A failure diagnosis system based on a neural network classifier for the space shuttle main engine

A conceptual design of a model based failure detection and diagnosis system is developed for the space shuttle main engine. This design relies on the accurate and reliable identification of the parameters of the highly nonlinear and very complex engine. The design approach is presented in some detail and results for a failed valve are presented. These preliminary results verify that the developed parameter identification technique together with a neural network classifier can be used for this purpose

A simplified dynamic model of the T700 turboshaft engine

A simplified open-loop dynamic model of the T700 turboshaft engine, valid within the normal operating range of the engine, is developed. This model is obtained by linking linear state space models obtained at different engine operating points. Each linear model is developed from a detailed nonlinear engine simulation using a multivariable system identification and realization method. The simplified model may be used with a model-based real time diagnostic scheme for fault detection and diagnostics, as well as for open loop engine dynamics studies and closed loop control analysis utilizing a user generated control law

Use of UAV Data and HEC-RAS Model for Dimensioning of Hydraulic Structures on Forest Roads

forest roads should have the capability to drain the expected maximum discharge for a 50-year return period during their lifespan (i.e., 20 years). In Türkiye, Talbot’s formula, as empirical method, has commonly been used in determining the required cross-sectional area (CSA) of the structures. However, in practice, forest road engineers in Türkiye do not pay enough attention to their construction with required dimensions calculated by Talbot’s formula. In the present study, the Hydrological Engineering Centre – River Analysis System (HEC-RAS) model was used to evaluate the dimensions of installed structures in terms of their ability to drain maximum discharges, with the aim of determining the required dimensions for those that could not meet this requirement. To this purpose, the 6+000 km forest road No. 410 in Acısu Forest Enterprise, Gerede Forest Directorate (Bolu, Türkiye) was selected as the study area. In total, 15 small watersheds crossed by the forest road were delineated, with only six of them having cross-drainage structures. The HEC-RAS model geometry was generated by manual unmanned aerial vehicle (UAV) flights at altitudes of 5–15 m, providing very high spatial resolution (<1 cm). The maximum discharges of the watersheds were estimated for the HEC-RAS model using the Rational, Kürsteiner, and Soil Conservation Service-Curve Number (SCS-CN) methods. Maximum discharges of 0.18–6.03 were found for the Rational method, 0.45–4.46 for the Kürsteiner method, and 0.25–7.97 for the SCS-CN method. According to the HEC-RAS hydraulic model CSA simulations, most of the installed culvert CSAs calculated by Talbot’s formula were found to be incapable of draining maximum discharges. The study concluded that the HEC-RAS model can provide accurate and reliable results for determining the dimensions of such structures for forest roads

A simplified dynamic model of the Space Shuttle main engine

A simplified model is presented of the space shuttle main engine (SSME) dynamics valid within the range of operation of the engine. This model is obtained by linking the linearized point models obtained at 25 different operating points of SSME. The simplified model was developed for use with a model-based diagnostic scheme for failure detection and diagnostics studies, as well as control design purposes

Real-time fault diagnosis for propulsion systems

Current research toward real time fault diagnosis for propulsion systems at NASA-Lewis is described. The research is being applied to both air breathing and rocket propulsion systems. Topics include fault detection methods including neural networks, system modeling, and real time implementations

Sensor Fault Detection and Diagnosis Simulation of a Helicopter Engine in an Intelligent Control Framework

This paper presents an application of a fault detection and diagnosis scheme for the sensor faults of a helicopter engine. The scheme utilizes a model-based approach with real time identification and hypothesis testing which can provide early detection, isolation, and diagnosis of failures. It is an integral part of a proposed intelligent control system with health monitoring capabilities. The intelligent control system will allow for accommodation of faults, reduce maintenance cost, and increase system availability. The scheme compares the measured outputs of the engine with the expected outputs of an engine whose sensor suite is functioning normally. If the differences between the real and expected outputs exceed threshold values, a fault is detected. The isolation of sensor failures is accomplished through a fault parameter isolation technique where parameters which model the faulty process are calculated on-line with a real-time multivariable parameter estimation algorithm. The fault parameters and their patterns can then be analyzed for diagnostic and accommodation purposes. The scheme is applied to the detection and diagnosis of sensor faults of a T700 turboshaft engine. Sensor failures are induced in a T700 nonlinear performance simulation and data obtained are used with the scheme to detect, isolate, and estimate the magnitude of the faults

Identification of space shuttle main engine dynamics

System identification techniques are used to represent the dynamic behavior of the Space Shuttle Main Engine. The transfer function matrices of the linearized models of both the closed loop and the open loop system are obtained by using the recursive maximum likelihood method

Model-Based Fault Diagnosis for Turboshaft Engines

Tests are described which, when used to augment the existing periodic maintenance and pre-flight checks of T700 engines, can greatly improve the chances of uncovering a problem compared to the current practice. These test signals can be used to expose and differentiate between faults in various components by comparing the responses of particular engine variables to the expected. The responses can be processed on-line in a variety of ways which have been shown to reveal and identify faults. The combination of specific test signals and on-line processing methods provides an ad hoc approach to the isolation of faults which might not otherwise be detected during pre-flight checkout

Electricity generation and color removal at sulfate-reducing conditions in microbial fuel cell

The main aim of this study is to investigate the simultaneous azo dye removal and bioelectricity production at sulfate-reducing conditions in a continuously fed dual-chamber microbial fuel cell (MFC). Initially, optimization of sulfate reduction was performed at different sulfate concentrations (100-900 mg/L) and the constant COD of 1000 mg/L, corresponding to COD/sulfate ratio of 1.11-10, and varying HRT of 12-48 h. Optimum COD/sulfate ratio and HRT was found 1.66 and 36 h, respectively, corresponding to 96% COD removal, 44% sulfate removal and yielded about 24 W/m2 power density. Further, MFC was fed with azo dye containing (50-1000 mg/L) simulated wastewater to evaluate dye removal performance of sulfate-reducing bacteria. Addition of azo dye slightly enhanced the power production to 26 W/m2 , the highest value obtained during our study. Sulfate and COD removals were adversely affected at azo dye concentrations over 300 mg/L and 150 mg/L, respectively. Additionally, color removal performance of MFC was excellent however, chemical azo dye reduction out-competed with enzymatic reduction at high azo dye levels (>500 mg/L) leading to a poor sulfate (<15%) and COD (<45%) removal and recovery of azo dye reduction efficiency to 91%

An Investigation on the Bearing Design and Friction Characteristics of a Hermetic Reciprocating Compressor

The most important design parameters for hermetically sealed compressors used in domestic refrigerators are the Coefficient of Performance (COP); low manufacturing and operating costs; long operating life, low noise and vibration levels and to achieve environmentally friendly constructions. Positive displacement piston type compressors are used in refrigerators today due to their high capacity/volume ratios. Hence, the bearings of the hermetic compressors must also satisfy these design conditions. Investigation and optimization of crank shaft bearings in hermetic compressor applications are the main objectives of this study . The effect of crank shaft geometry, bearing clearance, lubricant viscosity, surface roughness and bearing location along the shaft on the friction losses were investigated and the new journal bearing designs were developed. Detailed parametric numerical simulations were performed using commercial software. According to the results of the simulations number of compressors were assembled with the selected design parameters and performance measurements were carried out. The results of the numerical analysis have shown that the numerically calculated mechanical loss level is similar to the performance results measured in a calorimeter test system. Results of the simulations and experiments were evaluated with six sigma (6?) techniques. Measurement of the efficiency of the compressor with the improved bearing design showed 1.3 % increase in the coefficient of performance (COP) with respect to the compressor with previous bearing design. This study shows that the mechanical loss characteristics are significantly influenced by the length of the bearings, clearance between the crankshaft journal and its bearing, kinematic viscosity and operating conditions. Bearing analysis results help to characterize the optimum journal bearing parameters which lead to improved mechanical efficiency of the compressor