measurements can be made accurately and precisely using relatively inexpensive sensors and can subsequently reveal gear faults.

The inexpensive and yet trustworthy fault detection methodology developed in this work should help to improve the efficiency of maintenance actions on gearboxes and, therefore, improve the overall industrial efficiency of society.

The method described has distinct advantages over traditional analysis methods based on gearbox vibration and/or oil analysis.

The need for standards allowing computer‐to‐computer communication, and examples of technical issues are discussed. The framework of the Open Systems Interconnection Reference Model, consisting of seven layers, each performing a distinct and defined function, is explained and illustrated. Sidebars feature: 1) public data networks and X.25, 2) OSI standards, and 3) the OSI layer functions. A glossary is included.