# Measuring Rotational Speed Sensor

## Summary

In this report arithmetical representations are suggested for measuring rotational speed and cycle difference of speed sensors. The suggested arithmetical representations are used in parameter maximization and gear wheel blueprint of Hall Effect rotational speed detectors and measuring methods. Experiment outcomes indicate that the mathematical representations are very important and valuable for the design and measurement of rotational speed sensors.

## Introduction

Rotational speed sensors and mathematical models are broadly utilized in industrial machines, production systems, robots and automotive sector for measuring, monitoring and controlling generators, motors, spindles of various rotating instruments.

There are many rotational speed determining techniques. The most commonly utilized techniques are rotational signal counting techniques utilizing proximity switches, programmers and gear tooth sensors (Hernandez 407; Kirianaki 427; Liu and Zhe 84). Such devices have a comparative high resolution. Their demerits are costly and small frequency spectrum. A further sensor built-in the encoder is required for sensing the direction of rotation (Hernandez 405; Johnson 26).

Rotating speed detectors function based on certain standards. Such detectors utilize a metal gear in order that they are simple and inexpensive for industrial uses. Therefore the sensors find increasing uses in industrial sector. However, basic study of gear tooth speed detectors with dual yields is still incomplete until now.

This report describes arithmetical equations for measuring the metrics of rotating speed detectors. The suggested arithmetical representations are used in Hall Effect detector (Liu and Zhe 85). Experiment outcomes indicate that the mathematical representations are very important and valuable for the parameter maximization, design and application of rotational speed detecting devices.

The first section of this paper gives mathematical models. The second part gives the experiment results, measuring systems, phase drift between the impulse outputs and duty cycle of the impulse outcomes. The third part gives applications of the sensors. The last part of this report gives the conclusions drawn from this study.

## Arithmetical Representations

As indicated in figure 1, two sensors separated by a distance, a, are integrated in the detector. The sensors detect the rider of the target wheel consistent with various physical standards, for example capacitive, Hall Effect, inductive standards.

With “N” as the number of teeth of the target wheel, “T” as the time period and “f” as the frequency of impulse is determined by

The phase shift can be determined by:

In such case the phase difference and cycle depends simply on geometric metrics L1, L2 and the separation between the two sensors, a. One can utilize such expressions to design the wheel comparative easily (Hernandez 66; “Allegro Micro Systems” par. 3).

## Experiment results

### Impulse outputs

The impulse outputs of one final impulse of the detector are indicated below (see table 1). All utilized wheels have 6 teeth and external diameter of 28 mm, and diverse arithmetical impulses (Pallas-Areny 28; Pascal and Friz 37).

Utilizing these measured values one can formulate a regressive linear expression: Figure 4: Graphical representation of measured duty cycle values and regressive trend as function of L1/L. Figure 5: Duty phase of one final impulse of the detector as function of detecting distance.

in detecting distance range from 1.70mm to 3.70mm. Thus the equations (7) and (10) can be utilized for approximating the output impulses of rotational measuring devices during design (Patrascoiu and Sochirca 169; Papoulis 35).

## Conclusions

Based on the test outcomes one can conclude that:

• The difference between the two outputs can be calculated by use of the representations (4) and (9). The comparative variation of the metric determination is within .
• The net effect determinant of the gear wheel can be approximated by linear equation by use of the measuring values of duty cycles of the dual outputs at various arithmetical duty cycle of the gear wheel.
• The geometric equations suggested in this report can be used for calculating the metrics of the gear wheel and other metrics of the rotational speed sensing devices.
• The representations are very practical for evaluating gear tooth detectors with two output signals and very effective and supportive for the design and analysis of rotational speed sensing devices.

The additional studies should be focused on the model-oriented development of the rotational speed detectors and measuring devices so as to maximize the measuring device and save the development period and costs.

## Works Cited

“Allegro Micro Systems, Inc.: ATS617LSG, Dynamic, Self-Calibrating, Peak-Detecting, Differential Hall Effect Gear Tooth Sensor IC.” Data Sheet (2010): n.pag. Web.

Hernandez, Wilmar. “Improving the response of a wheel speed sensor by using frequency-domain adaptive filtering.” IEEE Sensors Journal 3 (2003): 404-413. Print.

Hernandez, Wilmar. “Improving the Response of Wheel Speed Sensors by using Robust and Optimal Signal Processing Techniques.” IEEE International Symposium on Industrial Electronics 4 (2005): 403-416. Print.

Hernandez, Wilmar. “Improving the Response of a Wheel Speed Sensor by Using a RLS Lattice Algorithm.” Sensors 6 (2006): 64-79. Print.

Johnson, Charles. Process Control Instrumentation Technology. 5th ed. 1997. Upper Saddle River, New Jersey: Prentice-Hall. Print.

Kirianaki, Yurish. “High Precision Wide Speed Range Rotation Sensing with UFDC-1.” Sensors & Transducers Magazine 59.9 (2005): 426-431. Print.

Liu, Ji-Gou and Zheng Zhe. “Mathematical Models of Gear Tooth Speed Sensors with dual outputs.” Joint International Symposium: proceedings of a Conference Held 2011 at Germany. Canberra: Department of Technology, 2011. 82 – 86. Print.

Liu, Ji-Gou. “Hall Effect Gear Tooth Sensors CYGTS104.” Data Sheet, ChenYang Technologies GmbH and Co. KG (2009): n.pag. Web.

Pallás-Areny, Webster. Sensors and Signal Conditioning. 2nd ed. 2001. New York: John Wiley & Sons. Print.

Papoulis, Pillai. Probability, Random Variables, and Stochastic Processes. 4th ed. 2001. New York: McGraw-Hill. Print.

Pascal, Desbiolles and Achim Friz. “Development of High Resolution Sensor Element MPS40S and Dual Track Magnetic Encoder for Rotational Speed and Position Measurement.” Technical Review 75.1 (2007): 36-41. Print.

Patrascoiu, Poanta and Tomus Sochirca. “Virtual Instrumentation used for Displacement and Angular Speed Measurements.” International Journal of Circuits, Systems and Signal Processing 2.5 (2011): 168-175. Print.