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Coaxial connectors can be better
| Coaxial connectors can be better |
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Modern RF and microwave electronics make it possible to work with low amplitude signals and poor signal-to-noise ratios. These improvements enable advanced communications and measurement systems.
Over a dozen basic types of coaxial connector are available, designed to match application requirements (for example, the APC range developed by Agilent and Amphenol consists of three types for frequencies ranging from DC to 50 GHz). Connector technology and design is continually improving, driven by market requirements, and enabled by improvements in materials, manufacturing methods and computer simulation. Much of the coaxial connector industry still designs products with the aid of analytic models, followed by prototype manufacture, measurement and evolution. This process takes time, and costs money. Computer simulation is far more efficient, especially now that there are products tailored for this application. To illustrate this, the design of a 7 mm precision coaxial connector will be used to show what can be achieved in less than an hour, including the time for production of the CAD models for manufacturing. The Concerto AS design software is used for this example. This software takes a novel approach to the coaxial connector design problem. It exploits the radially symmetric nature of these components to simplify design, by taking a 2D axisymmetric slice out of the connector model and simulating this (see sidebar: 'Slicing complex simulation problems down to size')
First, a parametric model of the connector is specified using the program's built-in modelling tool, based on the industry-standard ACIS geometry engine. A basic connector configuration is created with input and output connections to standard 50 ohm air lines (Figure 1). Materials for the insulators and supports were selected from a library and the dimensions of the insulators, conductor supports and conductors in the connector were defined (in this instance as variables, so that they could be changed with ease to optimise the design). The initial dimensions of the variables were determined from an analytic model, but this produced a connector with only 10 dB return loss.
Design optimisation can be performed manually by simply varying parameters in the model, or automatically by employing an optional tool. In this instance, the latter approach is used, and the software's finite difference time domain (FDTD) optimiser is configured to minimise the return loss by varying the dimensions of the connector within specified ranges (Figure 2). The program uses a combination of 'local descent' and stochastic algorithms to achieve the specified goals in the defined range of the variables. In less than 50 optimisation iterations the program produced a design with a return loss of better than 36 dB between 1 and 25 GHz. Figure 3 shows a screen image during the optimisation process. The average value of the return loss over the frequency range is being minimised and one of the graphs shows this as a function of the optimisation iterations.
Figure 4 shows the initial and optimal return loss as a function of frequency. This total sequential optimisation process was completed in five minutes on a 2.4 GHz PC, a speed made possible because the program uses a 2D FDTD method tailored to this application. In total, with the model building process, this example application was completed in well under an hour. Producing a viable optimised design is only the first stage. The software can also be used to examine the potential of the connector to support higher order modes that would limit the useful upper frequency, and to look at sensitivity to manufacturing and material tolerances. Computer simulation can thus be used to perform controlled experiments and make measurements that would be prohibitively expensive using prototypes. Computer simulation of connectors gives the same measurements that would be obtained on the bench. Uniquely, simulation can also display what happens to the fields and currents inside the connector, helping to produce the insight needed to guide innovative design changes. Another advantage is that the characteristics of the device being measured are specified exactly. Material dielectric constants and losses are known, dimensions are precise; in other words there are no concerns about spurious results resulting from one-off errors in test piece manufacture. Further, the sensitivity of the design to material variations and manufacturing tolerances may also be studied with complete confidence that trends will be correctly predicted. Computer simulation is easily integrated into the design and manufacturing cycle. The RF and microwave market has burgeoned over recent years with the explosion in mass-market applications, and this has created a large market for connectors. However, the applications demand high performance, while the market demands low cost and short product time cycles. Computer simulation methods now enable connector manufacturers to take better advantage of the opportunities presented.
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In such applications connectors play a critical role, since each contributes to signal degradation, be it loss, dispersion or intermodulation distortion. In many systems, particularly those aimed at the mass market, careful selection is required to balance cost against performance. On the other hand, the design of measurement system connectors is perhaps less driven by cost, but they must meet stringent quality requirements. Although nowadays measurement systems routinely user error correction to provide high accuracy and dynamic range, in practice, the achievable measurement system performance is dependent on the performance and repeatability of the system connectors. This article introduces a novel automated design approach that addresses that needs of designers and manufacturers of connectors for these markets.


When a final design is completed, the Modeller can output a CAD model for manufacturing, using a variety of industry standard formats, thus reducing the chance of errors and minimising time to manufacture. Equally, the Modeller can import CAD data, so that the effect of essential manufacturing changes can be rapidly predicted.

