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Microcontroller-based sensor systems offer great opportunities for the implementation of safety features for potentially dangerous machinery. However, in general they are difficult to assess with regard to their reliability and failure rate. This paper describes the safety assessment of hardware and software of a new and innovative sensor system. The hardware is assessed by standardized methods according to norm EN ISO 13849-1, while the use of model checking is presented as an approach to solve the problem of validating the software.
In this paper, we introduce an optical sensor system, which is integrated into an industrial push-button. The sensor allows to classify the type of material that is in contact with the button when pressed into different material categories on the basis of the material's so called "spectral signature". An approach for a safety sensor system at circular table saws on the same base has been introduced previously on SIAS-2007. This contactless working sensor is able to distinguish reliably between skin, textiles, leather and various other kinds of materials. A typical application for this intelligent push-button is the use at possibly dangerous machines, whose operating instructions include either the prohibition or the obligation to wear gloves during the work at the machine. An exemple of machines at which no gloves are allowed are pillar drilling machines, because of the risk of getting caught in the drill chuck and being turned in by the machine. In many cases this causes very serious hand injuries. Depending on the application needs, the sensor system integrated into the push-button can be configured flexibly by software to prevent the operator from accidentally starting a machine with or without gloves, which can decrease the risk of severe accidents significantly. Especially two-hand controls are incentive to manipulation for easier handling. By equipping both push-buttons of a two-hand control with material classification properties, the user is forced to operate the controls with his bare fingers. That limitation disallows the manipulation of a two-hand control by a simple rodding device.
The use of manually fed machines (e.g. table saws) bares risks of injury that are clearly above the average level of other high risk workplaces.
The wide use of such machines causes severe problems for occupational safety and implies high costs for medical treatments and accident annuities.
This thesis presents a new concept of a multispectral sensor to monitor an area in front of a danger zone to detect the user’s limbs and trigger safeguarding measures to prevent an accident in time.
The sensor concept realizes a contact-free material classification, which comprises the development of a system design and specific safety requirements with respect to international safety standards.
Furthermore, a prototypical implementation using four wavebands, which were determined for skin detection through an analysis of reflectance spectra acquired specifically for this purpose, was built.
This paper presents recent research on an active multispectral scanning sensor capable of classifying an object's surface material in order to distinguish between different kinds of materials and human skin. The sensor itself has already been presented in previous work and can be used in conjunction with safeguarding equipment at manually-fed machines or robot workplaces, for example. This work shows how an extended sensor system with advanced material classifiers can be used to provide additional value by distinguishing different materials of work pieces in order to suggest different tools or parameters for the machine (e.g. the use of a different saw blade or rotation speed at table saws). Additionally, a first implementation and evaluation of an active multispectral camera system addressing new safety applications is described. Both approaches intend to increase the productivity and the user's acceptance of the sensor technology.
Vorrichtung zur Authentifikation einer Person anhand mindestens eines biometrischen Parameters
(2008)
Die Vorrichtung zur Authentifikation einer Person anhand mindestens eines biometrischen Parameters, insbesondere anhand eines Fingerabdrucks, ist versehen mit einem Biometrie-Detektor (20) zur Detektion eines biometrischen Parameters, einem Haut-Detektor (24) zur berührungslosen Erkennung lebender menschlicher Haut innerhalb eines Erfassungsbereichs. Der Haut-Detektor (24) weist mindestens eine Gruppe aus mindestens einer Strahlungseinheit (26, 28) und mindestens einer Empfangseinheit (30) auf. Die mindestens eine Strahlungseinheit (26, 28) gibt in Richtung auf den Erfassungsbereich Strahlung bei mindestens zwei unterschiedlichen Wellenlängen im Wellenlängenbereich zwischen 400 nm und 1500 nm ab, wobei mindestens eine der Wellenlängen (26, 28) im Wellenlängenbereich von 900 nm bis 1500 nm liegt und die mindestens eine Empfangseinheit (30) aus dem Erfassungsbereich reflektierte Strahlung empfängt. Ferner ist die Vorrichtung versehen mit einer mit dem Biometer-Detektor (20) und dem Haut-Detektor (24) verbundenen Signalauswerteeinheit (22) zur Auswertung der Intensität der von der Empfangseinheit (30) empfangenen reflektierten Strahlungen der Strahlungseinheit (26, 28). In der Signalauswerteeinheit (22) ist anhand der Intensitäten der von der Empfangseinheit (30) empfangenen reflektierten Strahlungen der Strahlungseinheit (26, 28) bei den zwei unterschiedlichen Wellenlängen ermittelbar, ob der Haut-Detektor lebende menschliche Haut erkennt.
In the presented project, new approaches for the prevention of hand movements leading to hazards and for non-contact detection of fingers are intended to permit comprehensive and economical protection on circular saws. The basic principles may also be applied to other machines with manual loading and/or unloading. Two new detection principles are explained. The first is the distinction between skin and wood or other material by spectral analysis in the near infrared region. Using LED and photodiodes it is possible to detect fingers and hands reliable. With a kind of light curtain the intrusion into the dangerous zone near the blade can be prevented. The second principle is video image processing to detect persons, arms and fingers. In the first stage of development the detection of upper limb extremities within a defined hazard area by means of a computer based video image analysis is investigated.