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Ion pump control system of HIRFL is designed based on the real-time distributed control software, EPICS. The hardware architecture, communication principle, database design and interlock design are introduced and elaborated in the paper. PLC has been adopted to realize functions such as control monitoring and data communication. Interlock protect ion has been designed for ion pump control system to prevent damaging from high voltage. The test results show that the system has fast response function and high-speed data processing during the beam running and tuning. The response time of the system could reach 100 ms, the rate of data acquisition reaches to 10 time/s and the interlock protection time less than 40 ms. The reliable and stable long-term operation of the vacuum system indicates that the performance has been constantly improved with the continuous optimization of the ion pump control system.

Plant dye is a promising dyestuff to be used in textiles due to its unique environmental compatibility. However, currently there is no effective method for the identification of plant-dyed and chemical-dyed textiles. In this study, near-infrared (NIR) spectroscopy combined with three kinds of pattern recognition methods, namely soft independent modeling of class analogy (SIMCA), partial least squares (PLS) regression and principal component regression (PCR), were applied to identify cotton fabrics dyed with plant and chemical dyes. A total of 336 plant dye and chemical dye dyed cotton fabrics were prepared and the NIR spectra were collected; 267 samples were used as the calibration set, while the remaining 69 samples were used as the validation set. After pretreatment with the Savitzky–Golay first derivative, the calibration model was constructed. In the SIMCA model, the correct recognition rate values of the calibration and prediction sets were 100% and 98.55%, respectively. The PLS model showed that the number of principal components (PCs) and the correlation coefficient ( R2) were 8 and 0.9978, respectively, and the results of PCR were PC = 10, R2 = 0.9937. Both methods were satisfactory for the predicted results. The overall results indicated that NIR spectroscopy could be used for rapid and nondestructive identification of plant-dyed cotton fabrics and chemical-dyed cotton fabrics.

Status monitoring is a crucial part of the accelerator control and operating system and real-time performance of status monitoring control system is claimed higher and higher. Therefore, many special designed methods are proposed for the different status monitoring systems. The purpose of this paper is to classify and assess the system of vacuum control, temperature control and radiation dose monitoring which are based on EPICS used for many large scientific equipments. The water leakage detection and alarm system developed based on EPICS by the author is introduced in the last of this paper. The result manifests that the stability and accuracy of these monitoring system could meet design requirements exactly.

The paper proposes a method to analyze root causes of occurring alarms, for a special type of alarm variables in thermal power plants, where alarms are arisen from binary-valued root-cause variables. A Bayesian network with one child node and multiple parent nodes is used to describe the relationship between an alarm variable and root-cause variables. Probability parameters in the network are updated recursively. Root causes of occurring alarms are determined from the parent node set with the largest posterior conditional probability. The proposed method can remove negative effects of false and missing alarms in the nodes, handle the co-existence of multiple root causes, and detect the incompleteness of known root causes. Industrial examples are provided to illustrate the effectiveness of the proposed method.

Primary frequency control (PFC) responses for thermal power generation units are concerned about whether changes of turbine rotating speeds lead to proper responses of generator active powers. A new method is proposed to estimate performance metrics for PFC responses via system identification techniques. Dynamic models are identified from data samples of the turbine rotating speed and the main steam pressure as two inputs, and the generator active power as the output. Hypothesis tests are formulated to evaluate the qualities of identified models. If model qualities are satisfactory and the contribution from the turbine rotating speed to the generator active power is significant, then performance metrics are estimated from a noise-free unit step response of the identified model. The proposed method removes three major limitations of the most widely-used method in contemporary industrial practices, namely, (i) performance metrics are obtained from all data samples of PFC responses, instead of some specific data samples being sensitive to noises; (ii) the proposed method is applicable to arbitrary-type PFC responses, not limited to step changes of the turbine rotating speed; (iii) noticeable effects of the main steam pressure are separated to avoid erroneous performance assessment results. Examples from thermal power generation units are provided to illustrate the effectiveness of the proposed method.

Mathematical models of dynamic processes are often required for assessment, diagnosis and improvement of control loop performances in process industries. Data samples collected in daily operations of feedback control loops may enclose data segments suitable for process identification to obtain the mathematical models. This paper proposes a new method to search such data segments. The searching criterion is that the reference and process output in a feedback control loop should experience significant magnitude changes. Hypothesis tests are exploited to find changing positions of data segments with different probability distributions and to verify whether the reference and process output make significant magnitude changes inside one data segment or between two adjacent segments. Simulation and industrial examples are provided to illustrate the effectiveness of the proposed method.

To solve the problem of submarine cable route tracking, a multi way-points tracking control approach was designed based on Single Neuron Adaptive Proportional-Integral-Derivative controller (SNA-PID). Dynamic model of Remotely Operated Vehicle (ROV) was set up and simplified according to its kinetic characteristics and the actual needs of oceanic engineering application. Three SNA-PID controllers were used to control ROV's heading, surge velocity and sway velocity. And the LOS (line of sight) was utilized to guide ROV motion to track predefined way-points.

Optimal design is critical to the efficient operation of the combined cooling heating and power (CCHP) system, different design combinations will definitely lead to different characteristics. However, the problem of balancing different system performance by regulating the capacity of facilities and key parameters still remain unclear. This paper designs a CCHP system with the storage unit and the electric chiller. A multi-objective model considering the energetic, economic and environmental benefits has been built, aiming to optimize the rated power of the power generation unit (PGU), the capacity of storage unit, the electric chilling ratio and the on-off coefficient of the PGU. Moreover, the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is adopted to solve the optimal model, thus obtaining multiple optimal designing combinations focusing on different performance. The energy saving rate is chosen as an example, which is used for revealing the inherent effects of all designing parameters on the system performance. Furthermore, the coupling relationships between these objectives are quantified, thereby providing the reliable method of balancing the benefits of all participants for the decision-makers in the designing process.

Traditionally the evaluation and supervision of peak shaving operation of thermal power units depend on the simple variable of the minimum achievable load. This method didn't consider the rate of load change and the startup/shutdown time of units, and ignored the safety, emission and economy properties of the units. In addition, the peak shaving operation data of the units were acquired by means of steady-state field tests, it is difficult to obtain the unit's real-time low load operation properties and unable to achieve the real-time supervision. Based on the massive real-time and historical database, the Peak Shaving Real-time Supervision System was developed. By introduced the conception of Real-time Peak Shaving Coefficient, the properties of load regulation, safety, economy and emission of the units were integrated to present the peak shaving operation properties reasonably. This work will be a great help to achieve the real-time supervision of the peak shaving operation of the units, and will improve the safety, economy and emission performance of the power grid.

In order to cope with the incompatibility of traditional AGC control under CPS control performance standard, this paper proposes a hierarchical control framework based on DQN algorithm. It effectively solves the problem of dimensionality disaster of Q learning by using neural network instead of state action pair, and speed up the convergence. Through simulation verification, this method can effectively improve the system CPS control performance index and effectively reduce the system power generation cost.

Based on the demand for deep-sea submarine cable salvage in Northeast Asia, a mathematical model of Sub Marine Tracked Vehicle-Cable Salvage (SMT-CS) was designed in this study. Considering the slip characteristics of the submarine track, the mechanical model of the SMT-CS during steady-state steering was simplified to obtain the kinetic equation of the vehicle body during steady-state steering. According to the steering geometrical relationship, the arbitrary shear rate and shear displacement of the ground plane during the steering process were solved. Combined with the empirical shear model of bottom sediments, the longitudinal driving force, lateral resistance and resistance moment of the larboard and starboard were derived during steady-state steering. The functional relationship between the lateral shift of instantaneous center of the conventional steering rate and the turning radius and angular velocity of the vehicle body as well as that between the slipping rate and the turning radius and angular velocity of the vehicle body was derived according to the geometrical relationship of steering motion. These are of great reference value to the design, performance prediction and maritime application of SMT-CS in the future.

According to the testing methods, filthy degree measurement can be divided into direct detection and indirect detection. This paper reviewed the development history of impurity detection and the current status quo at home and abroad. On the basis of existing research, impurity detection technology application situation, analysis their respective advantages and disadvantages, summarized power system layout is structured and disadvantages. Impurity detection to seek new breakthroughs to integrated a variety of integrated pollution direct detection methods, build a real-time monitoring system, realize the insulator filth adherent state of timely, accurate, in order to reduce the pollution flashover accident and provide support for power grid external insulation protection.