Implementation Of On-line Monitoring Research Articles

Development of a Numeric Method to Validate the Reliability Improvement of Safety Critical Valves During Operation Through Online Monitoring Implementation

Online valve monitoring, also called “ValveWatch,” is a state-of-the-art method for improving the reliability of safety critical valves during operation. This well-known method has been used for almost two decades to reveal the possible failures of valves, actuators and control systems. This paper reviews some of the existing literature about ValveWatch technology to provide more detailed information about this online monitoring approach and its benefits. The possible causes and effects of failures associated with safety critical valves based on the existing literature are identified and summarized in this paper. Safety critical valves mainly include Emergency Shut Down and Process Shut Down (PSD) valves connected to Process Shut Down (PSD) systems. Three types of sensors that comprise part of the ValveWatch system will be identified and explained in this paper: the stain gauge, the dynamic pressure gauge and the static pressure gauge on the actuator. The function and logic of these three sensors are explained in this paper. All of the problems associated with valves, actuators and control system are identified and listed in a table and the probability of detecting these failures through visual inspection as well as online monitoring is assessed. A method of utilizing equations to calculate the probability of failure detection for valves, actuators, control system and the whole assembly through visual inspection as well as using sensors is developed. Additionally, the methodology given in functional safety and International Electrotechnical Commission 61,508 to calculate Diagnosis Coverage is used in this paper, and future research work to address condition monitoring for pressure safety valves and check valves is proposed. A Separate research is required to improve the reliability of the ValveWatch system.

Modeling the electrostatic control over depth of the introduction of intelligent sensors into a polymer composite material

Intelligent polymeric composites are materials that can remotely transmit data on the properties of material, including the stress-strained state. It is necessary for the implementation of online monitoring of critically important parts and nodes. Obtaining data is achieved by the introduction of intelligent sensors into a polymer composite. Intelligent sensor is a miniature measuring device consisting of one or more transducers of measured magnitudes. They form an output signal, which is used for the remote transmission, storage and use in the control systems. A problem of obtaining data about the depth of the introduction of intelligent sensors into polymer composites is a multifaceted one. On one hand, the question is about technology and equipment for the introduction of sensors into polymer composites, the interpretation of data on deformations and other properties received from the sensors, and is connected to polymer engineering. On the other hand, the question of receiving signals about the depth of placement of intelligent sensors and their further processing is associated with nondestructive control. The present article investigated the possibility of receiving a signal about the depth of placement of intelligent sensors that are introduced at a certain depth into a polymer composite material, using the electrostatic method of nondestructive testing. We performed a simulation of the distribution of electric potential in the material. Through modeling, we determined maximum possible depth of the introduction of intelligent sensor into polymer material, which can be measured with a given accuracy, which is 40H, where H is the relative magnitude of the size of electrodes. The technique applied might be used to any dielectric material after adjusting the properties of material. The obtained results allow the determination by numerical simulation of maximum depth of the introduction of intelligent sensors into a polymer material.

Compressive sensing and sparse decomposition in precision machining process monitoring: From theory to applications

Precision machining has been claimed to be the backbone to modern industry. It has been widely applied to the key parts’ production in the aerospace, medical and automotive industries. One of the main problems related to precision machining productivity and safety is the machining condition. By utilizing the acquired information from sensory measurements to direct the further actions, the signal processing bridges the gap between human instruction and full automation. Traditional signal acquisition and processing methods are mainly based on Shannon’s Sampling theory, Fourier methods or wavelet analysis. While these techniques meet challenges in precision machining environment, such as machining at high speed, low signal to noise ratio, and high sampling rate. These factors limit their applications especially the online monitoring implementation. The newly developed compressive sensing theory and sparse decomposition techniques provide a possible solution to these problems, while limited studies have been investigated. This paper serves as an introduction to the theory and shows the theory’s potentials in machining condition monitoring by reviewing related literatures and demonstrating case studies from real experiments.

Design and Implementation of Online Monitoring and Remote Diagnostic System for CNC Machine Tools

With the development of network technology and fault diagnosis technology, monitoring and diagnosis methods for the CNC machine tools had a great change. In this paper, an online monitoring and remote diagnosis system for CNC machine tools was built. The system was consisted of the multi-channel online acquisition system and remote fault diagnosis system. The online acquisition system achieved a real-time monitoring for CNC machine tools. The remote fault diagnosis system provided the management of devices and assistant for experts to analyze data which was uploaded from acquisition system. The system offered real-time state information of CNC machine tools and reduced downtime of machine effectively.

Design and Implementation of Online Monitoring and Calibration Platform for Anti-lock Braking System

To speed up ABS development, the online monitoring and calibration platform for mobile anti-lock breaking system was developed. Using USB to CAN module and CCP calibration protocol, real-time communication between platform and ECU was realized. The inspection management module, calibration management module, parameters optimization module and files management module were developed using VC++. Thus, the control effect real-time monitoring, control logic offline analysis, control algorithm flow offline analysis, control effect evaluation, control parameters optimization and control parameters online calibration were realized to provide a strong tool for ABS control algorithm development and road test. The control system for certain kind of camion was developed and road tests based on the platform were done. The result shows that the platform can not only analyze the logic of control algorithm and the control effects, but also evaluate the control effect and optimize the online control parameters. The ABS development was speeded up greatly by using the platform.