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Are you getting the frequency right?

11 July 2016

Metallic inclusions are the number one contaminant in food products. Phil Brown looks at the technologies behind effective metal detection. He explains the three key frequency options and why it is essential to select the correct frequency for your food application.  

The most widely used design of metal detector in the food industry functions on a principle known as the ‘balanced coil’. With a general-purpose search head, they are able to detect ferrous and non-ferrous metals, as well as stainless steels in fresh and frozen products – either unwrapped or wrapped – even in metallised films. However, they are still unable to detect every particle of metal passing through them.

Many factors will determine the theoretical sensitivity of a metal detector. Among them the aperture size (the smaller the aperture, the smaller the piece of metal that can be detected), the type of metal, product effect, and the type and orientation of the contaminant as it passes through the detector. Environmental conditions, such as airborne electrical interference – static, radio, earth loops – vibration and temperature fluctuation may also affect performance.

To reduce metal contaminant risks it is essential to identify the optimum frequency for any product. Many products inspected inherently have electrical conductivity and/or magnetic permeability within their makeup. For example, any product that is iron-enriched, such as cereals, will create a large magnetic signal that the detector must overcome in order to detect small pieces of metal. These are referred to as ‘dry’ products. Conversely, ‘wet’ products with high moisture and salt content, such as bread, meat and cheese, are electrically conductive.

Dry products tend to be easier in terms of detection capability, because there is no need to worry about the product effect. Equally, the sensitivity level of the wet products can be an issue, because the signature of the product needs to be taken into account. Even among wet products, bread, is very different to meat. They are both conductive, but meat contains more water, so consequently this will exhibit very different product effects.

The detector must remove or reduce this ‘product effect’ in order to identify a metal contaminant. To do this the frequency of operation needs to be changed to minimise the effect of the product. The downside is that this can impact the ability to detect different metals. Dropping frequency will enhance the ability to find ferrous metals but will limit performance when it comes to non-ferrous metals, because the lower end of the frequency is more responsive to magnetic effects of the contamination. By the same token, take the frequency higher and the reverse happens – ferrous detection capability is limited but non-ferrous detection is enhanced.

Running product samples and tests is advisable and it is important to choose the right frequency for the product.

Evolution of metal detection
In the last decade, metal detection technology has progressed significantly. Today, a food manufacturer generally has three technology options – fixed frequency, multi-frequency and simultaneous frequency.

With a single tuned-frequency device, the operating frequency has to be picked to suit the product. With a difficult conductive product like meat or cheese, or a larger product, the frequency has to be set low to deal with the product effect. That makes the system less sensitive to the detection of stainless steel and non-ferrous metals.

About 15 years ago, the introduction of selectable frequency made life a little bit easier, but the metal detector still had to be set to run at a specific frequency. In a worst-case scenario, that would be a low, less sensitive frequency.

To solve this problem, Fortress built a system with two frequencies for simultaneous inspection at a high and a low frequency. The high frequency could detect stainless steel, while the low frequency was able to identify ferrous metals. It worked really well, but was costly and difficult to build. The Interceptor range that Fortress unveiled last year builds further on this technology and improves stainless steel metal detection capability on ‘wet’ products by a further 100%, compared to the most recent generations of metal detectors. This means it can pick up metal contaminants half the dimensional size previously identifiable. Like other metal detectors, it can also reliably detect the full range of ferrous and non-ferrous metals, including stainless steel, which continues to pose the highest metal contaminant risks in the food industry.

Significant engineering and other challenges have had to be overcome to make the system more affordable for smaller-sized food manufacturers. Adding more electronics and a new coil structure brought the Interceptor system costs to only slightly more than that of a standard metal detector.

The technology works by carrying out a real-time analysis of a low frequency and a high frequency signal in parallel. Using an advanced algorithm, the Interceptor splits the product and metal detection signals and then links the readings back together. Compared to the traditional approach of tuning into specific frequencies, this new method makes it possible to identify the product effect (most noticeable at lower frequencies) and eliminate it from the higher-frequency signal, where the potential effect of the metal is more prominent.

Which technology?
So, which technology is best for today’s food production environments? A machine with a fixed frequency is good if you are consistently inspecting the same product requirements, like a chocolate bar, but there are obvious limitations if your product range is more expansive. Multi-frequency systems perform well on a range of products passing down the same production line, although the sensitivity and performance may be compromised, increasing the risk of metal contaminants going undetected. Machine operatives may still have to select the frequency, and this raises the issue of what they are basing their decision on. If its not tuned in exactly right, like a radio station, they might not select the frequency that delivers perfect clarity and sensitivity. Automatic product learning can reduce the possibility of human error. With simultaneous frequency it is more sensitive as you can ignore the product effect, making it ideal for wet products that vary in size and density, like cuts of meat, fish or blocks of cheese.

Critically, with any metal detector, there is no ‘best’ frequency. There are only ranges of frequencies, each better for different purposes. Understanding how these frequency options work and differ is fundamental to selecting the right inspection machine for your application.

Phil Brown is sales director at Fortress Technology.

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