Elevators in the building are the main vertical traffic system and they transport passengers to their destination floors conveniently. The ordinary elevator system uses the rope traction mechanism which moves the rope and drive pulley simultaneously by the friction force. Therefore, the regular maintenance is required to keep the proper friction force to the drive pulley. In this paper, we propose Rope Slip Observer (RSO) as a support tool for the maintenance. As RSO can estimate the rope slip on the drive pulley induced by friction reduction, it can watch the friction condition of the traction system in real time. Firstly, fundamental equations of motion for the traction elevator system are derived and a simple RSO model is proposed by the equations. Secondly, the proposed RSO model is improved by adding more detailed parameters of the actual elevator system. Finally, the improved RSO model is evaluated by experiment and we can conclude that the estimated rope slip by RSO model shows the same response as the measured one.

To unexpected accident under long term operation of reciprocating compressor, a newly monitoring system, which can predict something trouble and efficiently support during compressor operation periodic maintenance work. the purpose of this study is to build a dynamic model that is able to analyze the frequency characteristic for the acceleration response during compressor operation. By using multi body dynamic models representing connections and sliding portions of the compressor by a spring and dash pod, we perform numerical analysis for the acceleration response during compressor operation. Comparing numerical analysis with the experimental result of the experimental equipment, we consider validity of analysis models when we change dynamic model and attenuation characteristic.

This study aims at quantifying malfunctioning in the reciprocating compressor and establishing a new monitoring technique. We proposed a mathematical model (eleven degrees of freedom) in which deterioration and damage are expressed by changing model parameters. Our proposed method is simultaneously monitoring the damaged portion and the extent on the reciprocating compressor by estimating the stiffness change of the connecting portion and the sliding portion corresponding to the frequency characteristics change of the system in accordance with the long-term continuous operation. In this paper, we examined the vibration characteristics for reciprocating compressor using the analysis based on the rigid model and vibration test for a small experimental equipment. To investigate the relationship of the sliding portion characteristic change and the frequency characteristics during operation, we employ two kinds of the material, carbon and molybdenum steel as the ring bush of the ground support. As a result, it was confirmed by numerical analysis and experiment test the relationship between the sliding portion and frequency response during operation. In addition, it was possible to estimate the vibration characteristics by using the proposed model.

Structural materials (cast iron etc.) undergoing brittle failure produce large number of acoustic emission (AE) events with varying amplitudes. A common and useful method of describing the amplitude distribution of AE signals is by explaining their b-values (slope of the log-linear frequency magnitude distribution of AE events). Conventionally, the b-value of AB is computed by using the methods adopted in seismology since many similarities exist between AE and seismic waves. The b-value is usually obtained either from the cumulative frequency distribution or the discrete frequency distribution of earthquake magnitudes and the same principles hold good for the AE data also. Therefore, b-value characterized by the Gutenberg and Richter’s relations have been investigated according to the Aki’s modification for AE events due to material cracks or crack damages of structural materials. We applied Aki’s proposed Maximum likelihood method for calculating b-values from AE maximum amplitude distribution for acquired AE events during the crack damage experiments in tensile loading to ductile iron (pearlite). The calculation shows good evidence about crack initiation, propagation and damage phenomena as well comparing with microstructural video data.

Bolted joints are widely used in mechanical and architectural structures. However, many serious accidents occur because of loosening of bolted joints. Conventionally, the inspection method of the loosening bolted joint is generally the measurement of axial tension of a bolted joint by using ultrasonic waves. These methods require the use of special measurement equipment and the human operation. In this study, a smart washer was proposed to detect the loosening without human involvement. The smart washer is in cantilever type with piezoelectric material, which adds the washer of the self-sensing and actuating function. Previous research had indicated that a correlation was confirmed between the natural frequency of the smart washer and the tightening axial tension with the theoretical and experimental results. The subject of this method is to identify the natural frequency of the smart washer by changing the bolt tightening axial tension, which is using the self-sensing and actuating by applying the piezoelectric material. This paper describes the natural frequency identification method for smart washer with the adaptive observer by fixed and variable adaptive law. The influences of initial parameter vector were considered computationally and experimentally when applying the adaptive observer.

In this paper, a health monitoring methodology for a structure with bolted joints based on nonlinear piezoelectric impedance modulation method (NPIM method) is presented. This technique uses a single piezoelectric active sensor bonded on the structure surface, which is driven by a high frequency harmonic voltage source. When the structure including a contact surface such as a bolted joint is subjected to a pump excitation at low frequency, the induced structural vibration causes a fluctuation in the driving point mechanical impedance at high frequency range because of the contact acoustic nonlinearity at the contact surface in the structure. This causes a modulation of the coupled electro-mechanical admittance of the piezoelectric active sensor, which can be observed as the amplitude modulation and the phase modulation of the current. The healthiness of the bolted joint was evaluated based on NPIM method, and a positive correlation between the bolt axial force and the damage index was found.

境界潤滑から流体潤滑への行こうと潤滑,摩耗,を改善するために,ポリオールエステル,ジエステル系と植物油系エステル化合物などを主成分とした独自の新還元添加剤を開発し,潤滑面に固着したコンタミ,スラッジやワニスなどの吸着分子層の除去・溶解により,オイルクリアランスを再生し,トライボロジー性能に及ぼす影響を実験的に測定した。エンジンやデファレンシャルギアなどの金属表面を覆う汚れを元の金属表面に復元された事例や想定されるメカニズムを示し,自動車と産業機械用における新合成潤滑油のトライボロジー性能を化学的・物理的作用と実用試験などにより検証した。

Recent years, bearings frequently suffer from early damage caused by flaking. This is thought to be due to hydrogen embrittlement in connection with hydrocarbon decomposition when greases contact the nascent metal surface created under the current severer frictional situations. This study proposes the evaluation method of grease decomposition and hydrogen generation by a controlled atmosphere cutting apparatus. Mass spectrometry of this method provided the evidences of hydrogen generation and hydrocarbon decomposition in relation to the nascent metal surface appearance by cutting. The further investigation demonstrated additives in greases greatly influenced the grease decomposition and the hydrogen generation.

Because a lot of factors are controlled as for friction and wear phenomena between solids, it is complex and the forecast is difficult. There is a transfer film formation as the one phenomenon. The transfer film is a film formed to the entire friction surface with the transfer and remaining of the transfer particle in the friction surface, and the tribological characteristic changes greatly by the process of formation. In this study, the transfer film formation process was observed using acoustic emission while observing in situ with a high-speed camera. And, the evaluation and diagnosis of friction and wear phenomena that one by one changed were examined.

The Hamaoka Nuclear Power Station is improving plant reliability with condition monitoring technology. Vibrationdiagnosis, Lubricant diagnosis and Infrared Thermography diagnosis has been applied to the station. We have been doingthat activity for 12 years at the power station. We had many techniques for improving quality of the activities throughthe years. This paper presents these techniques of Infrared Thermography diagnosis.

The demand of inspection and diagnosis robot for plant machinery becomes increasingly large, because the request of the safety and reliability for the plant equipment is increasing. The inspection and diagnosis robot must monitor the condition of many plant machines at the same time. So it must not only inspect machine condition at prescribed inspection points, but also automatically move to a faulty machine after an abnormal state has been detected, in order to precisely identify faulty parts in the machine. This paper discusses fuzzy navigation method for leading the inspection and diagnosis robot to the faulty machine by using the sound signal. Furthermore, in order to verify the effectivity of the method discussed in this study, the experiment result of fuzzy navigation for searching sound source is also shown in this report.

Many infrastructures like bridges and tunnels had been constructed during the steep economic growth age. In Japan, degradation of those infrastructures becomes a problem. The main inspection method needs scaffolding under the bridge throughout, but it costs. Recently, Robots for the inspection has begun to attract notice. Inspection robots can cut cost and be safe. Inspectors must know the position where the robot captured the photo of damage. Therefore, localization system for robots is very important. Because, for example, a bridge inspection robot must be very compact, so localization system for the robots needs to be small and lightweight. In this study, we have created a localization system for the compact robots by using speakers and a microphone. This system consists of an analog circuit, an F PGA, a seven-segment display and a battery. However, It is necessary to mount only a microphone and the analog circuit on a small robot. The analog circuit with a microphone is very small and lightweight. First, we have performed experiments with only this system. As a result, it has been confirmed that this system can estimated the position. Then, we have mounted the microphone, the analog circuit and discrimination circuit on the small robot object and this system has estimate the position of the robot. According to the experimental results, the practical utility of this system has been confirmed

This paper discusses a method of improvement of vibration measurement by an aerial robot that can land on a steel structure using electro-permanent magnets for use in vibration-based structural health monitoring. In the experiment of the previous study using a steel beam structure, the vibration measurement by a prototype aerial robot was severely affected by the vibration characteristics of the airframe above 50 Hz. Hence, in this study, a FIR inverse filter determined by least-square method is introduced to eliminate the influence of the vibration characteristics of the airframe. The optimal filter order and the delay value are determined by evaluating the Akaike’s information criterion and the error function. The experimental results shows that the proposed inverse filter can reduce the measurement error approximately 1/10 and the band that can be measured expands to 5 to 150 Hz.

Since bearings are used for rotating parts in dynamic machinery, the integrity diagnosis becomes very important in order to maintain the operating state in the machinery. Although there are various methods for the diagnosis of bearings, an acoustic emission (AE) measurement that detects elastic stress waves when a material is deformed and fractured can be applied on assessing damage in rolling bearings. By paying attention to the frequency changes in the AE signal waveforms according to the changes in friction and wear mode, predicting possible failure in rolling bearings is possible. In this study, endurance tests of rolling bearings were examined focusing on the changes in the frequency spectrum of the AB signals, as well as the effects of foreign body particles (metallic particles and hard particles) in bearings.