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Machining accuracy of a machine tool is influenced by geometric errors produced by each part and component. Different errors have varying influence on the machining accuracy of a tool. The aim of this study is to optimize errors to get a desired performance for a numerical control machine tool. Applying multi-body system theory, a volumetric error model was constructed to track and compensate effects of errors during operation of the machine, and to relate the functional specifications on volumetric accuracy to the permissible errors on the joints and links of the machine. Error sensitivity analysis was used to identify the influence of different errors (especially the errors which have large influences) on volumetric error. Based on First Order and Second Moment theory, an error allocation approach was developed to optimize allocation of manufacturing and assembly tolerances along with specifying the operating conditions to determine the optimal level of these errors so that the cost of controlling them and the cost of failure to meet the specifications is minimized. The approach developed was implemented in software and an example of the geometric errors budgeting for a five-axis machine was discussed. It is identified that the different optimal standard deviations reflect the cost-weighted influences of the respective parameters in the equations of the functional requirements. This study suggests that it is possible to determine the coupling relationships between these errors and optimize the allowable error budgeting between these sources. [ABSTRACT FROM AUTHOR]

Biological oxidation pretreatment, which can improve the yield of gold, is the main gold extraction technology for disposing refractory gold ore with high arsenic and sulfur. The temperature of the oxidation tank influences the oxidation efficiency between the ore pulp and bacteria, including the yield of gold. Therefore, measurement has consistently been an important subject for researchers. As an effective data processing method, data fusion has been used extensively in many fields of industrial production. However, the interference of equipment or external factors such as the diurnal temperature difference or powerful wind may constantly increase measurement errors and damage certain sensors, which may transmit error data. These problems can be solved by following a pretreatment process. First, we establish a heat transfer mechanism model. Second, we design a small-range sensor network for the pretreatment process and present a layered fusion structure of sharing sensors using a multi-connected fusion structure. Third, we introduce the idea of iterative operation in data processing. In addition, we use prior data for predicting state values twice in order to improve the effectiveness of extended Kalman filtering in one time step. This study also proposes multi-fading factors on the basis of a weighted fading memory index to adjust the prediction error covariance. Finally, the state estimation accuracy of each sensor can be used as a weighting principle for the predictive confidence of each sensor by adding a weighting factor. In this study, the performance of the proposed method is verified by simulation and compared with the traditional single-sensor method. Actual industrial measurement data are processed by the proposed method for the equipment experiment. The performance index of the simulation and the experiment shows that the proposed method has a higher global accuracy than the traditional single-sensor method. Simulation results show that the accuracy of the proposed method has a 55% improvement upon that of the traditional single-sensor method, on average. In the equipment experiment, the accuracy of the industrial measurement improved by 37% when using the proposed method. [ABSTRACT FROM AUTHOR]

Hydrogen as an important clean energy source with a high energy density has attracted extensive attention in fuel cell vehicles and industrial production. However, considering its flammable and explosive property, gas sensors are desperately desired to efficiently monitor H 2 concentration in practical applications. Herein, a facile polymerization-induced aggregation strategy was proposed to synthesize uniform Si-doped mesoporous WO 3 (Si-mWO 3 ) microspheres with tunable sizes. The polymerization of the melamine-formaldehyde resin prepolymer (MF prepolymer) in the presence of silicotungstic acid hydrate (abbreviated as H 4 SiW) leads to uniform MF/H 4 SiW hybrid microspheres, which can be converted into Si-mWO 3 microspheres through a simple thermal decomposition treatment process. In addition, benefiting from the pore confinement effect, monodispersed Pd-decorated Si-mWO 3 microspheres (Pd/Si-mWO 3 ) were subsequently synthesized and applied as sensitive materials for the sensing and detection of hydrogen. Owing to the oxygen spillover effect of Pd nanoparticles, Pd/Si-mWO 3 enables adsorption of more oxygen anions than pure mWO 3 . These Pd nanoparticles dispersed on the surface of Si-mWO 3 accelerated the dissociation of hydrogen and promoted charge transfer between Pd nanoparticles and WO 3 crystal particles, which enhanced the sensing sensitivity toward H 2 . As a result, the gas sensor based on Pd/Si-mWO 3 microspheres exhibited excellent selectivity and sensitivity ( R air / R gas = 33.5) to 50 ppm H 2 at a relatively low operating temperature (210 °C), which was 30 times higher than that of the pure Si-mWO 3 sensor. To develop intelligent sensors, a portable sensor module based on Pd/Si-mWO 3 in combination with wireless Bluetooth connection was designed, which achieved real-time monitoring of H 2 concentration, opening up the possibility for use as intelligent H 2 sensors.

With the high sensitivity and anti-interference provided by a dual Z-scheme structure photoanode and a two-electrode system, a high-performance self-powered photoelectrochemical (PEC) aptasensor for oxytetracycline (OTC) detection was established in this work. Graphitic carbon nitride (g-C 3 N 4 ) with excellent photoelectric properties was used to be combined with WO 3 and MnO 2 to form a kind of dual Z-scheme heterojunction. The designed unique structure and the complementary performances of the three materials collectively guaranteed the highly stable photocurrent output of the photoanode due to the wide range of light absorption and the high separation rate of electron-hole pairs. The aptamer-based cathode modified with reduced graphene oxide (rGO) and Au nanoparticles (Au NPs) provided high conductivity and aptamer-binding sites, which brought excellent selective recognition of OTC as well as the self-powered capacity by receiving electrons from the photoanode. In the PEC sensing of OTC, the device presented a wide detection range from 1 pM to 150 nM and a low detection limit of 0.1 pM. Besides, the developed PEC aptasenor showed good selectivity, reproducibility, and stability, so as to be applied to real samples. The proposed PEC sensing method can be considered an effective and promising direction for the detection of antibiotics in the future.

A visible light self-powered photoelectrochemical (PEC) aptasensor based on silver chromate particles, graphitic carbon nitride nanosheets and graphene oxide sheets (Ag 2 CrO 4 /g-C 3 N 4 /GO) for the ultrasensitive detection of chloramphenicol (CAP) was reported in this work. g-C 3 N 4 was considered to be the fundamental photoelectric material because of its great oxidation ability of photogenerated hole as well as excellent biocompatibility and low toxicity. However, the narrow light absorption range and rapid carrier recombination rate limit the application of pure g-C 3 N 4 . Herein, Ag 2 CrO 4 and GO as photosensitizer were introduced to improve the photoelectric properties of g-C 3 N 4 . The photocurrent of the developed ternary composite was about 3 times higher than that of pristine g-C 3 N 4 , which proves it can be used as a suitable photoelectric active material. Moreover, the mechanism of Z-scheme electron transfer path was proved by density functional theory (DFT) calculation. The fabricated PEC aptasensor exhibited high sensitivity toward CAP with a wide liner response of 0.5 pM to 50 nM and a detection limit of 0.29 pM. The specific recognition mechanism and excellent sensing performance indicated this aptasensor could serve as a useful tool for selective and ultrasensitive CAP detection in practical analysis., (Copyright © 2020 Elsevier B.V. All rights reserved.)