A Tier 1 automotive supplier of brake drum assemblies with customers here and abroad has tried a number of different vision systems for brake drum assembly inspection, but have had very limited success. The main problem with the previous systems was their dependence on using pattern matching, which proved inadequate in handling the wide variations and complexities in the assemblies.

Their goal was to develop a reliable machine vision system for automated inspection of brake drum assemblies that can account for variations in the texture, glossiness, color, and shade of the components, as well as for differences in assembly. The company combined National Instruments’ (Austin, TX) Vision Development Module (including Vision Builder), NI LabVIEW, and the NI-IMAQ 1394 driver to develop core image processing algorithms, validate the developed algorithms on a large sample set, and create a highly reliable vision system.

Brake Test Requirements

The software’s user interface displays all parts being inspected.

The brake drum assembly test requirements call for the detection of the presence of various components, reversal of springs, proper locking or engagement of components, direction of assembly of geared components, angular orientation of clips, position of brake linings, the presence of threading in certain components, the presence of lettering; and gauging of diameters, lengths, and thicknesses.

The supplier needed a cost-effective test system that could meet the following requirements:

  • Flexibility — Ability to test various models of brake drums.
  • Reliability — Reliable and consistent inspection results.
  • Networking — Test results accessible over the local network.
  • Delivery — Aggressive 10-week delivery schedule for complete inspection station.
  • Compact footprint — Efficient utilization of valuable manufacturing floor space.

The company chose a 1280 × 960 pixel Sony FireWire digital camera with a number of programmable features, including more than 12 parameters such as selection of shutter speed and filter, that the engineers could configure from the application software. They used the NI-IMAQ 1394 driver software to interface with the camera.

Combining Hardware and Software

The brake inspection station consists of a rotary indexing table with a fixture mounted on it. Each type of brake assembly has a corresponding fixture. After manually mounting the brake assembly on the fixture, a pneumatic clamp prevents the assembly from moving. A centralizing mechanism makes sure that the brake shoes are centralized before the imaging process starts.

The supplier used a high-resolution IEEE 1394 camera with a corresponding PCI card. A software-controlled motorized zoom lens provided access to the full resolution of the camera for different brake models. Polarizers were provided to reduce the effects of glare from highly reflective components, and high-frequency lighting sources with the ability to control intensity through software were chosen.

The rotary table guarantees that all four quadrants of the brake assembly can be imaged separately so as to increase the available resolution. The images thus captured are transferred to the PC for analysis. The custom-built software analyzes the images using various techniques and actuates the marking mechanism based on whether the drum is accepted or not.

Software played a critical role in the success of the system. Some visual variations in components are considered normal for an “under the hood” application. In addition, the presence, absence, or shift in position of the components in the background affects detection of components, and shifting of the brake shoes — though limited to an extent by the centralizing mechanism — also poses a challenge.

The brake has a different base color, which explains how typical image processing fails when under-the-hood component color contrast varies.

Custom algorithms were built because pattern matching was unreliable for the conditions mentioned above. For example, one algorithm was designed to detect reversal of a spring. Every time a new algorithm was created or an existing one was altered, the supplier had to validate it over hundreds of brake assembly images to ensure that it was reliable over the entire sample set. National Instruments Vision Builder, with its batch processing capabilities, accomplished this task.

To be certain that the system worked well, an adaptive technique was used where certain parameters in the algorithm, such as threshold value, were iteratively changed until the appropriate feature was found. If at the end of the iteration the feature was not found, it was concluded that it was not present. Based on the images from the sample set, the supplier was able to identify a range that could be used for these iterations, thereby reducing the processing time required. Threshold values were changed iteratively from 50 to 100 in steps of five until a single particle of a certain area remained.

Adapting to Variations in Components

A fully automated brake inspection system was built using virtual instrumentation and machine vision technology during a period of 10 weeks. Custom-built, self-adapting algorithms were used to ensure reliable inspection irrespective of the wide variations in the components. The system also gives customers complete flexibility in choosing which features are inspected and the inspection criteria, so it is very easy to change from one model to another.

Whereas defect analysis was not possible with other configurable machine vision systems, with the new system, customers can use statistical details on various defects to curb problems in raw materials and upstream processes at the source. Finally, the system makes customized reports accessible over the network.

More Information

For more information on National Instruments’ machine vision hardware and software, visit http://info.hotims.com/15132-153.

Imaging Technology Magazine

This article first appeared in the June, 2008 issue of Imaging Technology Magazine.

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