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Quality assurance heats up: Infrared thermography is a relatively inexpensive part of a machine vision automation system that helps make sure foods are properly cooked and packages properly sealed.

In the food industry, it's essential to carefully control the temperature of perishable goods throughout production, transportation, storage and sales. Repeated warnings about infections due to tainted and improperly cooked foods highlight the need for tighter process control. Since this almost always involves a human factor, food processors need tools that automate crucial operations in a way that helps minimize human error while holding down costs. Infrared (IR) thermography is such a tool.

Automated Thermography

The main elements of automated thermography are an IR camera and associated software. They act as "smart" non-contact sensors to perform 100-percent inspections, measuring the temperature of cooked food items as they exit the cooking process. Measurement accuracy is typically [+ or -]2[degrees]C, they are easy to use, small, and can be positioned almost anywhere as needed.

IR cameras are also used to monitor cooking equipment, inspect package sealing, and improve efficiency in other food processing operations. Many IR cameras today have firmware and communication interfaces that enable their use in automated process control. Third-party software makes it easy to incorporate these tools into automated machine vision systems without the need for extensive custom written control code.

Thermography for QA and Product Safety

IR thermography is first and foremost a quality assurance (QA) tool. Controlling the quality and safety of cooked meat products is an excellent use of this technology. A permanently mounted IR camera can record the temperature of, for example, chicken tenders as they exit a continuous conveyor oven. The objective is to make sure they are done enough (reach the right temperature), but not over-cooked and dried out.

Considerable research has been conducted to correlate surface temperatures obtained through thermographic measurements with product core temperatures taken with thermocouples or other contact sensors [1]. For example, a Georgia Tech Research Institute (GTRI) Agricultural Technology Research Program study [2] found that the core temperature relative to the surface temperature of cooked chicken products depends on a number of factors. These include whether or not the chicken pieces have been breaded, how heavy that coating is, and whether the coating has been ruptured.

In addition, there is the possibility that some of the pieces may have been colder than others when they went into the oven, or may have gotten partially covered by another piece during handling or on the conveyor. In any case, pieces that come out of the oven with a temperature below or above the levels set in IR camera firmware will cause an alarm output to be triggered. This will also show up on a video or PC monitor so an operator can remove bad pieces from the conveyor.

Thermography for Microwave Precooking

GTRI also studied the use of microwave precooking to speed up subsequent cooking in a conventional conveyor oven. Their researchers found that by combining IR thermograms with visible-light images, they could avoid the non-uniform heating that sometimes occurs in microwave ovens. (Some IR cameras also have a built-in digital image camera that eliminates the need for a separate visible-light camera.) By examining both types of images, they combined information on product temperature, color, and size that led to the creation of a control algorithm that analyzes the data and allows adjustments to the microwave cooking system on the fly. This is more difficult to do in a conventional oven system.

Besides improving product quality and safety, overall throughput is increased with these thermography augmented cooking systems. An additional benefit is reduced energy costs.

Equipment Monitoring

In addition to cooked food inspections, IR thermography can also monitor the conveyor ovens. GTRI is in the process of using this to create a verification step and feedback loop to control oven temperature.

Another use of IR for conveyor ovens is monitoring temperature uniformity across the width of the cooking belt. If a heating element inside an electric oven fails, or you get uneven heating across an air impingement oven, one side of the product stream may be cooler. This can be quickly discovered with thermographic images and the IR camera's alarm system. Quality inspections of this sort are much more difficult with conventional contact type temperature sensors. Thus, IR can help correct product variability and improve quality before a lot of product needs to be scrapped.

Even microwave oven heat patterns can be monitored with IR thermography. Figure 1 is a thermogram of the interior of a microwave oven showing horizontal mode heating.

[FIGURE 1 OMITTED]

In the final cooking process it's still a good idea to periodically sample meat product core temperatures with thermocouples or other types of contact sensors. Even there, thermographic images and temperature measurements can help inspectors give more attention to products likely to be outside the acceptable temperature range.

Other Baked and Roasted Products

Recent salmonella problems seem to suggest that manufacturers of roasted nut products might benefit from thermographic inspections. As alluded to above, nuts roasted in heated air impingement ovens may be prone to uneven cooking. An IR camera can be used to inspect the roasted nuts and the oven for proper temperature.

Another possible use of IR cameras is combining temperature measurements with pattern matching for baked goods such as cookies. The temperature measurements check for doneness, while the camera's pattern matching capabilities can make sure that finished pieces conform to the required shape of the product.

Safe Packaging

Software is available that allows a thermographic vision system to learn and locate objects and patterns in the images. One application for pattern matching is in the production of frozen entrees. IR machine vision can use pattern recognition software to check for proper filling of food tray compartments.

A related application is automated 100-percent inspection of the heat-sealed cellophane cover over finished microwave entrees. IR cameras can see heat radiating from the lip of the container where the cellophane heat-seal is formed. The temperature along the entire perimeter of the package can be checked by using the camera's thermographic image with machine vision software.

An issue affecting product safety indirectly is the integrity of cartons that overwrap and protect food containers. One of the most cost effective ways of sealing overwrap cartons is to use heated glue spots on the carton flaps.

Since the glue is heated, an IR camera can "see" through the cardboard to check the pattern and size of the applied glue spots. The camera can be set up to look at predefined areas of the flaps where glue should be applied, and verify spot sizes and their temperatures. The digital data collected is used for a pass/fail decision on each box, so bad boxes can be immediately removed from the production line.

Automating Thermographic Measurements

Application software currently available provides functions that support a wide variety of food processing applications, and complement the functions built into IR cameras. The imaging tools and libraries in these packages are hardware- and language-independent, making it easy for food processing engineers to quickly implement thermographic monitoring and control systems.

This is made possible with analog and digital interfaces on the IR camera. For cameras with an Ethernet connection, such as the FUR Model A320/325 Series, digitally compressed (MPEG-4) streaming video is available for monitoring on a PC screen. In addition to local monitoring, images and alarms can be sent to a remote PC via ftp and SMTP (email) protocols.

A simplified block diagram of conveyor monitoring is shown in Figure 2. This could be representative of a conveyor oven application. One IR camera may be adequate for many applications, or an IR camera may be combined with a visible light camera to record other target object attributes.

[FIGURE 2 OMITTED]

Additional Considerations

Placing a camera directly over a conveyor line generally is not acceptable unless a protective shield is placed between it and the food to protect against possible contamination from the camera. Conventional glass and plastics that are transparent to visible light greatly attenuate IR radiation, making accurate temperature measurements nearly impossible.

One way to avoid this problem is to position the camera at an angle to the conveyor and a few feet away from it. This requires a calibration adjustment, but is a viable option. Another option is to place the camera in a food compliant enclosure with a special window that is transparent to IR energy, thereby allowing the camera to be located directly over the conveyor. These enclosures can be air or water cooled to avoid heat damage to the camera.

In automated machine vision systems, IR cameras are frequently combined with visible light cameras to record other target object variables. In the case of food processing, particularly with baked goods, color is another indication of proper cooking and product quality. With the type of software mentioned earlier, this combination of cameras can also monitor a wide range of size, shape, and temperature variables for highly sophisticated monitoring and control, plus 100-percent inspection.

References

(1.) Ibarra, Juan G.; Tao, Yang; Xin, Hongwei (in collaboration with Tyson Foods), "Combined IR imaging-neural network method for the estimation of internal temperature in cooked chicken meat", Optical Engineering, Vol. 39, No. 11, November 2000.

(2.) Sanders, Jane M., "Seeing the Unseen: Infrared computer vision system could help make meat products safer, tastier, and less costly to produce", PoultryTech: Volume 19, Number 1, Spring 2007.

Jason Styron, Automation Business Development Manager, FLIR Systems, Inc.
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Title Annotation:EXCLUSIVE FEATURE
Author:Styron, Jason
Publication:Food Manufacturing
Date:Jun 1, 2010
Words:1552
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