A vapour compression chiller fault detection technique based on adaptative algorithms. Application to on-line refrigerant leakage detection

The existence of faults in vapour compression chillers plays a significant role in terms of energy efficiency loss, performance degradations, and even environmental implications. In this paper, a dynamic model-based fault detection technique suitable for real-time implementation is proposed. The main objective is to obtain a reliable and automated tool for fault detection in vapour compression chillers, which can be applied in steady-state or transient operation. The fault detection methodology is based on comparing actual and expected performance using an adaptative model and operating variables dynamic thresholds. The technique has been successful applied for on-line refrigerant leakage detection with experimental tests involving the artificial introduction of the fault in a laboratory vapour compression plant, showing the results its capability of detecting incipient leakage failure conditions avoiding false alarms.     

Performance investigation of a variable speed vapor compression system for fault detection and diagnosis

An experimental study has been performed to investigate the effect of four artificial faults on the performance of a variable speed vapor compression system. Experimental setup to test several artificial faults was made by modifying the conventional vapor compression test rig. Four major faults of compressor fault, condenser fault, evaporator fault, and refrigerant leakage, were implemented by observing the variation of cooling capacity. Two different rule-based modules for constant and variable speed operations were organized for an easy diagnosis of system faults. These two modules were applied differently as the cooling capacity satisfies the necessary air conditioning load. As a result, COP degradation due to the fault in a variable speed system is severer than that in a constant speed system.     

Design of a steady-state detector for fault detection and diagnosis of a residential air conditioner

This paper presents a general methodology for developing a steady-state detector for a vapor compression system based on a moving window and using standard deviations of seven measurements selected as features. The feature thresholds and optimized moving window size were based upon steady-state no-fault tests and startup transient tests. The study showed that evaporator superheat and condenser subcooling were sufficient for determining the onset of steady-state during the startup transient. However, they misidentified steady-state during indoor temperature change tests where evaporator saturation temperature and air temperature change across the evaporator were needed for proper steady-state identification. Hence, the paper recommends including all fault detection and diagnosis (FDD) features in the steady-state detector to ensure the robustness of the detector because different features may play key roles with different transients.     

嵌入式Linux在液压系统的状态监测与故障诊断中的应用

针对国产地下无轨采矿设备液压系统故障率高,而其检测和故障诊断手段落后的背景,本文提出了一种基于嵌入式Linux的多传感器信息的液压系统状态监测与故障诊断的设计方案,通过该系统能实时地、可靠地跟踪地下无轨采矿设备液压系统的工作状态,并能将设备运行状态发展趋势、故障信息通过友好的人机界面反映出来。     

Fuzzy goal-programming model with an artificial immune system (AIS) approach for a machine tool selection and operation allocation problem in a flexible manufacturing system

Some of the important planning problems that need realistic modelling and a quicker solution, especially in automated manufacturing systems, have recently assumed greater significance. In real-life industrial applications, the existing models considering deterministic situations fail as the true language adopted by foremen and technicians are fuzzy in nature. Thus, to map the situation on the shop floor to arrive at a real-time solution of this kind of tactical planning problem, it is essential to adopt fuzzy-based multi-objective goals so as to express the target desired by the management of business enterprises. This paper presents a fuzzy goal-programming approach to model the machine tool selection and operation allocation problem of flexible manufacturing systems. The model is optimized using an approach based on artificial immune systems and the results of the computational experiments are reported.     

An evaluation of machine learning and artificial intelligence models for predicting the flotation behavior of fine high-ash coal

In this study, five different machine learning (ML) and artificial intelligence (AI) models: random forest (RF), artificial neural networks (ANN), the adaptive neuro-fuzzy inference system (ANFIS), Mamdani fuzzy logic (MFL) and a hybrid neural fuzzy inference system (HyFIS) were employed to predict the flotation behavior of fine high ash coal in the presence of a novel “hybrid” ash depressant consisting of polyacrylamide chains grafted onto aluminium hydroxide nanoparticles: Al(OH)₃-PAM (Al-PAM). A total of 51 flotation tests were conducted on coal samples with 38% ash-content and a P₈₀ of approximately 49?μm. Different influencing variables of coal flotation including polymer dosage, pH, polymer conditioning time, sodium metasilicate dosage (commercial dispersant), and the impeller speed were used as inputs for the models. The combustible recovery and ash content of coal reported to the concentrate were used as response variables (outputs). For AI model development, 80% of the total data was used for training phase and 20% was used for testing phase. Coefficient of determination (R²) and root-mean-square error (RMSE) were used as performance indicators of the models. The MFL model showed the best accuracy for the prediction of the combustible recoveries and the froth ash contents for this specific feed. However, in case of any significant change in the characteristics of the feed, these models would have to be re-trained using the data obtained through further physical experimentation and/or process model simulations. Moreover as these models are trained on laboratory scale data, these are only good for the predictions at laboratory scale.     

Genetic-Algorithm-Based Computational Models for Optimizing the Process Parameters of A-TIG Welding to Achieve Target Bead Geometry in Type 304 L(N) and 316 L(N) Stainless Steels

The weld-bead geometry in 304LN and 316LN stainless steels produced by A-TIG welding plays an important role in determining the mechanical properties of the weld and its quality. Its shape parameters such as bead width, depth of penetration, and reinforcement height are decided according to the A-TIG welding process parameters such as current, voltage, torch speed, and arc gap. Identification of a suitable combination of A-TIG process parameters to produce the desired weld-bead geometry required many experiments, and the experimental optimization of the A-TIG process was indeed time consuming and costly. Therefore it becomes necessary to develop a methodology for optimizing the A-TIG process parameters to achieve the target weld-bead geometry. In the present work, genetic algorithm (GA)-based computational models have been developed to determine the optimum/near optimum process parameters to achieve the target weld-bead geometry in 304LN and 316LN stainless steel welds produced by A-TIG welding.     

Gold nanoparticle-based simple colorimetric and ultrasensitive dynamic light scattering assay for the selective detection of Pb(II) from paints, plastics, and water samples

Pb (II) is a common water pollutant with high toxicity. According to the CDC, about 310,000 U.S. children of ages 1-5 have high levels of lead in their blood that it is due to the exposure to lead from plastic toys and other products. As a result, the development of ultrasensitive assays for the real-time detection of Pb(II) from plastic toys and paints is very important for water controlling, clinical toxicology and industrial processes. Driven by the need to detect trace amounts of Pb(II) from water samples, we report a label-free, highly selective and ultra sensitive glutathione modified gold nanoparticle based dynamic light scattering (DLS) probe for Pb(II) recognition in 100 ppt level from aqueous solution with excellent discrimination against other heavy metals. The sensitivity of our assay to detect Pb(II) level in water is almost 2 orders of magnitude higher than the EPA standard limit. We have also demonstrated that our DLS assay is capable of measuring the amount of Pb(II) in paint, plastic toys, and water from MS river. A possible mechanism and operating principles of our DLS assay have been discussed. Ultimately, this nanotechnology driven assay could have enormous potential applications in rapid, on-site monitoring of Pb(II) from day-to-day sample.     

Design and synthesis of immunoconjugates and development of competition inhibition enzyme-linked immunosorbent assay (CIEIA) for the detection of O-isopropyl methylphosphonofluoridate (sarin): an organophosphorous toxicant

Three haptens of the organophosphorus (OP) toxicant ‘sarin’ having different spacer arm were designed and synthesized. Haptens were conjugated with BSA (bovine serum albumin) and ovalbumin (OVA) for raising antibody and coating antigen. High antibody titer with higher specificity was obtained from 4-(4-(isopropoxy(methyl)phosphoryloxy)phenylamino)-4-oxobutanoic acid (hapten B) having reasonable long spacer arm. For the standard curve, an IC₅₀ (inhibitory concentration) of free antigen was found to be 0.415 μg mL⁻¹ on the basis of indirect competitive ELISA. The study revealed that heterology in competition inhibition enzyme immunoassay (CIEIA) produced remarkable improvement in the sensitivity and specificity of the assay. Under the optimized conditions, the quantitative working range was found to be 0.19-1.56 μg mL⁻¹ with a limit of detection (LOD) of 0.05 μg mL⁻¹. The antibodies showed negligible cross reactivity (CR) with other OP toxicants and pesticides, which makes the assay suitable for the selective detection of sarin.     

Software design specification and analysis technique (SDSAT) for the development of safety-critical systems based on a programmable logic controller (PLC)

This paper introduces a Software Design Specification and Analysis Technique (SDSAT) for safety-critical systems based on a Programmable Logic Controller (PLC). During software development phases, the design phase performs an important role in connecting the requirements phase and the implementation phase, and it is a process of translating software requirements into software structures. In this work, the Nuclear FBD-style Design Specification and analysis (NuFDS) approach was proposed for nuclear Instrumentation and Control (I&C) software. The NuFDS approach is suggested in a straightforward manner for effective and formal software design specification and analysis. Accordingly, the proposed NuFDS approach is composed of a software design specification technique and a software design analysis technique. In addition, for tool support in the design phase, we developed the NuSDS tool based on the NuFDS approach; this tool is used specifically for generating software design specification and analysis for nuclear fields.     

Role of Brassica juncea (L.) Czern. (var. Vaibhav) in the phytoextraction of Ni from soil amended with fly ash: selection of extractant for metal bioavailability

A pot experiment was carried out to study the potential of the plant of Brassica juncea for the phytoextraction of metal from fly ash amended soil and to study correlation between different pool of metals (total, DTPA, CaCl(2) and NH(4)NO(3)) and metal accumulated in the plant in order to assess better extractant for plant available metals. The results of total metal analysis in the soil revealed the presence of Cr, which was found below detection limit (BDL) in the plants. The fly ash (FA) amendments and soil samples were extracted with different extractants and the level of metal vary from one extractant to another. The regression analysis between total and extractable metals showed better regression for all the tested metals except Mn (R(2)=0.001) in DTPA extraction. Correlation coefficient between metal accumulation by the plant tissues and different pool of metals showed better correlation with DTPA in case of Fe, Zn and Ni, whereas, Cu was significantly correlated with NH(4)NO(3) and other metals (Pb, Mn) with CaCl(2). The soil analysis results revealed that the mobility and plant availability of metals (Fe, Mn, Zn, Ni) within the profiles of amended soils was influenced by the change in pH, however, Pb and Cu was not affected. The metal accumulation in total plant tissues was found in the order of Fe>Ni>Zn>Mn>Cu>Pb and its translocation was found more in upper part. The plants grown on soil amended with 25%FA have shown significant increase in plant biomass, shoot and plant height, whereas, no significant effect was observed in root length. The cluster analysis showed 10%FA behave differently on the basis of physico-chemical properties and metal behavior. Thus, it may be concluded that B. juncea can be used for phytoextraction of metals, especially Ni in fly ash amendment soil.     

Determination of the total acid number (TAN) of used gas engine oils by IR and chemometrics applying a combined strategy for variable selection

The most common analyses carried out to assess gas engine oil quality include determination of viscosity, total base number (TBN), and total acid number (TAN). TAN has been considered to be an important indicator of oil quality, specifically in terms of defining oxidation and the extent of acidic contamination of used oils. TAN can be determined by potentiometric titration, and typical values for used oils can reach up to 4 mg KOH/g. A more convenient approach for the determination of TAN is based on infrared (IR) spectral data and multivariate regression models.We developed partial least-squares (PLS) models for the determination of TAN using IR data measured from monograde mineral gas engine oils (SAE 40, medium ash) that have been used in sewer and wood gas engines run with gaseous fuels from a sewage plant and a wood gasification plant, respectively. The final model performance was 0.07 mg KOH/g for the standard error of prediction (SEP). Essential for the development of powerful empirical models was an appropriate variable selection by combining expert knowledge, biPLS or dyn-biPLS, and a genetic algorithm. The optimum complexities of the models (the number of PLS components) and their prediction performances have been estimated by repeated double cross validation (rdCV).     

Superhard phases of simple substances and binary compounds of the B-C-N-O system: from diamond to the latest results (a Review)

The basic known and hypothetic one- and two-element phases of the B-C-N-O system (both superhard phases having diamond and boron structures and precursors to synthesize them) are described. The attention has been given to the structure, basic mechanical properties, and methods to identify and characterize the materials. For some phases that have been recently described in the literature the synthesis conditions at high pressures and temperatures are indicated.     

Sequential eluent injection technique as a new approach for the on-line enrichment and speciation of Cr(III) and Cr(VI) species on a single column with FAAS detection

This paper introduces a sequential eluent injection (SEI) technique combined with an on-line preconcentration/separation system for a fast and sensitive FAAS determination of trace amounts of Cr(III) and Cr(VI) species. The method is based on the simultaneous retention of Cr(III) and Cr(VI) on a single mini-column packed with a chloromethylated polystyrene functionalized with N,N-bis(naphthylideneimino)diethylenetriamine (PS-NAPdien) at pH 6.7. The retained chromium species was eluted by sequential injection of HCl for desorption of Cr(III), and NH₃ and NH₄NO₃ buffer solutions for desorption of Cr(VI). All the chemical and flow injection variables were optimized for the quantitative preconcentration and speciation of Cr(III) and Cr(VI). Under the optimum conditions, the calibration graph obtained is linear over the concentration range of 2.0-60.0 μg L⁻¹ for Cr(III), and 8.0-180.0 μg L⁻¹ for Cr(VI). The preconcentration factors for Cr(III) and Cr(VI) were 70 and 30, respectively. The 3σ detection limits were 0.6 μg L⁻¹ and 2.5 μg L⁻¹ for Cr(III) and Cr(VI), respectively. The relative standard deviations were 2.55% and 0.8%, respectively, for 6 replicate determinations of Cr(III) and Cr(VI) at the 40.0 μg L⁻¹ level. The proposed method was applied for determination of Cr(III) and Cr(VI) in different water samples with satisfactory results.     

Carminic acid modified anion exchanger for the removal and preconcentration of Mo(VI) from wastewater

Removal and preconcentration of Mo(VI) from water and wastewater solutions was investigated using carminic acid modified anion exchanger (IRA743). Various factors influencing the adsorption of Mo(VI), e.g. pH, initial concentration, and coexisting oxyanions were studied. Adsorption reached equilibrium within <10 min and was independent of initial concentration of Mo(VI). Studies were performed at different pH values to find the pH at which maximum adsorption occurred and was determined to be at a pH between 4.0 and 6.0. The Langmuir adsorption capacity (q(max)) was found to be 13.5mg Mo(VI)/g of the adsorbent. The results showed that modification of IRA743 with carminic acid is suitable for the removal of Mo(VI), as molybdate, from water and wastewater samples. The concentration of Mo(VI) was determined spectrophotometrically using bromopyrogallol red as a complexation reagent. This allows the determination of Mo(VI) in the range 1.0-100.0 μg/mL. The obtained material was subjected to efficient regeneration.     

Evaluation of large deuterated scintillators for fast neutron detection (E=0.5-20 MeV) using the D(d,n)He, C(d,n) and Al(d,n) reactions

The response of large deuterated liquid scintillators (up to 10 cm diameter by 15 cm) to neutrons 0.5-20 MeV has been studied using the 2.5 MeV neutron generator at the University of Michigan, and the d(d,n), ¹³C(d,n), ²⁷Al(d,n) and other reactions at the University of Notre Dame FN tandem accelerator. The latter utilize 9 and 16 MeV deuteron beams including a pulsed beam, which permitted time-of-flight measurements. Combining pulse-shape discrimination and time-of-flight allows gating on specific neutron energy groups to determine the detector response to specific neutron energies. This will permit accurate simulation of the detector response functions for applications of these detectors in nuclear research and homeland security applications.     

A DDC-based capacity controller of a direct expansion (DX) air conditioning (A/C) unit for simultaneous indoor air temperature and humidity control – Part II: Further development of the controller to improve control sensitivity

The development of the novel direct digital control (DDC)-based capacity controller for a direct expansion (DX) air conditioning (A/C) unit having variable-speed compressor and supply fan to simultaneously control indoor air temperature and relative humidity (RH) in a conditioned space served by the DX A/C unit has been reported in Part I of the two-part series. The results of preliminary controllability tests for the novel capacity controller presented in Part I, however, suggested that the controller developed was operational, with acceptable control accuracy but rooms for improvement with respect to control sensitivity. This paper, the second part of the two-part series, reports on the further development of the controller to improve its control sensitivity and the associated controllability test results. Both control accuracy and reasonable control sensitivity were achieved by incorporating a traditional Proportional–integral (PI) controller into the DDC-based capacity controller.     

Kinetic and equilibrium study for the sorption of cadmium(II) ions from aqueous phase by eucalyptus bark

The efficiency of eucalyptus bark as a low cost sorbent for removing cadmium ions from aqueous solution has been investigated in batch mode. The equilibrium data could be well described by the Langmuir isotherm but a worse fit was obtained by the Freundlich model. The five linearized forms of the Langmuir equation as well as the non-linear curve fitting analysis method were discussed. Results show that the non-linear method may be a better way to obtain the Langmuir parameters. Maximum cadmium uptake obtained at a temperature of 20 degrees C was 14.53mgg(-1). The influence of temperature on the sorption isotherms of cadmium has been also studied. The monolayer sorption capacity increased from 14.53 to 16.47 when the temperature was raised from 20 to 50 degrees C. The DeltaG degrees values were negative, which indicates that the sorption was spontaneous in nature. The effect of experimental parameters such as contact time, cadmium initial concentration, sorbent dose, temperature, solution initial pH, agitation speed, and ionic strength on the sorption kinetics of cadmium was investigated. Pseudo-second-order model was evaluated using the six linear forms as well as the non-linear curve fitting analysis method. Modeling of kinetic results shows that sorption process is best described by the pseudo-second-order model using the non-linear method. The pseudo-second-order model parameters were function of the initial concentration, the sorbent dose, the solution pH, the agitation speed, the temperature, and the ionic strength.     

Combined use of photocatalyst and adsorbent for the removal of inorganic arsenic(III) and organoarsenic compounds from aqueous media

A novel method for the removal of inorganic arsenic(III) (As(III)), monomethylarsonate (MMA), and dimethylarsinate (DMA) from aqueous media, was proposed and investigated. This method involves the combined use of TiO₂-photocatalyst and an adsorbent, which has a high ability of As(V) adsorption, under photo-irradiation. When an aqueous solution of As(III) was stirred and irradiated by sunlight or xenon lamp in the presence of TiO₂ suspension, the oxidation of As(III) into As(V) was effectively attained. By use of the same photocatalytic reaction, MMA and DMA were also degraded into As(V), while the total organic carbon (TOC) in the aqueous phase was decreased. When an aqueous solution of As(III) was stirred with a mixed suspension of TiO₂ and an adsorbent for As(V) (activated alumina) under sunlight irradiation, the arsenic removal reached 89% after 24 h. By use of the same photocatalyst–adsorbent system, 98% of MMA and 97% of DMA were removed. The mechanism of the removal of arsenic species by the photocatalyst–adsorbent system was discussed.