Development and Application of On-Line Corrosion Monitoring Device for Condenser Tube

This paper introduces the development and industrial application of an on-line corrosion monitoring device for condenser tubes. Corrosion sensors are made up of representative condenser tubes chosen by eddy current test, which enable the monitoring result to be consistent with the corrosion of actual condenser tubes. Localized corrosion rate of condenser tubes can be measured indirectly by a galvanic couple made up of tube segments with and without pits. Using this technology, corrosion problems can be found in time and accurately, and anticorrosive measures be made more economic and effective. Applications in two power plants showed the corrosion measurements are fast and accurate.

On-Line Monitoring of Cutting Tool Fracture & Wear

A technique of detecting cutting tool fracture and ultimate wear by si- multaneously monitoring both the spindle motor current and cutting process related acoustic emission(AE)in the cutting process is reported.The technique can detect breakage of drills having diameter over 0.8mm,turning cutter crack of area over 0.2mm,and the ultimate wear.The principle,system construction,experimental method and result of the technique are discussed.The ratio of success in detection approaches 96% or higher.

Industrial LAN for Vibration Monitoring and Fault Diagnosis of Turbo-Generator

The unique of using industrial LAN based on field bus to construct the system of vibration monitoring and fault diagnosis is introduced. The LAN topology, client/server architecture, database and designing of application software for vibration monitoring and fault diagnosis are involved. How to apply industrial LAN to the vibration monitoring and fault diagnosis of turbo generator is discussed, and a scheme of how to construct the industrial LAN for vibration monitoring and fault diagnosis of turbo generator is presented.

Fault diagnosis and analysis of main sea water pump based on vibration monitoring in offshore oil field

The main sea water pump is the key equipment for the floating production storage and offloading （FPSO）. Affected by some factors such as hull deformation, sea water corrosion, rigid base and pipeline stress, the vibration value of main sea water pump in the horizontal direction is abnormally high and malfunctions usually happen. Therefore, it is essential to make fault diagnosis of main sea water pump, By conventional off-line monitoring and vibration amplitude spectrum analysis, the fault cycle is found and the alarm value and stop value of equipment are set, which is helpful to equipment maintenance and accident prevention.

Monitoring and Assessing Method for Blasting Vibration on Open-pit Slope in Hainan Iron Mine

A type of velocity sensor CD 1, an auto recording instrument on blasting vibration YBJ 1 and a random signal and vibration analysis system (CRAS) were used to monitor the particle vibration induced by blasting at open pit slope in Hainan Iron Mine. The attenuating rules of blasting ground vibration on slope were developed. By means of the analysis and calculation of the blasting vibration data at open pit slope and the vertical particle vibration velocity assessment method based on the concept of vibration strength, the empirical attenuating equations which can be used for predicting and estimating the damage of slope were derived.

Variational Mode Decomposition for Rotating Machinery Condition Monitoring Using Vibration Signals

The failure of rotating machinery applications has major time and cost effects on the industry.Condition monitoring helps to ensure safe operation and also avoids losses.The signal processing method is essential for ensuring both the efficiency and accuracy of the monitoring process.Variational mode decomposition(VMD)is a signal processing method which decomposes a non-stationary signal into sets of variational mode functions(VMFs)adaptively and non-recursively.The VMD method offers improved performance for the condition monitoring of rotating machinery applications.However,determining an accurate number of modes for the VMD method is still considered an open research problem.Therefore,a selection method for determining the number of modes for VMD is proposed by taking advantage of the similarities in concept between the original signal and VMF.Simulated signal and online gearbox vibration signals have been used to validate the performance of the proposed method.The statistical parameters of the signals are extracted from the original signals,VMFs and intrinsic mode functions(IMFs)and have been fed into machine learning algorithms to validate the performance of the VMD method.The results show that the features extracted from VMD are both superior and accurate for the monitoring of rotating machinery.Hence the proposed method offers a new approach for the condition monitoring of rotating machinery applications.

On-line Monitoring for Phosphorus Removal Process and Bacterial Community in Sequencing Batch Reactor

For efficient energy consumption and control of effluent quality, the cycle duration for a sequencing batch reactor (SBR) needs to be adjusted by real-time control according to the characteristics and loading of waste-water. In this study, an on-line information system for phosphorus removal processes was established. Based on the analysis for four systems with different ecological community structures and two operation modes, anaerobic-aerobic process and anaerobic-anaerobic process, the characteristic patterns of oxidation-reduction potential (ORP) and pH were related to phosphorous dynamics in the anaerobic, anoxic and aerobic phases, for determination of the end of phosphorous removal. In the operation mode of anaerobic-aerobic process, the pH profile in the anaerobic phase was used to estimate the relative amount of phosphorous accumulating organisms (PAOs) and glycogen accumulat-ing organisms (GAOs), which is beneficial to early detection of ecology community shifts. The on-line sensor val-ues of pH and ORP may be used as the parameters to adjust the duration for phosphorous removal and community shifts to cope with influent variations and maintain appropriate operation conditions.

Field monitoring of railroad embankment vibration responses in seasonally frozen regions

To investigate the vibration characteristics of a railway subgrade in different seasons, three field experiments were carried out in the seasonally frozen Daqing area of China during spring, smnmer, and winter. The vibration characteristics and attenuation rates of the subgrade induced by passing trains were investigated, and the influences of the season, train speed, train type, train load, and number of train compartments are described in this paper. The results show that： （1） near the rail track the vibration in the vertical direction was more significant than in the lateral and longitudinal directions, and as the distance from the railway track increased, the acceleration amplitudes and the attenuation rates all decreased in all three directions; （2） the acceleration amplitudes and at- tenuation rates decreased in the three different study seasons as the distance from the railway track increased, and the attenuation rates in the freezing period were the largest; and （3） the acceleration amplitude induced by a freight train was greater than that by a passenger train, and the subgrade vibration increased with increasing passenger train speeds when the number of train compart- ments was similar. These results have great significance for enhanced understanding of the characteristics of wain-induced vibra- tion embankment response in seasonally frozen regions, and provide essential field monitoring data on train-induced vibrations in order to improve the performance criteria of railroading in seasonally frozen regions.

Vibration Deformation Monitoring of Offshore Wind Turbines Based on GBIR

In view of the disadvantages of vibration safety monitoring technology for offshore wind turbines,a new method is proposed to obtain deformation information of towering and dynamic targets in real-time by the ground-based interferometric ra-dar(GBIR).First,the working principle and unique advantages of the GBIR system are introduced.Second,the offshore wind turbines in Rongcheng,Shandong Province are selected as the monitoring objects for vibration safety monitoring,and the GPRI-II portable radar interferometer is used for the health diagnosis of these wind turbines.Finally,the interpretation method and key processing flow of data acquisition are described in detail.This experiment shows that the GBIR system can accurately identify the millimeter-scale vibration deformation of offshore wind turbines and can quickly obtain overall time series deformation images of the target bodies,which demonstrate the high-precision deformation monitoring ability of the GBIR technology.The accuracy meets the requirements of wind turbine vibration monitoring,and the method is an effective spatial deformation monitoring means for high-rise and dynamic targets.This study is beneficial for the further enrichment and improvement of the technical system of wind turbine vibration safety monitoring in China.It also provides data and technical support for offshore power engineering management and control,health diagnosis,and disaster prevention and mitigation.

Research on Distribution of Electromagnetic Environment around Substations and Optimization Layout of On-line Monitoring

The characteristics and distribution law of electromagnetic environment around substations with different levels of voltage were studied,and the main influencing factors were discussed. Meanwhile,a scheme for locating monitoring points suitable for an on-line monitoring system of electromagnetic environment was proposed.

On-line monitoring of dissolved gas-in-oil with FTIR spectra

To overcome the disadvantages of conventional DGA (dissolved gas-in-oil)analysis using gas chromatography and other electrochemical sensors, initial researches werecompleted to realize on-line monitoring of dissolved gas-in-oil of power transformers using FTIR(Fourier Transform InfraRed) spectroscopy. Gas cell method is used to determine the characteristicabsorption peaks of each diagnostic gas; simple and novel devices and procedures were designed inorder to get measurable samples and spectra of mixed diagnostic gases with known concentration aretaken using long optical path gas cell. The range of wavelength is estimated to be 3.0-13.9 mum fromexperimental spectra data. Hence the corresponding sampling frequency range should be in 536-4288Hz and usable optical materials are suggested. It is concluded that a resolution of 10 cm^(-1) maywell satisfy the monitoring of all diagnostic gases and water content except hydrogen, and thelowest detection limit may be as low as 2Xl0^(-8) to acetylene with a 2.4-meter-long optical length.

Health Monitoring of Milling Tool Inserts Using CNN Architectures Trained by Vibration Spectrograms

In-process damage to a cutting tool degrades the surface􀀀nish of the job shaped by machining and causes a signi􀀀cant􀀀nancial loss.This stimulates the need for Tool Condition Monitoring(TCM)to assist detection of failure before it extends to the worse phase.Machine Learning(ML)based TCM has been extensively explored in the last decade.However,most of the research is now directed toward Deep Learning(DL).The“Deep”formulation,hierarchical compositionality,distributed representation and end-to-end learning of Neural Nets need to be explored to create a generalized TCM framework to perform eciently in a high-noise environment of cross-domain machining.With this motivation,the design of dierent CNN(Convolutional Neural Network)architectures such as AlexNet,ResNet-50,LeNet-5,and VGG-16 is presented in this paper.Real-time spindle vibrations corresponding to healthy and various faulty con􀀀gurations of milling cutter were acquired.This data was transformed into the time-frequency domain and further processed by proposed architectures in graphical form,i.e.,spectrogram.The model is trained,tested,and validated considering dierent datasets and showcased promising results.

Sensor Layout of Hoisting Machinery Vibration Monitoring Based on Harmony Genetic Search Algorithm

With the construction of automated docks,health monitoring technology as a parallel safety assurance technology for unmanned hoisting machinery has become a hot spot in the development of the industry.Hoisting machinery has a huge structure and numerous welded joints.The complexity and nonlinearity of the welded structure itself makes the structural failure parts random and difficult to arrange for monitoring sensors.In order to solve the problem of effectiveness and stability of the sensor arrangement method for monitoring the structure of hoisting machinery.Using the global and local search capabilities enhanced by the complementary search mechanism,a structural vibration monitoring sensor placement algorithm based on the harmony genetic algorithm is proposed.Firstly,the model is established for modal analysis to obtain the displacement matrix of each mode.Secondly,the optimal parameter combination is established through parameter comparison,and the random search mechanism is used to quickly search in the modal matrix to obtain the preliminary solution,and then the preliminary solution is genetically summed The mutation operation obtains the optimized solution,and the optimal solution is retained through repeated iterations to realize the decision of the vibration sensor layout of the crane structure monitoring.Combining the comparison test of harmony genetic algorithm,harmony search algorithm and genet-ic algorithm,the fitness of harmony genetic algorithm in X,Y and Z directions were 0.0045,0.0084 and 0.0058,respectively,which were all optimal.And the average probability of deviating from the optimal path is 1.10%,19.34%,and 54.43%,which are also optimal.Harmony genetic algorithm has the advantages of simplicity,fastness and strong global search ability,and can obtain better fitness value and better search stability.

Vibration Signals and Condition Monitoring for Wind Turbines

Rolling element bearings are critical parts of modern wind turbines as they carry the loads of the turning structure and the wind force. The stochastic nature of the wind loads makes it difficult to estimate the useful operational life of the bearings. Condition monitoring of these bearings in a real time environment could be very helpful in estimating their performance and in scheduling maintenance actions when a condition-based maintenance strategy is followed. This procedure can be successfully implemented by using vibration analysis in the time domain or in the frequency domain, giving useful results about the current condition of bearings and the location of potential faults. Permanently located transducers on proper positions on the bearings’ housings can be used in order to collect, process and evaluate real time measurements and provide information about the bearing’s performance. In this work, a test rig is utilized in order to evaluate the performance of rolling bearings. The results of the experimentation are satisfactory and the progress of fatigue failures can be predicted through vibration analysis techniques showing that implementation in real scale may be useful.

Monitoring and Detection of Wind Turbine Vibration with KNN-Algorithm

Maintenance for wind turbines has been transformed using supervised machine learning techniques. This method of automatic and autonomous learning can identify, monitor, and detect electrical and mechanical components of wind turbines and predict, detect, and anticipate their degeneration. Using a machine learning classifier and frequency analysis, we simulate two failure states caused by bearing vibrations. Implementing KNN facilitates efficient monitoring, monitoring, and fault-finding for wind turbines. It is possible to reduce downtime, anticipate breakdowns, and import offshore aspects through these technologies.

Research on the Correlation Between Oil Menitoring and Vibration Monitoring in Information Collecting and Processing Monitoring

Oil monitoring and vibration monitoring are two principal techniques for mechanical fault diagnosis and condition monitoring at present. They monitor the mechanical condition by different approaches, nevertheless, oil and vibration monitoring are related in information collecting and processing. In the same mechanical system, the information obtained from the same information source can be described with the same expression form. The expressions are constituted of a structure matrix, a relative matrix and a system matrix. For oil and vibration monitoring, the information source is correlation and the collection is independent and complementary. And oil monitoring and vibration monitoring have the same process method when they yield their information. This research has provided a reasonable and useful approach to combine oil monitoring and vibration monitoring.

Design on Vibration Monitoring and Fault Diagnosis System of Large Water Pump Motor

Large water pump motor,whose operation decides the reliability of the whole production line,plays a very important role.Therefore,its online condition monitoring can help companies better know its operation,process fault analysis and protection.The essay mainly studies and designs large water pump motor′s real time vibration monitoring and fault diagnosis system.The essay completes the systems project design,the establishment of the system and performance test.Eddy-currentsensor,XM-120 vibration module,XM-320 axial translation module,XM-362 temperature module,XM-360 process amount module and XM-500 gateway module are used to measure the axial vibration and displacement of main motors.Laboratory tests prove that the system can meet the requirements of motor vibration monitoring.

Vibration Severity Monitoring and Evaluation of Armored Vehicle Transmission

Vibration monitoring and vibration severity evaluation of armored vehicle transmission are realized by additional sensors. An algorithm of vibration severity in frequency domain is presented. The algorithm has powerful applicability for signal type and flexible selectivity for frequency range,and avoids the processing of signal conversion used calculus and filtering compared to the algorithm of vibration severity in time domain. An applied example is given in company with attentive proceedings and measures for improving evaluation effect.

On-line Condition Monitoring and Diagnostic Network System for Rotating Machine Set

Several industrial computers and a server are combined to set up the on-line monitoring and diagnostic system of turbo-generator sets. The main function of the system is to monitor machine sets' running condition. Through analyzing running data, technicians can detect whether there exist faults and where they occur. To share and transmit the dynamic information of the turbo-generator sets, a distributed network system is introduced. NetWare network operating system is used in the LAN (Local Area Network) system. The LAN is extended to realize the sharing of data and remote transmission of information. Furthermore, functions of monitoring and diagnostic clients are listed.

On-line monitoring of insulation quality of high voltage electric power equipment

Discusses on-line monitoring of electric parameters, such as dielectric loss, divulging current, equivalent capacitance and running voltage, and presents an on-line monitoring system of insulation quality, based on monitoring divulging current and dielectric loss of high voltage equipment, and its advantages, such as helping people to discover the hidden problems in a timely manner, to reduce power cut and overhaul and to improve security of power supply.