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With a sound sensing system using stochastic resonance (4SR), it became possible to obtain an acoustic pulse wave (APW)—a waveform created via a mixture of apex beat and heart sound. We examined 50 subjects who were healthy, with no underlying cardiovascular diseases. We could determine boundary frequency (BF) using APW and phonocardiogram signals. APW data was divided into two bands, one from 0.5 Hz to BF, and a second one from BF to 50 Hz. This permitted the extraction of cardiac apex beat (CAB) and cardiac acoustic sound (CAS), respectively. BF could be expressed by a quadratic function of heart rate, and made it possible to collect CAB and CAS in real time. According to heart rate variability analysis, the fluctuation was 1/f, which indicated an efficient cardiac movement when heart rate was 70 to 80/min. In the frequency band between 0.5 Hz and BF, CAB readings collected from the precordial region resembled apex cardiogram data. The waveforms were classified into five types. Therefore, the new 4SR sensing system can be used as a physical diagnostic tool to obtain biological pulse wave data non-invasively and repeatedly over a long period, and it shows promise for broader applications, including AI analysis.

In stand-alone operations, on-site generators must balance and meet demand at any time for second-by-second fluctuations in output and load demand. However, the previous optimization tool for private generator configuration in hospital buildings did not consider demand sufficiency. Herein, this qualitative electricity problem was solved by proposing a new optimization method that considers the balance of power supply and demand in the stand-alone operation of on-site generators during power outages. As a demand sufficiency condition, a power balance simulator obtained available configurations of private generators that can be operated within the standard alternating current (AC) frequency range of 49–51 Hz. We also compared case study results by applying these constraints to the findings of earlier studies. The same case study from an earlier paper reported that the optimal amount of photovoltaic systems installed is approximately the upper limit (set at 600 m2 in this calculation) and the optimal solution. In contrast, the optimization results with additional constraints to keep frequency fluctuations within specified limits yielded an optimal value significantly less than the previous optimization; one case study showed that the optimal installation amount of photovoltaics was 0 m2. However, the key equipment in this study was the emergency diesel generator. The emergency generator compensates for power shortages and balances supply and demand under power outages. The results suggest that case studies with demand-satisfying conditions tend to select equipment configurations that effectively improve the expected power shortage rate.

In hospitals, the energy supply is the key to ensuring modern medical care even during power outages due to a disaster. This study qualitatively examined whether the supply–demand balance can be stabilized by the private generator prepared by the hospital building during stand-alone operations under disaster conditions. In the nanogrid of the hospital building, the power quality was examined based on the AC frequency, which characterizes the supply–demand balance. Gas engine generators, emergency diesel generators, photovoltaic panels, and storage batteries were presumed to be the private generators in the hospital building. The output reference values for the emergency diesel and gas engine generators were set using droop control, and the C/D controller-enabled synchronized operation. In addition, to keep the AC frequency fluctuation minor, the photovoltaic panels were designed to suppress the output fluctuation using storage batteries. As a result of case studies, the simulator predicts that the frequency fluctuation varies greatly depending on the weather conditions and the fluctuation suppression parameters, even for the same configuration with the same power generation capacity. Therefore, it is preferable to increase the moving average time of the output and reduce the feedback gain of the storage battery to suppress the output fluctuation from the photovoltaics. However, there is a trade-off between suppressing the output fluctuation and the minimum required storage capacity. Furthermore, since the photovoltaics’ output varies with the weather, other private generators’ capacity and control parameters significantly impact power quality. The simulator proposed in this study makes it possible to study each hospital's desirable private generator configuration.

From previous combustion oscillation experiments using a simulated gas turbine combustor, oscillation frequencies around 350 Hz were measured in only natural gas-fired, and around 200 and 400 Hz were measured in the case of hydrogen-containing fuel. In this study, the axial gas column vibration mode was assumed, and the method to reproduce the change of oscillating frequency due to the difference of fuel was investigated. In the previous study, the temperature distribution in the combustor was divided into only two regions, and there were problems in terms of parameter estimation for modeling the flame dynamics. Therefore, the transfer matric method that incorporates a linear temperature gradient was employed. Also, the temperature distributions obtained from computational fluid dynamics, and experiments were reduced to one dimension to reproduce the difference in combustion characteristics due to the difference in fuel composition; four methods were proposed, the axial representative temperatures. The Nyquist plot method was used to calculate up to 10 combinations of resonant frequency and growth rate simultaneously. Furthermore, the oscillation frequency was determined in which the resonance frequency with the growth rate was maximum. As a result, the value of the oscillating frequency obtained differed depending on creating the representative temperature distribution.

A combustion oscillation experiment showed combustion oscillation frequencies of around 350 Hz when only natural gas was used as fuel and approximately 200 and 400 Hz when a hydrogen–natural gas mixture was used. To analyze the resonant frequency, two- and four-region models considering unburned and burned regions of the combustor were developed. The experimental frequencies of the 100% natural gas condition were successfully predicted. Conversely, the experimentally observed frequencies under the hydrogen–natural gas condition were not accurately predicted. A swirler-combustor model was then constructed to get closer to the actual configuration and shape of the experimental setup. However, the model could not reproduce the experimental value under the hydrogen–natural gas condition. A whole piping model was then developed by adding a casing and an air supply pipe to the combustor. The resonant frequencies under both the 100% natural gas and hydrogen–natural gas conditions were successfully calculated. The model reproduced the range and change tendency of the experimentally measured oscillation frequency.

text, 学術雑誌論文 / Journal Article, In this study, we propose a design method of a model-based nonlinear feedforward controller for a diesel engine air-path system. First, a physical air-path model of the diesel engine was developed. Then, a feedforward controller was developed based on the inverse characteristics of the developed physical model. To improve the transient responses of the boost pressure and EGR ratio, the response delay of the turbocharger and manifolds dynamics were considered while designing the feedforward controller. The effectiveness of the proposed method was evaluated by conducting experiments using a real diesel engine. The experimental results indicated a good tracking performance for both the boost pressure and EGR ratio.

It is essential to secure energy sources by installing a private power generator for business continuity in a power outage. The authors have developed an optimization tool to estimate the optimal amount of distributed power supply equipment using economic efficiency and resilience as two evaluation indicators. However, it is questionable whether the private generator in a hospital building can generate sufficient electricity to meet demands in case of a power failure, because demand has short cycle fluctuations on the order of seconds, and the private generator must respond to these fluctuations from time to time in the case of stand-alone operation. The optimization tools we have developed in the past have not considered the balance between power output and load demand (demand sufficiency). Therefore, this paper proposes a new optimization method that considers balancing power supply and demand in private generators’ independent operation during power outages. We narrowed the optimization constraints as demand sufficiency conditions: standard AC frequency range between 49 and 51 Hz. More practical optimal solutions are obtained by applying the new constraints to the multi-optimization. We also compare the case study results by applying these constraints to the results of previous case studies.

A combustion oscillation experiment fueling a mixture of hydrogen and natural gas was performed. The results showed oscillating frequencies of around 350 Hz in the case of the town gas only, whereas oscillating frequencies of around 200 and 400 Hz were observed in the hydrogen-containing fuel case. We hypothesized that the oscillating frequencies shift may occur by changing the temperature-distribution inside the tube, which was caused by different combustion conditions with the fuel mixture. As a result, the possible oscillating frequencies of not only around 350 Hz but also around 200 and 400 Hz were obtained. Although three types of possible oscillating frequencies were obtained in our previous study, more detailed temperature distributions should be considered to clarify the effect of the changing fuel mixture composition. In this paper, representative one-dimensional temperature distributions were formed by the combination of measured and calculated temperature distributions in the combustion tube for the corresponding fuel mixture. To include the detailed temperature distributions, the acoustic network model was divided into enough small elements to express the temperature distributions, where each element was connected by the transfer matrix. Then, the possible oscillating frequencies were calculated, taking account of the influence of the temperature distributions.

It is fair to conclude that people with a disorder in the brain and/or cardiovascular system are more likely to experience physical condition changes while driving, which may cause health-induced traffic accidents as a result. In response, we developed a sound sensing system that uses stochastic resonance to continuously capture the trunk acoustic pulse wave (or APW) transmitted through the body. We extracted a pressure waveform derived from the apical beat and the ejection wave to the chest and a pressure waveform generated by the abdominal aorta from the APW. We compared the information obtained from electrocardiogram and blood pressure readings and duly examined the possibility of predicting fluctuations in physical condition via the APW. The pressure waveform extracted from the APW was similar to the data created by heart rate and blood pressure fluctuations and showed a tendency to be disturbed when an arrhythmia occurred. Therefore, the APW could show changes in cardiovascular dynamics and fluctuations in systolic blood pressure and highlight an arrhythmia.

We developed a seat suspension for use on earth-moving machines. The suspension’s mechanism consists of a torsion bar that produces non-linear spring characteristics, a magneto-spring, and a free play damper, which acts as a damping element despite having no actual damping force. We installed a structure that absorbs front-rear vibration of the suspension mechanism with a 40 mm stroke. The vibration control performance in the low- and high-frequency bands was improved by the dead zone of the two-layer suspension mechanism, as well as the free play damper. The phase control using seat suspension and magneto-suspension was able to satisfy ISO 7096:2000 EM7 guidelines.

This paper was removed as a dual publication on August 5, 2022. Copyright © 2022 by ASME

In this study, a multiple-input multiple-output feedforward controller for use with multiple-point fuel injection systems is applied to a diesel engine using an original control-oriented model. The target-tracking performance of this multiple-input multiple-output feedforward controller was then tested in terms of how well the controller adjusts the fuel delivery ratios to the pilot injection, pre-injection, main fuel injection, and the main fuel injection timing, and controls the in-cylinder peak pressure and its timing. Control experiments are conducted at different engine outputs and speeds while changing the targets of the in-cylinder peak pressure and its timing. The controller is able to track the varying targets within an acceptable error included in the original model. The calculation time, which is almost double that of a single-input single-output controller, is sufficiently fast to derive the applicable inputs.

In 2017, the Mistry of Health, Labor, and Welfare in Japan added a requirement for domestic disaster base hospitals to install electric power generation equipment with a generation capacity at least 60% of usual demand for securing business continuity. In this study, we developed a multi-objective optimization tool for assisting the determination of the capacity of distributed generation equipment and contract plans considering energy-resiliency after a disaster. The selected objective functions are a total cost representing economy and environment, and an expected value of power shortage ratio after the catastrophe representing energy-resiliency. As a result, our developed tool could obtain the Pareto-optimal solutions for various size hospitals on the parameter plane of the two objective functions. As well as total costs, for all optimal solutions, the expected value of power shortage ratio under disaster situation resulted in less than 40% suggesting that the national requirement standard is satisfied. Then, the cluster analysis was carried out to grasp the tendency of optimal solutions. From the analysis of average value for each cluster, it is shown that the optimal introductory capacities of gas engine generators and storage batteries couple through the outage probabilities of gas supply. Furthermore, the optimal capacity of photovoltaic is much larger than the one assumed to install on the estimated rooftop area of the hospital building, which suggests that hospital can take an option to introduce more photovoltaics to an adjacent area if possible.

This paper deals with a combustion control system design problem for diesel engines. The consider combustion in this paper is a premixed diesel combustion which produce a dual peak heat release rate. This combustion has high thermal efficiency and low NOx and PM emissions. However, in order to implement this combustion, it is required to design a robust combustion control system because this combustion is low robust with respect to changes of the engine state. Therefore, in this paper, we design an adaptive output feedback control system by considering the in-cylinder heat release rate as the output to be controlled. The effectiveness of the proposed method is confirmed through numerical simulations and experiments on a practical diesel engine.

text, 学術雑誌論文 / Journal Article, In this research, we developed a two-degree-of-freedom control system for a Diesel engine air path system. First, a physical air path model of the Diesel engine was developed. Then, a feedforward controller was designed based on the inverse of the developed physical model, thus reducing the computational effort in real-time calculation. The feedback controller was designed by using an H∞ control theory by regarding the plant nonlinearities and the response delay of the actuators as uncertainties to the nominal model. The feedforward and feedback controllers were implemented as a two-degree-of-freedom control scheme. Further, an anti-windup scheme was introduced in the feedback controller to reduce the overshoot in the intake manifold pressure response. The effectiveness of the proposed method was evaluated by conducting not only simulations using the nonlinear physical model, but also experiments using a real Diesel engine.

Subsidy and social systems should be designed to effectively promote, for example, the introduction of a mechanical system. For an effective subsidy distribution, developing evidence-based decision-making methodologies is essential. We developed a tool that minimizes an objective function includes economic costs, environmental cost, and disaster risk to determine the amount of energy distributed by the equipment when installing in hospitals against disasters. Open data available on the Internet are used as simulation values herein. This simulation model optimizes six design values using a genetic algorithm based on the values (business site area, demand for heat and electricity, and maximum allowable loss) input by customers for their construction and visualizes the total cost. The tool allows to quantitatively assess the changes in the initial and running costs owing to equipment installation and the avoidable losses related to $$\hbox {CO}_{2}$$ emission reductions and disaster risks. In addition, the net present value (NPV) can be calculated using the obtained values for initial and running costs, thereby allowing to clearly estimate the return on investments after equipment installation. The opportunity profit can be calculated based on the difference between the NPV after 15 years assuming no risk and with disaster risks. A method to set this opportunity profit as a calculated subsidy amount is proposed herein. Decision support can be provided via these simulations to the customers and government subsidy system design engineers.

text, 学術雑誌論文 / Journal Article, Premixed charge compression ignition (PCCI) combustion has a potential to achieve the low emission level while the thermal efficiency remains high. It requires more precise combustion control due to the low robustness of the premixed combustion. In this study, a model-based control system for both air path system and combustion is developed for realizing the ideal PCCI combustion in future. For the air path system control, a feedback (FB) controller based on H∞ control theory is used. In this controller, the nonlinearity of the plant is considered as the perturbation and robustness is ensured by H∞ control. For the combustion control, a feedforward (FF) controller is designed as an inverse model of a discretized combustion model. In this controller, the inverse model is updated cycle by cycle on-board to consider the variation of combustion characteristics depending on operation condition. The performance of the overall control system including both controllers is evaluated by the reference following test under the transient mode operation in both the simulation and the experiment for PCCI-like combustion with advanced fuel injection timing. The control system showed good tracking performance both in air path and combustion systems and the availability of the model-based control system is shown.

In order to realize stable and fuel-efficient operation with homogeneous charge compression ignition (HCCI) combustion, it is necessary to precisely control in-cylinder conditions such as gas temperature and oxygen concentration according to the target load set for each cycle. The HCCI combustion discussed in this study utilizes internal exhaust gas recirculation (EGR). For this type of combustion, the exhaust gas temperature and composition in the last cycle should be accurately estimated, and the internal EGR rate and the fuel injection quantity should be appropriately commanded to generate in-cylinder conditions that ensure combustion in the next cycle. To implement this effectively, the authors constructed a control-oriented model for the HCCI combustion which utilizes internal EGR with the negative valve overlap method, and developed a model-based feedforward controller based on this model. Firstly, the model-based feedforward controller was validated by simulations in which a change in the target load was given to the controller. Secondly, engine experiments were conducted to validate the controller in the same way. The results confirmed that the model-based feedforward controller was able to generate in-cylinder conditions suitable for the target load given to each cycle and thus realize stable HCCI combustion while following the target load.

We developed a feed-forward controller for a conventional diesel combustion engine with triple fuel injection and experimentally evaluated its performance. A combustion model that discretizes an engine cycle into a number of representative points to achieve a light calculation load is embedded into the controller; this model predicts the in-cylinder gas-pressure-peak timing with information about the operating condition obtained from the engine control unit. The controller calculates the optimal main-fuel-injection timing to control the in-cylinder gas-pressure peak using the prediction result as a controller with a single input and output. The controller’s performance was evaluated by experiments using a four-cylinder diesel engine under changing the target value of the in-cylinder gas-pressure-peak timing during a target-following test and the performance was also evaluated under changing the exhaust gas recirculation ratio at the constant target value of the in-cylinder gas-pressure-peak timing for the disturbance-response test. It was found that the controller could calculate the optimal main-injection timing over a cycle and maintain the targeted in-cylinder gas-pressure-peak timing even when the target value or exhaust gas recirculation changed. The combustion model was also shown to be fast enough at predicting diesel combustion for onboard control.

Engine systems must continuously increase their thermal efficiencies and lower their emissions in real operation. To meet these demands, engine systems are increasingly improving their transient performance through control technology. Conventional engine control systems depend on control maps obtained from huge numbers of experiments, which is necessarily limited by the available number of man-hours. These time-consuming control maps are now being replaced by control inputs derived from on-board models. By calculating optimized control inputs in real time using various information, model-based control increases the robustness of advanced combustion technologies such as premixed charge compression ignition and homogeneous charge compression ignition, which use auto-ignition and combustion of air–fuel mixtures. Models also incur relatively low computational loads because the specifications of the engine control unit are lower than those of current smartphones. This article develops a simple diesel combustion model with model-based control of the multiple fuel injections. The model employs the discretized cycle concept based on fundamental thermodynamic equations and comprises simple fuel injection and chemical reaction models. Our control concept aims mainly to decrease the fuel consumption by increasing the thermal efficiency and reduce the combustion noise in real-world operation. The model predicts the peak in-cylinder gas pressure and its timing that minimize the combustion noise and maximize the thermal efficiency, respectively. In an experimental validation of the model, the computed and measured in-cylinder pressures were well matched at each phase under various parameter settings. In addition, the calculation time of the model is sufficiently short for on-board applications. In future, the proposed model will be extended to the design and installation of controllers for engine systems. The control concept and associated problems of this task are also described in this article.

This paper proposes a scheme, called the disaster-risk-weighted damage inequality, for a customer to perform introductory planning for a distributed generation system considering business continuity planning in a disaster case. To calculate this inequality, the relevant disaster risks are surveyed and system operating simulations for target buildings such as a hotel, a hospital, a large-scale office, and a collective housing building are performed by solving a mixed integer linear programming problem under the assumption that a cogeneration system is installed as a distributed generation system. Next, we determined the probabilities of a disaster occurrence and business interruption due to a disaster, the initial cost of the equipment, the running cost, and the reduction in running cost due to a cogeneration system installation. The cogeneration system was found to effectively reduce the running cost. Finally, the suggested inequality is calculated and determined whether it is satisfied. The result showed that cogeneration system installation very effectively reduces the running cost for a hotel, a hospital, and a large-scale office, compared to the tolerable amount of loss that is preliminarily determined by a customer.

This paper proposes a novel unconstrained monitoring system that measures heart and respiratory rates and evaluates autonomic nervous activity based on heart rate variability. The proposed system measures the aortic pulse waves (APWs) of a patient via an APW sensor that comprises a single microphone integrated into a mattress. Vital signs (i.e., heart rate, respiratory rate) and autonomic nervous activity were analyzed using the measured APWs. In an experiment with supine and seated participants, vital signs calculated by the proposed system were compared with vital signs measured with commercial devices, and we obtained the correlations of r > 0.8 for the heart rates, r > 0.7 for the respiratory rates, and r > 0.8 for the heart rate variability indices. These results indicate that the proposed system can produce accurate vital sign measurements. In addition, we performed the experiment of image stimulus presentation and explored the relationships between the self-reported psychological states evoked by the stimulus and the measured vital signs. The results indicated that vital signs reflect psychological states. In conclusion, the proposed system demonstrated its ability to monitor health conditions by actions as simple as sitting or lying on the APW sensor.

Diesel engines exhibit highly efficient, environmentally sound performance under good operational control; however, because of the demand of controlling multiple actuators under various environmental conditions, the conventional experimental method for controlling diesel engines has become increasingly difficult. Therefore, diesel combustion models with less calculation loads were ultimately developed with the aim of implementing such model-based controllers for engine control unit in the future. To achieve the on-board application of the diesel combustion model, the in-cylinder state of a single cycle was discretized into several representative phases such as a valve-opening and valve-closing phase, ignition phase, and maximum pressure phase. Temperature and oxygen quantities in residual gas were considered as the state variables of the system because they have a critical effect on combustion and induce cyclic coupling. The model could take account of the effect of actuators in diesel engines, and the states in each phase were calculated by fundamental thermodynamic equations and some empirical equations. The model was validated against experimental results and had a good agreement with in-cylinder pressures and temperatures at each phase. In addition, the calculation times of the model were confirmed to be capable of on-board application. Furthermore, as a demonstrative example and to show the added value of the model, it was used to synthesize controllers to enable multi-input/multi-output control of a diesel engine in simulation.

This paper proposes a system to extract biological signals from aortic pulse waves which are measured by a microphone type pulse wave sensor. Theproposed system enables extraction of three biological signals corresponding to respiratory rate, pulse pressure wave, and RR interval simply by sitting on the seat on which the sensor is laid. Experiment results demonstrated that the mean absolute errors between the signals measured by the proposed system and the conventional sensors are as low as 0.38 times per minute for the respiratory rate, 11.2 mmHg for the pulse pressure wave, and 16.6 ms for the RR interval. The proposed system thus may be applied to monitor the physiological state of a human subject to prevent accident caused by health condition.

In this paper, we propose a novel method for predicting acute clinical deterioration triggered by hypotension, ventricular fibrillation, and an undiagnosed multiple disease condition using biological signals, such as heart rate, RR interval, and blood pressure. Efforts trying to predict such acute clinical deterioration events have received much attention from researchers lately, but most of them are targeted to a single symptom. The distinctive feature of the proposed method is that the occurrence of the event is manifested as a probability by applying a recurrent probabilistic neural network, which is embedded with a hidden Markov model and a Gaussian mixture model. Additionally, its machine learning scheme allows it to learn from the sample data and apply it to a wide range of symptoms. The performance of the proposed method was tested using a dataset provided by Physionet and the University of Tokyo Hospital. The results show that the proposed method has a prediction accuracy of 92.5% for patients with acute hypotension and can predict the occurrence of ventricular fibrillation 5 min before it occurs with an accuracy of 82.5%. In addition, a multiple disease condition can be predicted 7 min before they occur, with an accuracy of over 90%.

In this study, combustion oscillation characteristics of hydrogen-rich fuel were investigated. The experimental results fueled by mixture of natural gas and hydrogen show that hydrogen-rich combustion influences on the oscillating frequencies. In the case of only natural gas, the single oscillating frequency around 350 Hz is obtained, and in the hydrogen-containing fuel case, the double oscillating frequencies around 200 and 400 Hz are measured. However, the latter oscillating frequencies could not be derived from the one-dimensional acoustic analysis. Therefore, to figure out these frequencies, the acoustic impedance was measured experimentally and the oscillating frequencies were re-calculated using the measured acoustic impedance as the acoustic boundary conditions. As a result, the 200, 350, and 400 Hz frequencies could be expressed using the acoustic impedances.

In this study, we construct a cardiovascular model considering the interaction of cardiac and vascular systems, and investigate factors affecting hypertension. In the cardiovascular model, stroke volume, the blood volume pumped by a heart per beat, is determined based on the operating conditions of the system. In addition, positions of baroreceptors, pressure sensors of cardiac system, in blood vessels are also considered. Consequently, the functions proportionally controlling the baroreceptor activities and determining the activities of autonomic nerves have significant effects on hypertension, which are comparable to those of aortic stiffness.

This study aims to tailor the bearing stiffness for enhancing the load-carrying capacity of foil thrust bearings. New architectures for the bump foil are introduced with structural stiffness tailored in the radial and circumferential directions to ensure a converging gas film under high axial loads while maintaining a reasonable bearing compliance to accommodate thermal as well as mechanical distortions. The structural stiffness of the bearing is calculated with an analytical method previously introduced by the authors, and the flow in the gas film is modeled with 2-D compressible Reynolds equation. The Couette Approximation technique is used to calculate the temperature distribution in the gas film and the small perturbations method is used to calculate its dynamic force coefficients. Enhanced load capacity could be obtained with the introduced bump foil designs.