Reliable system design with a high degree of diagnostic procedures for embedded systems

Maintenance starts with reliable diagnostics. Programming Logic Controllers (PLCs) are often equipped with a high degree of diagnostic procedures in order to ensure that the processing unit is functioning correctly. It is vital to verify that the system with its programme is still within a 'healthy' state, otherwise a safety function is called and the system is brought into a safe state, or if possible, defect and malfunctioning components are exchanged during operation and the process can continue without shutting down the system. However, when it comes to smaller devices such as intelligent sensors, embedded controller devices with the functionality of an e.g. PID (Proportional-Integral-Derivative), predictive controller, filter or analytical algorithm, which is embedded into a FPGA or micro-controller then diagnostics and verification methods are often not considered in the way they should be. For example, if an intelligent sensor system is not able to diagnose that the sensor-head is malfunctioning, but the sensor-head still provides some data, then the smart algorithm bases its calculation on wrong data, which can cause a dangerous situation. This paper investigates and shows recent results to combine diagnostic methods for small scale devices. Several safety-related structures are considered with a high degree of diagnostic coverage. The paper presents relevant procedures and structures to increase the reliability of small devices without utilising a full scale microcontroller system

Characterization of unique aerosol pollution episodes in urban areas using TXRF and TXRF-XANES

Identifying sources of unique, short-time aerosol pollution episodes in urban areas is a difficult task since they could last only for a couple of hours. With the combination of size-fractioned sampling with May-type cascade impactor and total-reflection X-ray fluorescence (TXRF) in addition to X-ray absorption near-edge structure spectroscopy various sources could be identified in samples collected in Budapest (Hungary) and Cassino (Italy). Using short-time (1–4 h), size-fractionated (70 nm up to 10 μm into 7 stages) sampling method, TXRF is capable of detecting transition metals in the order of 0.1 ng/m3. The present study discusses pollution episodes with Cu and Br concentrations in the range of 1–40 ng/m3. The contribution of both exhaust and non-exhaust type traffic-related emission sources were found to be dominant in the Cu species. Wear products of brake system were identified in coarse particles in addition to resuspension of roadside dust. The ratio of organic/inorganic Br could be determined for a pollution episode with elevated Br concentration