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The cleavage of linkages of lignocellulose is important for its valorization. The linkage cleavage of cornstalk hydrolysis residue was investigated over catalysts (Ru/C + MgCl2) in EtOAc/H2O solvents. The results show that almost hydrogen bonds, C–C bonds, ether and ester bonds in the matrix of lignin and cellulose were broken, accompanying 80.6% of lignin and 98.5% of cellulose conversion, and obtaining 37.5% of aromatic monomers and 28.8% of lignin oligomers. In the reaction system, biphasic EtOAc/H2O solvents exhibited an effect on cleaving the intermolecular linkages between lignin and cellulose. MgCl2 showed limited abilities of breaking the α-O-4 and β-O-4 linkages in lignin and limited β-1, 4-glycosidic and hydrogen bonds in cellulose were cleaved over Ru/C catalyst. The cleavage of C–O linkages (α-O-4, β-O-4, 4-O-5) and C–C bonds (α-β, β-5) in lignin were mainly dependent on Ru/C catalyst. Much C–O and the stubborn C–C linkages of β-5, β-1 and 5-5 were significantly disrupted by the synergistic effect between MgCl2 and Ru/C. However, MgCl2 exhibited great contribution to breakage of β-1, 4-glycosidic linkage, hydrogen bonds and sugar ring of cellulose. The linkage of β-1, 4-glycosidic, hydrogen bonds and C–C in C5/C6 sugars were significantly broken. The increased yield of products was evidently due to the synergistic effect of Ru/C combined with MgCl2.

Misalignment is one of the commonly encountered faults that generate excessive rotor vibration. The diversity of its characteristic frequency brings great trouble for fault diagnosis. Especially when misalignment-induced vibration manifests it as only synchronous (1x) component, properly diagnosing this fault becomes more difficult, since other faults often show the similar frequency signature. To extract discriminative information from the view of fault development, a diagnostic method is proposed with comprehensive utilization of changes in rotor static and dynamic response characteristics. First, rotor static and dynamic responses are deduced, the average rotor centerline (ARC) plot and orbit plot are introduced separately to represent these responses. The results indicate that ARC position changes considerably and 1x-orbit synchronously becomes more flattened with the increase of misalignment, when all machine operating conditions remain constant. Combination of these symptoms can be used to better distinguish misalignment from other 1x vibration problems related to changes in unbalance force, e.g. rotor unbalance and temporary thermal bend. Subsequently, the combination plot and its feature trend plot of ARC and 1x-orbit are developed to fully describe the changes in rotor static and dynamic responses with time and their correlation. Finally, the proposed method was successfully applied to 1x vibrations of a NOx compressor and a flue gas expander.

Herein, we report the catalytic use of multifunctional CuO nanoparticles (NPs) to oxidatively fractionate lignocellulosic feedstock with dioxygen in aqueous NaOH under mild conditions . In presence of CuO NPs, lignocellulose is fractionated into three parts, overall yielding 90% carbon efficiency. Lignin is converted to up to 45.6 wt% in organic soluble aromatic aldehyde monomers, rich in vanillin and syringaldehyde, the value surpassing the theoretical one based on b-O-4 bond content, indicating significant cleavage of other ether bonds. All hemicellulose is selectively converted into water soluble small (di)acids, mainly to oxalic acid. Up to 81% of cellulose, in contrast, is obtained as a white crystalline residue with high cellulose purity (over 95%), which can readily be transformed into high quality nanocellulose, useful in many applications.

In the context of a carbon neutral economy, catalytic CO

Propelled by the vision of carbon-neutral energy systems, heterogeneous hydrogenation of CO2 to formic acid/formate, a liquid hydrogen carrier, has been intensively studied as a promising approach to realize renewable and decarbonized energy supply. In the present review, the state-of-the-art of heterogeneous catalysts for this process is comprehensively summarized. First, a brief description of the challenges associated with thermodynamics is provided. Major advancements on constructing efficient heterogeneous catalysts then constitute the main body of this review, mainly involving nanostructured and single atom catalysts based on noble metals. Special attention is paid to the relevant structure–activity correlations and mechanistic insights, which provide strong bases for rational catalyst design. Key factors related to catalytic activity are highlighted including metal dispersion, electron density, basic functionalities, and concerted catalysis of metal and basic sites. A summary and outlook is presented in the end. We believe that this review will inspire more novel research from the catalysis community to advance the design of innovative catalytic materials towards the ultimate sustainable energy sector with a closed carbon loop.

Pentanoic acid (PA) is considered as an important derivative from the levulinics family. Herein, γ-valerolactone (GVL) is converted to PA in the presence of aqueous formic acid (FA) as an available, sustainable and alternative reducing agent. For this purpose, bifunctional catalyst comprising Pt supported on acidic zeolites were utilized. Pt has a dual role, decomposing FA into hydrogen which occurs in the initial stage of the reaction, and hydrogenation of the intermediate pentenoic acids (PEAs), which are formed through acid-catalyzed ring opening of GVL, to PA. Since the ring opening is thermodynamically disfavored under hydrothermal condition at high reaction temperature (543 K), hydrogenation on Pt is rate limiting and thus fast provision of hydrogen by decomposing FA on Pt is a prerequisite to PA formation from GVL. High surface area of Pt is indeed improving GVL conversion rates, whereas a rate dependency on the Brønsted acid site, as opposed to similar reaction with pure hydrogen instead of formic acid, is not encountered in this study. The acid sites though should be strong such as on ZSM-5, but stability is challenging for long term reactions in hot liquid water. Balancing the molar ratio of GVL to FA is essential for the catalytic system for two reasons. Sufficient amount of hydrogen and thus FA is needed for complete GVL conversion, but a too high FA content sluggishes hydrogenation due to strong interaction of FA and its decomposition side-products, e.g. CO, with the metal surface, overall hampering the conversion of GVL. The temperature dependence of this cascade reaction was determined, showing an apparent activation energy for GVL conversion and FA dehydrogenation of 73 kJ mol-1 and 19 kJ mol-1, respectively, thus being strong for GVL conversion and moderate for FA decomposition. Finally, the selective one-pot process of levulinic (LA), instead of GVL, to PA using FA as a reducing agent was pioneered successfully.

Lignin transformation to high-value chemicals is key for forthcoming biorefineries. Here, we report efficient delignification of pine wood by oxidative biorefining in aqueous alkali, producing both...

Background: With the wide use of robots in electric welding and mechanical manufacturing, we need to reflect their trajectory at work, verify the effectiveness of robotic working principles and prevent unnecessary problems through simulation experiments. In order to meet the requirements of precision and controllable trajectory of robots in the assembly process, we need to model the kinematics of robots, and adopt an interpolation method to improve the kinematic accuracy of robots. Methods: To solve the problems of low accuracy and poor stability of robots in assembly trajectory, a method which combines an optimized Denavit and Hartenberg (D-H) parameter modeling method and interpolation method is presented for the first time in this paper. For this purpose, the configuration and startup files required for robot motion planning are created to configure the corresponding simulation platform of an AUBO-i5 collaborative robot. In order to study the reliability of the proposed method, a three-dimensional environment model of the manipulator is established. Then, the robot’s linear trajectory planning is realized, and thus the position changes of each joint are analyzed. Results: The simulation results show that the improved D-H method effectively improves the stability and accuracy of the motion trajectory of each joint and provides a basis for the robot to realize more flexible motion planning. Conclusions: In the assembly process, we can use the simulation platform for simulation experiments to avoid unnecessary problems. In addition, we can use the improved D-H method and interpolation method to improve the trajectory accuracy of robots. The method presented in the paper can effectively reduce the damage of the robot in the process of use and improve the assembly efficiency of robots.

© 2018 American Chemical Society. This contribution studies the steam-assisted dealkylation of 4-n-propylphenol (4-n-PP), one of the major products derived from lignin, into phenol and propylene over several micro- and mesoporous acidic aluminosilicates in gas phase. A series of acidic zeolites with different topology (e.g., FER, TON, MFI, BEA, and FAU) are studied, of which ZSM-5 outperforms the others. The catalytic results, including zeolite topology and water stability effects, are rationalized in terms of thermodynamics and kinetics. A reaction mechanism is proposed by (i) analyzing products distribution under varying temperature and contact time conditions, (ii) investigating the dealkylation of different regio- and geometric isomers of propylphenol, and (iii) studying the reverse alkylation of phenol and propylene. The mechanism accords to the classic carbenium chemistry including isomerization, disproportionation, transalkylation, and dealkylation, as the most important reactions. The exceptional selectivity of ZSM-5 is attributed to a pore confinement, avoiding disproportionation/transalkylation as a result of a transition state shape selectivity. The presence of water maintains a surprisingly stable catalysis, especially for ZSM-5 with low acid density. The working hypothesis of this stabilization is that water precludes diphenyl ether(s) formation in the pores by reducing the lifetime of the phenolics at the active site due to the high heat of adsorption of water on H-ZSM-5, besides counteracting the equilibrium of the phenolics condensation reaction. The water effect is unique for the combination of (alkyl)phenols and ZSM-5. ispartof: ACS Catalysis vol:8 issue:9 pages:7861-7878 status: published

Subsynchronous pseudo-vibration (SPV) of rotating machinery is one of the primary reasons for fault misdiagnosis. SPV has similar signal signatures to those of a real fault, which usually leads to excessive maintenance or even unscheduled shutdown. For this reason, it is essential to investigate the root causes of SPV so as to reduce unnecessary downtime and maintenance cost. Aiming at this issue, a novel signal model for rotor non-contact vibration is built to describe the generating mechanism of one kind of SPV by considering the combined effects of rotor axial motion and detection surface runout on vibration signal. To obtain more discriminative fault features from the vibration signals, the two-dimension holospectrum (2DH) is employed to integrate the phase information from two perpendicularly installed sensors. The characteristics of precession orbit used to describe the lateral motion of a rotor could be fully extracted by 2DH. It is shown that the precession orbit at the fault feature frequency will degenerate into a straight line when SPV occurs, and thus the eccentricity of precession orbit could be considered as a key feature for discriminating SPV from real subsynchronous vibration (RSV). The effectiveness of proposed method was validated on a rotor test rig. By using this method, the SPV problem of a real gearbox in a blast furnace blower set in a steel mill was successfully diagnosed.

© 2018 American Chemical Society. Mesostructured silica-carbon nanocomposites with large mesopore interconnectivity are created from sucrose as sustainable carbon source using a mild vapor-phase assisted hydrothermal treatment procedure. The resultant mesostructured silica-carbon nanocomposite can be readily sulfonated to provide a strong acid catalyst with high sulfonic acid density, or the carbon phases of the nanocomposite can be removed by calcination to produce a silica material with ultrahigh porosity (Vpore = 1.25 to 1.34 cm3 g-1). A superior catalytic activity is demonstrated for the solvent-less condensation of 2-methylfuran with furfural; both product yield and conversion rate surpass that of reference catalysts such as their counterparts from dry pyrolysis and the commercial strong acid resins. The enhanced catalytic activity is attributed to the higher SO3H acid density (0.64 to 1.08 mmol g-1), the larger and better communicating mesopores (Vmeso = 0.38 to 0.82 cm3 g-1) and the abundant presence of surface oxygen-containing functional groups on the vapor-phase assisted hydrothermally treated samples. The origin of the well-developed large interconnecting mesopores is investigated and discussed. The mild hydrothermal treatment causes local etching of the original mesopores in the precursor material, creating unexpected interconnectivity between the pores, while the original micropores are basically eliminated during the treatment. Therefore, the here specified hydrothermal treatment provides a promising method to conventional pyrolysis for the efficient and eco-friendly synthesis of highly mesoporous silica-carbon nanocomposites and modification of their physicochemical properties. ispartof: ACS Sustainable Chemistry & Engineering vol:6 issue:6 pages:7859-7870 status: published

Amorphous aluminosilicates catalysts have been used industrially on a large scale for almost a century. However, the influence of the pH on the alumination of silica in aqueous solutions has remained largely unclear. Herein, room temperature aluminations of different mesoporous amorphous silicas (fumed silica, dried silica gel, SBA-15, MCM-41, and COK-12) with aqueous solutions of various pH (3-13) are explored. The aqueous solutions are prepared using different aluminum sources (Al(NO3)3 or NaAlO2) and alkaline additives (NaOH or NH4OH). The decoupling of pH and Al source using alkaline additives results in a vast experimental potential to prepare unique aluminosilicates, where an important role is played by the pH development during the treatment. The bulk and surface composition, acidity, aluminum coordination, morphology, hydrothermal stability, and porosity of the obtained materials are characterized. Optimal samples possess large surface areas and superior acidities (up to 50% higher) and outstanding stabilities compared to aluminosilicates prepared via state of the art methods. The obtained materials are evaluated in a series of acid-catalyzed model reactions. The potential of the obtained materials is emphasized by the similar or superior acidity and catalytic performance compared to several benchmark industrial silica-alumina-based catalysts.

A novel and practical synthesis method for carbonaceous materials was proposed by the vapor-phase hydrothermal treatment of sucrose at a mild 200 °C temperature. The resultant carbon possesses a 52 m2 g−1 specific surface area and 0.18 cm3 g−1 total pore volume – values that are substantially higher than those of conventional hydrothermally treated sugar solutions. The functionalization of the porous carbon with –SO3H led to acidic materials with high catalytic activity and selectivity towards, e.g., the sylvan condensation with furfural.

The bearing fault signal can be seen as convolution of periodical impulses and interference components. The minimum entropy deconvolution (MED) is effective approach for the deconvolution of signal. However, the MED is vulnerable to random impulse and interference components. To solve the problem, an improved method, named minimum entropy morphological deconvolution (MEMD), is proposed in this paper. Firstly, the amplitude frequency response of two typical morphological operators (MOs) are discussed. These operators are then introduced into MED to filter the sample matrix. The optimal MO is selected based on the amplitude ratio of diagonal slice spectrum (DSS). Eventually, the filtered result is analyzed by DSS to identify the fault type. In MEMD, the influence of random shocks is eliminated and the scale of SE can be determined adaptively. The MEMD is verified by simulation and experimental signals. Comparison study is implemented and the analysis results verify its effectiveness and feasibility.

The orbit shape responded from each concerned section of anisotropic rotating machinery varies along with the axial position of unbalance force, especially its parameters like the inclination angle and the major to minor axis ratio. Considering the axial position difference between the original unbalance mass existed and the balancing planes adopted, vibration reduction with balancing could be disturbed by the anisotropy of rotating machinery. Through in-depth analysis on these mechanisms, a method for anisotropy evaluation is presented based on the dispersion characteristics estimation of system difference coefficients. Balancing experiments under different degrees of system difference coefficients dispersion and different unbalance mass distribution are implemented to show the effectiveness of this method. Essentially, the unbalance response of each concerned section is a synthesis of system difference coefficients and unbalance mass. Therefore, as weight coefficients of unbalance mass, the dispersion evaluation indexes of system difference coefficients can be used in distributing the original unbalance mass to further reduce the disturbance of system anisotropy to vibration reduction.

Metal burn is encountered very often in industrial practice. Different degree of metal burn leads to unlike damage to related parts. In order to monitor the burn degrees accurately, AE burn signals are studied and the total process is given in the following steps. Firstly, four different degrees of surface burn are generated in experiment, during which AE signals are collected. Secondly, frequency shift regulation is found. It is explained by the phase transition principle and utilized to distinguish the burn degrees. Then, Variational Mode Decomposition (VMD) method is applied to extract main frequency of AE burn signals. And the input parameters of VMD are selected by scale-space method and comparison of anti-noise performance. Finally, the four degrees of metal burn are recognized by feature parameters successfully.

© 2018 Elsevier B.V. Selective dealkylation of alkylphenols, the opposite reaction of the more commonly studied phenol alkylation, may represent an important reaction in the production of base chemicals like phenol and olefins from fossilized and raw lignocellulosic matter. This study reports the first thermodynamics and kinetics studies of the vapor-phase conversion of ethylphenol (EP) over acidic γ-Al2O3, amorphous (ASA) and crystalline aluminosilicates (like ferrierite, ZSM-22, ZSM-5, beta, and USY) in the absence of hydrogen and noble metals, as a way to produce phenol and ethylene. The reaction was studied deliberately in presence of steam to get stable time on stream catalysis. The thermodynamic analysis shows an endothermal EP conversion to phenol and ethylene, favoured at high reaction temperature, while isomerisation, disproportionation and transalkylation are thermodynamically preferred at low temperature. The kinetic study examines the role of the catalytically active sites; it reveals the importance of site constraint on the activity, selectivity and stability, and shows the complex temperature dependency of the dealkylation. Both Brønsted and Lewis acid sites are active, but multifactor dependency (such as acid strength and site accessibility) complicates the establishment of simple quantitative relationships with the acid type. EP does not enter the micropores of ferrierite and ZSM-22, as suggested by adsorption experiments. Kinetics without significant diffusion limitations were obtained with ZSM-5, beta and USY. Thus, in absence of intracrystalline diffusion limitation (as verified by calculations using reported effective diffusivities, and substantiated by a comparably high apparent activation energy for all zeolites), the increased reaction turnover rate with increasing pore size from medium to large pore zeolites is largely explained by a change in reaction pathway (from monolecular to bimolecular) to convert EP to phenol and ethylene. A pathway proceeding through fast thermodynamically favourable bimolecular reactions occurs in the spatially non-constrained pores and crystal surface, whereas monomolecular reactions take place in the micropores of ZSM-5. Despite the lower rate, the selectivity over ZSM-5 strongly benefits from active site confinement, being responsible to achieve quantitative formation of phenol and ethylene from ethylphenol. The excellent performance of ZSM-5 thus accords with its shape selective property that avoids undesired side reactions such as the sterically demanding bimolecular reactions like disproportionation, transalkylation and C-C cracking, and severe cokes formation. ispartof: Applied Catalysis B-Environmental vol:234 pages:117-129 status: published

The preparation of vanillin from lignin is one of the lignin valorization strategies. However, obtaining high vanillin yield is still a challenge. Therefore, the process of vanillin production and factors that affect yield of vanillin has attracted much attention. Here, oxidation of vanillin was performed to study its degradation behavior under lignin alkaline oxidation conditions. High-performance liquid chromatography, liquid chromatography–electrospray mass spectrometry, gas chromatography–mass spectrometer and gel permeation chromatography were employed to analyze the products including monomers and dimers. Results demonstrated that reaction temperature and time greatly affected vanillin degradation; vanillin can be completely converted in 5 h at 160 °C. At 160 °C, the main products of vanillin oxidation were small molecule acids and alcohols, other monophenols, and even condensed dimers. A possible vanillin degradation pathway was proposed. The results indicate that vanillin degradation and condensation are the main reasons for decreasing vanillin yield during lignin valorization under alkaline oxidation circumstances.

Selective conversion of alkylphenols to phenol and olefins is presented as a challenging key step in upgrading raw and fossilized lignocellulose. An exceptional and stable dealkylation performance is achieved by application of an acidic ZSM-5 zeolite, in which co-feeding of water is crucial to maintain catalytic activity. The role of water is attributed to competitive adsorption of water and phenol. The lignin-first pathway towards phenol yields a tenfold improvement of phenol compared to the state-of-the-art single-step lignocellullosic depolymerization techniques.

In this review, recent advances in the one-pot hydrolytic hydrogenation and hydrogenolysis of cellulose to value-added polyols, including hexitols (sorbitol, mannitol, and isosorbide) and 1,2-alkanediols (ethylene glycol and 1,2-propylene glycol), are summarized. Methods for the generation of H+ in the first step of cellulose hydrolysis to form intermediate sugars, such as the use of soluble acids (mineral acids and heteropoly acids) and H+ produced in situ from functional supports and H-2 dissociation, are classified and analyzed, considering its combination with active metals for the subsequent hydrogenation or hydrogenolysis of sugars to polyols. The interaction of non-noble metals such as nickel, bimetals, and tungsten with support materials in the catalytic conversion of intermediate sugars to hexitols and ethylene glycol is reviewed. The corresponding reaction pathways and mechanisms are discussed, including the conversion process using basic supports and solution conditions. Major challenges and promising routes are also suggested for the future development of the chemocatalytic conversion of cellulose. (C) 2015 Elsevier Ltd. All rights reserved.

The vibration responses of different linear faults all possess some common features, which make fault diagnosis very difficult. Based on the multi-sensor information fusion theory, this paper presents a new qualitative identification method for the diagnosis of linear faults. The excitation–response dynamic equation is constructed and system balancing response with full consideration of system anisotropy is analyzed. Through discussion of the precession orbit shape difference and its dispersive situation, the orbit shape average difference coefficient and the corresponding dispersion term are estimated to obtain the theoretical balancing effect. Finally, the qualitative identification of linear fault can be done according to whether the calculated balancing effect meets the safe operation requirement or not. The dynamic characteristic of the system difference coefficients is verified by a simulation experiment and the case study further testifies the capability and reliability of the proposed method.

Enhancing the contact or interaction between cellulose and solid catalyst is a significant aspect in its efficient catalytic conversion. Herein, mixed ball milling of cellulose and solid catalyst was presented to achieve this goal, and the promotion effect was measured by hydrolytic hydrogenation of cellulose to sugar alcohols (the platform compounds for biogasoline) with solid acid and commercial 5 wt % Ru/C in water. The effects of ball-milling modes, time, and reaction parameters were studied. The properties of cellulose and solid acid catalyst before and after treatment were also analyzed. The yield of sugar alcohols reached 90.3% at 463 K with amorphous zirconium phosphate and Ru/C (mixed ball-milling time of 2 h). This high yield of sugar alcohols achieved in the mixed ball-milling time of 2 h was 12 times faster than that by the single ball milling of 24 h under the same reaction conditions. It is ascribed to the enhanced contact between cellulose and catalyst, resulting in promoting cellulose depo...

ZrP with large surface, mesoporous volume, and size was prepared. Its catalytic performance was evaluated in hydrolytic hydrogenation of cellulose to sorbitol/mannitol combined with commercial Ru/C. A significantly enhanced sorbitol/mannitol yield was obtained as compared with that of the water-soluble acidic phosphates and buffer solution of potassium acid phthalate combined with the same Ru/C. The enhanced yield was attributed to the Lewis and Bronsted acid on ZrP surface improving the surface’s absorption and activation for cellulose and accelerating the rate-determined hydrolysis step. The maximal sorbitol/mannitol yield of 63% and 81% could be obtained by using microcrystalline and ball milling cellulose as the feedstock, respectively. The ZrP combined with Ru/C was adaptable to the high concentrated cellulose and obtained 5.8 wt % of sorbitol/mannitol concentration. The remarkably enhanced cellulose hydrolysis by ZrP sharply decreased the use of Ru/C, which is significant for the essential application.

Non-edible cellulose has attracted considerable attention to be converted into valuable platform chemicals. Direct transformation of cellulose to C6 alditols (mannitol and sorbitol) provides a sustainable route. A productive approach is presented in this work using a Ru/C catalyst combined with H+-released boron phosphate in an aqueous phase. A yield of C6 alditols as high as 74.9% with a 91% conversion of cellulose is achieved. By adding silica–alumina materials, the yield of C6 alditols can be improved to 93.5% with complete conversion. The acid sites gradually released from boron phosphate under hydrothermal conditions could promote the hydrolysis of cellulose without significant degradation of glucose. Furthermore, the interaction of boric acid with C6 alditols may form borate–polyol complexes, which can enhance the stability of the C6 alditols to avoid further hydrogenolysis and dehydration of the C6 alditols formed. Due to the adsorption ability of the substrate, the addition of silica–alumina materials with a high content of silica leads to improved performance.

The selective transformation of cellulose to C6 alditols provides a feasible route towards the sustainable synthesis of chemicals and fuels. Herein, the catalytic performance of amorphous zirconium phosphate (ZPA) combined with 5 wt% Ru/C was evaluated in the direct conversion of cellulose to C6 alditols (sorbitol and mannitol) under hydrothermal conditions. The yield of C6 alditols reached 63.5% and 85.5% with microcrystalline cellulose and ball-milled cellulose as the feedstock, respectively. This hybrid catalyst was developed to convert concentrated cellulose to obtain C6 alditols with a high concentration of 68.8 mg mL−1 in the final products. The high yield of C6 alditols from cellulose was ascribed to the fact that ZPA favoured the adsorption of cellulose and promoted its depolymerization to cellobiose and glucose, which was hydrogenated immediately to C6 alditols over Ru/C. The weak adsorption of C6 alditols over ZPA inhibited the dehydration of C6 alditols to sorbitan. Furthermore, ZPA exhibited excellent hydrothermal stability and could be reused for several runs.

Properties of time domain parameters of the vibration signal have been extensively studied for the fault diagnosis of rolling element bearings (REB). Parameters like kurtosis and Envelope Harmonic-to-Noise Ratio are most widely applied in this field and some important progress has been made. However, since only one-sided information is contained in these parameters respectively, problems still exist in practice when the signals collected are of complicated structure and/or contaminated by strong background noises. A new parameter, named Shock pulse index(SPI), is proposed in this paper. It integrates the mutual advantage of both parameters above and can help effectively identify fault related impulse components under the interference of strong background noises, unrelated harmonic components and random impulses. The SPI optimizes the parameters of Maximum Correlated Kurtosis Deconvolution (MCKD), which is used to filter the signals under consideration. Finally, the interested transient information contained in the filtered signal can be highlighted through demodulation with Teager Energy Operator (TEO). Fault related impulse components can therefore be extracted accurately. Simulations and experiment analyses verify the effectiveness and correctness of the SPI.

Based on the idea of multi-sensor information fusion, one of the main problem—insufficient utilization of rotor vibration information—existing in the traditional rotor balancing methods is solved. By integration of all the amplitude, frequency and phase information, the Holobalancing method can help to correct the rotor balancing state more accurately and efficiently than other traditional methods. The field balancing capability has been greatly improved therefore. Since the Holobalancing method truly considers the characteristics of system support stiffness anisotropy, the unreasonable isotropic assumption adopted in traditional balancing methods is no longer required therefore. The balancing result of the Holobalancing method is more reliable and fewer number of trial runs is needed. Recently, the Holobalancing method is further improved by reselection of balancing object. With the Initial Phase Vector (IPV) being replaced by its forward precession component (IPV+), the impact of probe orientation on the balancing analysis and calculation is completely eliminated and the computational procedure is greatly simplified without sacrificing the balancing accuracy. The experiments and field application cases verify the effectiveness and reliability of this method.

The fault diagnosis schemes are roughly divided into two major categories: signal analysis and modeling method. Compared with the signal analysis approaches, the availability of suitable models of machines could be exploited more conveniently, which allows a more precise and reliable fault identification. In this paper, a modeling fault diagnostic approach based on Volterra series for rotating machinery is presented. After a brief review of the Volterra series theory, the process of the new diagnostic approach and the identification method of Volterra kernels are introduced in detail. The computer simulation verifies its feasibility and validity. Then, this novel method based on Volterra modeling is employed for the fault diagnosis of a rotor-bearing system. Through investigating the changes of generalized frequency response functions of the system under different states, the faults are identified successfully. Finally, the laboratory experimental results verify its effectiveness.

The precession behavior of an unbalanced rotor–bearing system with anisotropic supporting stiffness is analyzed. The result shows that the probe-orientation-related problem is still unsolved in the holospectrum technique based rotor balancing method. The deficiency of the balancing object of this method now in use, the Initial Phase Vector (IPV), sometimes makes the description or evaluation of rotor balance state unclear. Necessary modification to this method is made in this paper. A compound balancing object comprised of the magnitude of the major axis and the Initial Phase Angle (IPA) of the precession orbit is presented to replace the IPV as the rotor unbalance response. The amount and angular location of the mass unbalance can be determined precisely by the magnitude of the major axis and the IPA, respectively. Since the isotropic assumption is no longer a prerequisite and the evaluation of the mass unbalance amount is independent of the probe orientation, optimal result then can be ensured. The experiment and real application case verify its capability and feasibility.

In this paper, a new fuzzy membership function for fuzzy support vector machine is presented. It provides an effective approach to deal with the over-fitting problem when outliers exist in the training data set. Combining with the concept of the K-nearest neighbor algorithm, we give a definition of the new fuzzy membership function. Then, fuzzy support vector machine with some improvements is successfully applied in machinery fault diagnosis and some engineering experimental results show the good performance of the present approach.

The dynamic transmission error of a CNC machine tool affects the manufacturing precision significantly. It may be caused by many factors, such as the geometric error of the transmission parts, the defects on the tooth flank as well as the torsional vibration of running shafts etc. It is very important to locate where the major source is so as to provide a guidance to reduce the transmission error. In this article, the dynamic behavior of the transmission is obtained by using some built-in encoders of a CNC machine tool. Signals obtained from those encoders are the rotating angles of the shafts varying with time. The transmission error can be estimated by using those signals. Some signal processing approaches are established to analyze those signals to locate the error sources. Vibration is one of the most troubling problems encountered in CNC machine tools, this paper also provides an approach for vibration source identification based on the information obtained from the built-in encoders.

Synchronization among the running shafts in a CNC machine tool is always suffered by the speed variation of the drive motor and the vibration of mechanical transmission components. Synchronization error may decrease the manufacturing accuracy. A novel method is proposed to evaluate the synchronization for the shafts by using the built-in sensors in this article, which can be considered as a sensorless evaluation method. The advantage of this method is that no extra sensors are required. At the same time, some advanced signal processing techniques are applied to analyze those signals to discover more information about the synchronization. Experiments are taken on two CNC grinding machines to study on the synchronization among the running shafts. Some spectrum analysis approaches are employed to evaluate the synchronization among the running shafts. The stability of the running process can be clearly described by using those methods. The synchronization error fluctuation is also obtained at the same time, which is of great help to improve the performance of the machine tool.

The NARX network is a dynamical neural architecture commonly used for input-output modeling of nonlinear dynamical systems. When applied to time series prediction, the NARX network is designed as a feedforward time delay neural network (TDNN), i.e., without the feedback loop of delayed outputs, reducing substantially its predictive performance. In this paper, it is shown that the original architecture of the NARX network can be easily and efficiently applied to prediction of time series using embedding theory to reconstruct the input of NARX network. We evaluate the proposed approach using a real-world data set, which is the vibration data measured from a Co2 compressor. The results show that the proposed approach consistently outperforms standard neural network based predictors, such as the TDNN architecture.

In this paper, the holospectrum technique based balancing method has been improved by reselection of the balancing object. Current holospectrum based balancing technique uses the initial phase vector (IPV) as the balancing object. Theoretical analysis of the precession behavior of an unbalanced rotor with anisotropic stiffness shows that, compared with the IPV, its forward precession component vector is much better in describing the rotor balance state and is more suitable to be used as the measurement of unbalance response. After the backward precession component is removed, the impact of probe orientation on the balancing analysis and calculation is completely eliminated and the computational procedure is greatly simplified without sacrificing the balancing precision. The experiments and field application cases verify the accuracy and effectiveness of this method.

This study applies a novel neural-network technique, support vector regression (SVR), to predict reliably in dynamical system. The aim of this study is to examine the feasibility of SVR in state prediction by comparing it with the existing neural-network approaches. To build an effective SVR model, SVR’s parameters must be set carefully. This study proposes a novel approach, known as GA-SVR, which searches for SVR’s optimal parameters using genetic algorithms, and then adopts the optimal parameters to construct the SVR models. The application results of practical vibration data state forecasting measured from a Co2 compressor demonstrate that the GA-SVR model outperforms the existing neural network based on the criteria of mean absolute error (MAE) and root mean square error (RMSE).

A novel method of direct degradation of cellulose into 5-hydroymethylfurfural (HMF) in hot compressed steam was introduced, with the inorganic acidic salts (NaHSO4, KHSO4, NaH2PO4 and KH2PO4) as catalysts. The water molecules in the steam were absorbed by the catalysts to form an acidic aqueous layer on the surface of the cellulose, where the cellulose was converted into HMF and spread into the gas phase. The relative humidity of steam could influence the reaction route by controlling the acidity of the aqueous layer. Low relative humidity of steam was favoured for the carbonization of cellulose, while high relative humidity was preferred for hydrolysis-dehydration of cellulose to form HMF. A moderate HMF yield of 30.4 mol% was obtained with NaH2PO4 as the catalyst. This novel methodology demonstrated an efficient and green HMF production from cellulose, without organic solvents and toxic transition metal cations.