Air-doors are important facilities for regulating the air flow in a mine ventilation network. It is of value to study the influence of air-doors, which are adjacent to a fire source on smoke back-layering in order to build a rational ventilation system. By regulating air-doors in a mine ventilation network test platform, two typical mine ventilation networks, with parallel branches and a diagonal branch, were constructed. During the study, into the closing degree of the air-doors adjacent to a fire source in a ventilation network with parallel branches, the back-layering length is up to 3.70 m when the ventilation velocity is 1.40 m/s. When the air-door on the return side of the adjacent branch is closed, the back-layering subsides within 1 min and the upstream temperature drops rapidly to normal. When the air-door is half closed, there is still a back-layering flow within 5 min. Smoke control, with the air-door is closed, is better than when the air-door is half closed. Based on this,... [more]

The flow-matching problem of hydraulic systems is an important factor affecting the working performance and energy saving of hydraulic systems. According to the different flow-matching mechanisms, the flow-matching technology of hydraulic systems can be divided into three categories: positive flow-control technology, negative flow-control technology, and load-sensitive control technology. In this paper, the working mechanism of flow-matching technology and the cause of energy loss are analyzed, and the research results of flow matching are introduced from two aspects of energy saving and consumption reduction and system performance improvement. In the direction of energy saving and consumption reduction, the purposes of energy saving and consumption reduction are achieved by means of multi-way valve commutation, independent inlet and outlet control, parallel replacement of shuttle valve by a cylinder piston rod controlled by pilot pressure, change of hydraulic resistance of a pressure... [more]

The corrosion process leads to high power consumption, high maintenance costs and the loss of commercial income during downtime in various branches of industry. The proper methods to measure and forecast the corrosion process would help intervene in process production where corrosion is a common phenomenon. Therefore, the main aim of this experimental study is to improve the widely used corrosion monitoring methods with corrosion coupons. As part of this work, the installation for testing corrosion process under controlled conditions and with the application of mild steel coupons is proposed. The measurement concept is to install the coupons in a stream with the corrosion liquid (these conditions should be controlled). The numerical simulations of the fluid flow in the coupon installation were carried out, and the obtained results in the form of a velocity map allowed us to propose the placement of the coupons in the tested installation in such a way that the flowing liquid evenly wash... [more]

Optical density (OD) is a critical process parameter during fermentation, this being directly related to cell density, which provides valuable information regarding the state of the process. However, to measure OD, sampling of the fermentation broth is required. This is particularly challenging for high-throughput-microbioreactor (HT-MBR) systems, which require robotic liquid-handling (LiHa) systems for process control tasks, such as pH regulation or carbon feed additions. Bioreactor volume is limited and automated at-line sampling occupies the resources of LiHa systems; this affects their ability to carry out the aforementioned pipetting operations. Minimizing the number of physical OD measurements is therefore of significant interest. However, fewer measurements also result in less process information. This resource conflict has previously represented a challenge. We present an artificial neural-network-based soft sensor developed for the real-time estimation of the OD in an MBR syst... [more]

Raise boring is an important method to construct the underground shafts of mines and other underground infrastructures, by drilling down the pilot hole and then reaming up to the desired diameter. Seriously different from the drilling operations of the mechanical parts in mechanized mass production, it is very difficult to obtain a good consistency in the construction environments of each raise or shaft, to be more exact, every construction process is highly customized. The underground bottom-up reaming process is impossible to be observed directly, and the rock breaking effect is very difficult to be measured in real-time, due to the rock debris freely falling under the excavated shaft. The optimal configurations of the operational parameters in the drilling and working pressures, torque, rotation speed and penetration speed, mainly depend on the accumulation of construction experience or empirical models. To this end, we presented a machine learning method, based on the extreme learn... [more]

The present investigations on sealability evaluation for tubing and casing premium connections depend on the FEM with testing. This paper proposed a theoretical model to evaluate the sealability of a sphere-type premium connection based on make-up torque, which combines Hertz contact pressure and the von Mises yield criterion for calculating elastic−plastic contact pressure distribution on sealing interface and adopts the gas sealing criterion obtained from Murtagian’s experimental results for deducing gas sealing capacity. With the proposed model, the effects of additional make-up torque from the sealing interface on the sealing contact pressure distribution and key sealability parameters, including contact width, yield width, average contact pressure and gas sealing capacity, were analyzed and compared. The results show that additional make-up torque from the sealing interface closely influenced sealability parameters’ variation and gas sealing capacity. The gas sealing index based o... [more]

The stability of a quadruped robot is mainly affected by the obstacles in the horizontal direction and the roughness in the vertical direction, which often leads to the robot unable to achieve the desired gait effect. In order to solve this problem, the Model Predictive Control (MPC) model and the Zero Moment Point (ZMP) method are combined, and applied to gait planning and the foot end landing control of a small quadruped robot. The tort gait of a small quadruped robot is the focus of research in this study, which simulated trajectory planning and gait stability. In addition, through comparative analysis with the corresponding experiments, the results show that the simulation results are similar to the experimental results, and the quadruped robot gait is stable. Meanwhile, it shows that the combination of the MPC model and ZMP method is feasible for gait stability control of a quadruped robot.

The present work proposes a simulation and control framework for home and building automation, focusing on heating, ventilating, and air conditioning processes. Control systems based on different advanced control architectures and different control policies are simulated and compared, highlighting control performances, and energy-saving results in terms of CO2 emissions reduction. Heat, lighting, and natural ventilation phenomena were modelized through first-principles and empirical equations, obtaining a reliable and flexible simulation framework. Energy-consuming and green energy-supplying renewable sources were integrated into the framework, e.g., heat pumps, artificial lights, fresh air flow, and natural illuminance. Different control schemes are proposed, based on proportional−integral−derivative advanced control architectures and discrete event dynamic systems-based supervisors; different control specifications are included, resulting in a multi-mode control system. The specifica... [more]

The rational use of natural wind in extra-long tunnels for feedforward operation ventilation control can dramatically reduce tunnel operation costs. However, traditional tunnel natural wind calculation theory lacks a prediction function. This paper proposes a three-stage tunnel natural wind prediction method relying on the Yanglin Tunnel in Yunnan, China based on the massive meteorological parameters provided by the open-source national meteorological stations around the tunnel, which make up for the partial deficiency of the meteorological parameters of the tunnel portal. The multi-layer perceptron model (MLP) was used to predict the real-time meteorological parameters of the tunnel portal using the data from four national meteorological stations. The nonlinear autoregressive network model (NARX) was used to predict the meteorological parameters of the tunnel portal in the next period based on the predicted and measured real-time data. The natural wind speed in the tunnel was obtained... [more]

The prediction and early warning efficiency of mine gas concentrations are important for intelligent monitoring of daily gas concentrations in coal mines. It is used as an important means for ensuring the safe and stable operation of coal mines. This study proposes an early warning model for gas concentration prediction involving the Spark Streaming framework (SSF). The model incorporates a particle swarm optimisation algorithm (PSO) and a gated recurrent unit (GRU) model in the SSF, and further experimental analysis is carried out on the basis of optimising the model parameters. The operational efficiency of the model is validated using a control variable approach, and the prediction and warning errors is verified using MAE, RMSE and R2. The results show that the model is able to predict and warn of the gas concentration with high efficiency and high accuracy. It also features fast data processing and fault tolerance, which provides a new idea to continue improving the gas concentrati... [more]

As the most critical equipment in the pre-calcination process of dry cement production, the temperature of the precalciner is an essential factor affecting the quality of cement. However, the cement calcination system is time-delayed, nonlinear, and multi-disturbance, which makes it difficult to predict and control the precalciner temperature. In this study, a deep learning-based Hammerstein model is proposed, and a model predictive control system is built to predict and control the precalciner temperature. In the prediction model, the CNN-GRU network architecture is used to extract the operating states of the precalciner, and an attention mechanism is employed to find and emphasize the important historical information in the extracted states. Then, an ARX model is built to predict the temperature of the precalciner using the extracted operating state information. The complex nonlinear model solution in the control system is formed into a linear control problem and an inverse solution... [more]

Reasonable control of the content of niobium (Nb) in a steel slab is of great significance to improve the strength of the slab and the regularity of precipitation of precipitates. In this study, the high-temperature strength and precipitates of the same steel with four different Nb contents (A: 0.006%, B: 0.031%, C: 0.050%, D: 0.065%) were tested and analyzed. The results show that when the Nb content is 0.031%, the tensile strength and yield strength of the steel reach the ideal state; the two-phase particles that precipitated in the Q355GJ steel after heat treatment are mainly square- and star-shaped (Ti, Nb) (C, N) composite precipitates, and their amount increases with the increase in Nb content. Most of the two-phase particles (84%) precipitated in the steel with the Nb content of 0.031% are smaller than 80 nm, and the continuous increase in the Nb content cannot increase the precipitation amount of the two-phase particles in the steel, but can increase the size of the two-phase p... [more]

Transfer learning is a machine learning technique that takes a pre-trained model that has already been trained on a related task, and adapts it for use on a new, related task. This is particularly useful in the context of model predictive control (MPC), where deep transfer learning is used to improve the training of the MPC by leveraging the knowledge gained from related controllers. One way in which transfer learning is applied in the context of MPC is by using a pre-trained deep learning model of the MPC, and then fine-tuning the controller training for a new process automation task. This is similar to how an equipment operator quickly learns to manually control a new processing unit because of related skills learned from controlling the prior unit. This reduces the amount of data required to train the approximate MPC controller, and also improves the performance on the target system. Additionally, learning the MPC actions alleviates the computational burden of online optimization ca... [more]

Metronidazole, ornidazole, tinidazole, and secnidazole are 5-nitroimidazoles. The purpose of this work was to propose a new economical TLC−densitometric method to evaluate the chemical stability of metronidazole, secnidazole, ornidazole, and tinidazole under stress conditions. A forced degradation study was performed on silica gel and aqueous solutions at various pH values; the metronidazole, secnidazole, ornidazole, and tinidazole solutions were prepared in saline and in hydrogen peroxide, respectively. The samples of the 5-nitroimidazoles were heated. TLC analyses were performed on silica gel 60F254 using chloroform−methanol (9:1, v/v) as the mobile phase. As the TLC−densitometric method can effectively separate the metronidazole, secnidazole, ornidazole, and tinidazole from their degradation products which formed as a result of the stress studies, it is considered to can be a good alternative and important tool in the routine quality control and stability testing of metronidazole, s... [more]

As the working conditions of host equipment become more complex and severe, performance improvement and increased intelligence of high speed on/off valves (HSV) are inevitable trends in the development of digital hydraulic technology. The characteristics of HSVs can be regulated by control strategies, which determine the comprehensive performance of the system. This paper discusses the development of control strategies for HSVs. First, the results of research in relation to the discrete voltage and pulse control of single HSVs and the coding control of parallel HSVs are summarized. In addition, the advantages, disadvantages and application scope of different control strategies are analyzed and compared. Finally, the development trends are predicted from the performance regulation, intelligent maintenance, intelligent coding and function programmability.

Water-efficient products, a key component of water-saving technology, are widely installed and utilized in all sectors of society. Due to China’s extensive and varied use of this product, advancements in effectiveness and quality will significantly enhance people’s standard of living. In recent years, manufacturers, corporate purchasers, and individual customers have given more attention to the quality of these items due to the spike in local market and export demands for water-efficient products in China. It has been a pressing problem to find a practical solution for increasing product quality in a reasonable and scientific manner. In order to build a DECIA quality improvement model for water-efficient product quality that is quantifiable and technically practical, this paper investigates how to improve the quality of smart water closets based on six-sigma management. Thus, the development of a water-efficient industry can be green and sustainable.

Lab-on-a-Disc (LoaD) has great potential for applications in decentralised bioanalytical testing where speed and robustness are critical. Here, a disc-shaped microfluidic chip is rotated to pump liquid radially outwards; thus, all microfluidic structures must be fitted into the available radial length. To overcome this limitation, several centripetal pumping technologies have been developed. In this work, we combine buoyancy pumping, enabled by displacing aqueous samples and reagents centripetally inwards by a dense liquid (fluorocarbon FC-40), with dissolvable film (DF) to automate a multi-step assay. The DF dissolves in the presence of water but is not in contact with the FC-40. Therefore, the FC-40 can be stored behind the DF membranes and is autonomously released by contact with the arriving aqueous sample. Using this technology, tasks such as blood centrifugation can be located on the disc periphery where ‘disc real estate’ is less valuable and centrifugal forces are higher. To de... [more]

This paper investigates the imperfect premise matching-based (IPMB) static output feedback (SOF) controller for T−S fuzzy systems with time-varying delays. Firstly, by employing integral inequality techniques, the membership-function-independent fuzzy SOF design methods in terms of LMIs are presented based on imperfect premise matching (IPM) strategy. The obtained stabilization conditions do not contain equality constraints, and the output matrices do not have rank constraints. Secondly, some suitable relaxation variables are employed, and more relaxed membership-function-dependent (MFD) stabilization conditions are obtained by considering the local boundary information of membership functions (MFs). Finally, two simulation examples are given to show the progressiveness of the proposed methods in this paper.

Aluminium metal is avoided as main reactant in submerged arc welding (SAW) because it is easily oxidised in this process. Aluminium is an effective de-oxidiser and can be used to prevent Cr and Co loss to the slag by preventing oxidation of these metals. In our novel application of aluminium metal powder in SAW we demonstrate the modification of flux oxygen behaviour. The Co-Cr-Al-alloyed weld metal total oxygen content is decreased to 180 ppm O, compared to 499 ppm O in the weld metal from the original flux, welded without metal powder additions. The flux oxygen behaviour is modified by the added aluminium powder through the lowering of the original flux-induced partial oxygen pressure in the arc cavity and at the molten flux-weld pool interface. Carbon steel was alloyed to 5.9% Co, 6.3 % Cr and 5.1% Al at 81% Co yield, 87% Cr yield and 70% Al yield. Gas-slag-alloy thermochemical equilibrium calculations confirm the partial oxygen-pressure-lowering effect of aluminium. BSE (backscatte... [more]

The control of a simulated moving bed (SMB) is always a challenging chemical control topic due to its complexity and nonlinearity. Its mathematical model must undergo an affine transformation and digitization before it can be controlled. Basically, there are three aspects that need to be considered in the nonlinear control of an SMB. First, the nonlinear characteristics are more complicated due to the switching time parameters of discrete events. Second, the control objective is not to minimize the control output error, but to make the separated concentrations between the components of the substance reach a certain ratio. Finally, the control variables are highly coupled. So far, the vast majority of the industry still uses relatively simple PLC controls; a few use specific controllers based on materials to be separated such as model predictive controls and PID controllers. Therefore, there is no unified intelligent processing mode. In this paper, a type-II fuzzy controller is presente... [more]

Due to the growing complexity of industrial processes, it is no longer adequate to perform precise fault detection based solely on the global information of process data. In this study, a silhouette stacked autoencoder (SiSAE) model is constructed for process data by considering both global/local information and silhouette information to depict the link between local/cross-local. Three components comprise the SiSAE model: hierarchical clustering, silhouette loss, and the joint stacked autoencoder (SAE). Hierarchical clustering is used to partition raw data into many blocks, which clarifies the information’s characteristics. To account for silhouette information between data, a silhouette loss function is constructed by raising the inner block’s data distance and decreasing the distance of the cross-center block. Each data block has a properly sized SAE model and is jointly trained via silhouette loss to extract features from all available data. Using the Tennessee Eastman (TE) benchmar... [more]

The kinetics of nitroxide-mediated dispersion copolymerization with crosslinking of styrene (STY) and divinylbenzene (DVB) in supercritical carbon dioxide (scCO2) is addressed experimentally. 2,2,6,6-Tetramethylpiperidinyl-1-oxy (TEMPO) and dibenzoyl peroxide (BPO) were used as nitroxide controller and initiator, respectively. A high-pressure cell with lateral sapphire windows at 120 °C and 207 bar was used to carry out the polymerizations. The nitroxide-mediated homopolymerization (NMP) of STY, as well as the conventional radical copolymerization (FRC) of STY/DVB, at the same conditions were also carried out as reference and for comparison purposes. The effect of nitroxide content on polymerization rate, evolution of molecular weight averages, gel fraction, and swelling index was studied.

The purpose of this study was to develop an integrated control strategy for multiscale crystallization processes. An image analysis method using a deep learning neural network is used to measure the fine-scale information of the crystallization process, and the mathematical statistical method is adopted to obtain the mean size of the crystal population. A feedforward neural network is subsequently trained and employed in a nonlinear model predictive control formulation to obtain the optimal profile of the manipulated variable. The effectiveness of the proposed nonlinear model predictive control method is evaluated using alum cooling crystallization experiments. Experimental results demonstrate benefits of the proposed combination of feedforward neural network and nonlinear model predictive control method for the multiscale crystallization process.

A remotely operated underwater vehicle (ROV) is crucial in ocean exploration and underwater missions. An ROV is manipulated through a tether cable by an operator on shore or mother boat, and it can be used for underwater observations or as a robotic arm to take samples back. The position control and movement of an ROV are not stable due to buoyancy, ocean current, and surge waves. To overcome the influence of these disturbances on the ROV, we propose a switch proportional-integral (PI) controller combined with a buck-boost converter (BBC) to process the ROV’s position following. In this paper, a six-axis ROV was designed and implemented. The ROV controller was designed by a NI-roboRIO-based embedded system, which includes a pressure sensor, an accelerometer, six thrusters, and two webcams. The LabVIEW human−machine interface was designed to integrate the control system, sensors, and thrusters. The PI controller was employed to perform the station-keeping and trajectory following. Diffe... [more]

Hemorrhage remains a leading cause of preventable death in emergency situations, including combat casualty care. This is partially due to the high cognitive burden that constantly adjusting fluid resuscitation rates can require, especially in austere or mass casualty situations. Closed-loop control systems have the potential to simplify hemorrhagic shock resuscitation if properly tuned for the application. We have previously compared 4 different controller types using a hardware-in-loop test platform that simulates hemorrhagic shock conditions, and we found that a dual input—(1) error from target and (2) rate of error change—fuzzy logic (DFL) controller performed best. Here, we highlight a range of DFL designs to showcase the tunability the controller can have for different hemorrhage scenarios. Five different controller setups were configured with different membership function logic to create more and less aggressive controller designs. Overall, the results for the different controlle... [more]