J. Jayanthi, CSIR-NAL
Performing real-time demonstration and visualization of a data validation algorithm used in Saras Aircraft PT1-N safety-critical systems, with time constraints of 25 ms.
Designing the algorithm in LabVIEW code and simulating the same by acquiring real-time inputs from sensor data for validation, and simulating input generation and verifying the validation algorithm embedded in the safety-critical system.
J. Jayanthi - CSIR-NAL
Manju Dr. Nanda - CSIR-NAL
G. Shamsundar Dhage - CSIR-NAL
Kushal K S - CSIR-NAL
John Atlan - CSIR-NAL
National Aerospace Laboratories (NAL), a constituent of the Council of Scientific and Industrial Research (CSIR), is the only civilian aerospace research and development (R&D) organization in India. CSIR-NAL has several advanced facilities and many recognized National Facilities, which are the best in India and on par with facilities in other countries. CSIR-NAL’s globally recognized competence has also led to notable R&D successes, innovative technology developments, and advanced testing capabilities.
NAL is India’s second largest aerospace firm after Hindustan Aeronautics Limited (HAL). The firm closely operates with HAL, DRDO (Defence Research Development Organization), ISRO (Indian Space Research Organization), and other national and international aerospace organizations. CSIR-NAL has also added valuable input to all national aerospace programmes. Its contributions over the last five decades have helped create a niche for itself in the areas of advanced aerospace research and technology development.
An algorithm was designed for validating the inputs received in analog, discrete, and ARINC (Aeronautical Radio, Incorporated) formats by the safety-critical systems in Saras Aircraft. The algorithm designed validates at miniscule time constraints in units of milliseconds. Since the algorithm is employed in safety-critical systems, we need to verify and validate its performance for certification. The setup to test the algorithm in the dedicated NAL lab could not demonstrate the algorithm working due to time constraints. Hence, we could not verify and validate the functionality for certification.
For safety-critical systems employed in aircrafts, the data acquired must be valid for the system to perform efficiently. If the data is invalid and not validated as per the requirement and standard guidelines, then the whole system is affected by the erroneous data. Data validation is an important task in the system life cycle.
Saras aircraft acquire data in analog, discrete, and ARINC formats. Any airborne system is prone to erroneous data due to external factors such as sensor errors, calibration errors, EMI effects, transmission errors, and more. Algorithms dedicated for analog data, discrete data, and ARINC data perform the validation individually against the requirements of the system.
We perform analog data validation in the time frame of 250 ms, wherein we monitor the voltage value corresponding to the input physical data. We compared the variation in the voltage to the threshold specified by the system requirements. We validated the discrete input under the time frame of 500 ms. We validated ARINC input based on refresh rate and sign status matrix bit corresponding to the data label.
The algorithm is hard to verify and validate since the operational time frame is so small in the hardware/software integration test bed available. Since the validation of the algorithm is a mandate in the process of certification, we chose NI real-time DAQ systems to simulate the algorithm’s functionality. We used LabVIEW software with NI MAX and PXI DAQ modules from NI to build a model based on the validation algorithm requirements and demonstrate the same to the certification authority.
We performed the algorithm validation in two ways. First, we generated the data input for the safety-critical system using LabVIEW by adding noise, transition errors, and SSM bit errors in the input. We fed this input to the test setup and viewed the outcome. Second, we designed models as per the software requirement (like the software embedded in the hardware) in LabVIEW for analog, discrete, and ARINC data validation. We obtained real-time inputs from the safety-critical systems and gave them to the models so designed.
LabVIEW and data acquisition can demonstrate the real-time application of the algorithm which helps in visualizing the control flow of the algorithm. We used LabVIEW, NI MAX, a PXIe-6363 module, and a PXI-6528 module to design and demonstrate the algorithm model.
We used the graphical function blocks such as arrays, numeric function blocks, and signal generation blocks to generate inputs and direct the inputs acquired according to the control flow of the algorithm. We also used the advanced built-in analysis and signal processing libraries. Highly customizable user interfaces made the visualization of the algorithm more interactive and easy to understand. Sequential and parallel execution of the algorithm for different system interfaces was hassle free because we could design, prototype, and deploy within a single development environment with LabVIEW. We used data flow representation to eradicate complex and unwanted functions in the design environment. DAQ assistant integration into the models for I/O designed for engineering data provided real-time data integration to test the algorithm.
Due to the time dependency of the algorithm, we opted to use NI software and hardware features. To demonstrate the algorithm, fault injection into the analog and discrete signals is required as part of verification cases and procedures prescribed by the certification authority.
Fault injection in the real-time test setup is almost impossible; hence, we opted to use the time-related function blocks in LabVIEW as an alternative to monitor, inject fault into, and control the signal pulse width of the signal generated. Fault injection needed to be done as and when desired to test the integrity of the algorithm. We had to specify the fault injection for different cases in the signal generation to verify algorithm functionality.
During the course of the project, we experienced start-up issues with the PXI-6528 module due to dissimilar labeling of the pin configuration in the connector board and the device pin-outs of the DAQ module. The interfaced LabVIEW model could not generate digital signals and the engineer could not reconcile the issue. We requested NI’s professional support, and the technical team provided on-call support that played a critical role in the completion of the model demonstration.
J. Jayanthi
CSIR-NAL
Aerospace Electronics and Systems Division
Kodihalli, Bengaluru 560075
India
jayanthi@nal.res.in