Dynamic Health Monitoring Research Articles

Weighted squared envelope dispersion entropy as nonlinear measure for dynamic health monitoring of rotating machineries

In the context of nondestructive testing and evaluation, dispersion entropy (DisE) stands out as a promising dynamic nonlinear health monitoring measure for rotating machineries. However, in high-noise scenarios, transient impulses linked to rotating machinery faults often get submerged under the noise component present in the collected vibration signal. As a result, DisE not only fails to detect the presence of a fault at the earliest stage of inception but also performs poorly in tracking the progression of the incepted fault. Aiming at overcoming the limitations of DisE in dynamic health monitoring of rotating machineries, in this paper, impulses corresponding to a fault is extracted by suppressing the unnecessary noise component by weighting the squared envelope of the collected vibration signal. Due to the application of weighted squared envelope in calculating the DisE, the proposed measure is termed as weighted squared envelope dispersion entropy (WSEDisE). Effectiveness of WSEDisE in dynamic health monitoring of rotating machineries is verified by two different experimental run to failure data collected from rolling element bearings and spur gears. Experimental results show that WSEDisE not only overcomes the weaknesses of original DisE but also demonstrates better performance than conventional entropy-based methods such as permutation entropy (PE) and advanced DisE based method namely multiscale DisE (MDisE).

Dynamic Health Monitoring of Aero-Engine Gas-Path System Based on SFA-GMM-BID

This paper proposes a dynamic health monitoring method for aero-engines by extracting more hidden information from the raw values of gas-path parameters based on slow feature analysis (SFA) and the Gaussian mixture model (GMM) to improve the capability of detecting gas-path faults of aero-engines. First, an SFA algorithm is used to process the raw values of gas-path parameters, extracting the effective features reflecting the slow variation of the gas-path state. Then, a GMM is established based on the slow features of the target aero-engine in a normal state to measure its health status. Moreover, an indicator based on the Bayesian inference distance (BID) is constructed to quantitatively characterize the performance degradation degree of the target aero-engine. Considering that the fixed threshold does not suit the time-varying characteristics of the gas-path state, a dynamic threshold based on the maximum information coefficient is designed for aero-engine health monitoring. The proposed method is verified using a set of actual operation data of a certain aero-engine. The results show that the proposed method can better reflect the degradation process of the aero-engine and identify aero-engine anomalies earlier than other aero-engine fault detection methods. In addition, the dynamic threshold can reduce the occurrence of false alarms. All these advantages give the proposed method high value in real-world applications.

Internet of medical things for VTE patients in ICU: A self-attention mechanism-based energy-efficient risk identification scheduling algorithm

The explosive growth of medical data has dramatically increased the demand for computing power, resulting in insufficient spectrum resources and communication overload. Hospitals need to invest much money to expand computing resources. Various diseases require varying degrees of multi-sensor and continuous monitoring. Take venous thromboembolism (VTE) patients in the intensive care unit (ICU) as an example, enlargement of the right heart, widening of the pulmonary artery, and abnormal results of myocardial enzyme examination maybe lead to sudden death within a short time in the ICU inpatient ward. Steady and dynamic health monitoring is essential. Patients’ immediate risk perception can significantly improve medical efficiency and reduce adverse consequences. How to provide a more efficient and secure full-time monitoring scheme, dynamically adjust the workload, and allocate computing tasks and requests reasonably is a practical problem to be solved urgently. First, this paper defines a task similarity to measure the similarity between different task packages and determine the priority of tasks to avoid forwarding highly similar task packages and reduce energy consumption. Second, the edge gateway caching mechanism with a self-attention mechanism is constructed, which changes the centralized scheduling mode of traditional cloud computing, devolves the coordination function to the edge, and divides the network into multiple local sub-networks. The central node of the sub-network determines the scheduling scheme. The experimental results show that the system can ensure the quality of service and use the edge’s limited computing resources, effectively shield the inefficient data transmission requirements, reduce the use cost and medical quality, and has a specific theoretical and practical value.

Strain-induced dielectric anisotropy of polymers for rapid and sensitive monitoring of the small elastic strain

Stretching is the most important way of forming polymer films, and the mechanism of stretch-induced structural evolution is a long-standing fundamental issue in the stretching process of polymer films. Current methods are limited in sampling frequency or transparent materials and difficult to in situ measure the molecular chain structure evolution. In this study, we proposed a new principle for measuring the stretching process of polymer materials based on dielectric anisotropy. Firstly, the strain-dielectric anisotropy linear relation during small elastic deformation was found, and an extremely small strain (∼0.1%) can be measured with a high sampling frequency (∼8.3 Hz). Then, the molecular chain orientation-induced dielectric anisotropy for the underlying mechanism was confirmed by molecular dynamics simulations and in situ polarized Raman spectroscopy experiments. The proposed method was successfully applied in measuring tube compliance and dynamic health monitoring by measuring small elastic strain accurately, exhibiting the potential for wide applications.

An integrated framework via key-spectrum entropy and statistical properties for bearing dynamic health monitoring and performance degradation assessment

Dynamic health monitoring (DHM) and performance degradation assessment (PDA) is critical for mechanical bearings throughout their long in-service life. For this issue, it is currently rare to find a framework with interpretable and automatic approaches developed from pure signal processing techniques and statistical theories. Therefore, an integrated framework via key-spectrum entropy and statistical properties for bearing DHM and PDA is developed in this paper, which integrates the proposed key spectrum, key-spectrum entropy, joint statistical alarm and fault identification strategy, health phase segmentation strategy, and three-dimensional (3D) key spectrums. First, a Kurtosis-Energy metric is defined to extract the key spectrum, which is reconstructed by two wavelet-decomposed sub-bands where the interference components are suppressed. A new health index (HI) of key-spectrum entropy is then defined to quantify the bearing degradation process. Second, a joint statistical alarm and fault identification strategy via updated HIs and key spectrum is proposed to form a DHM methodology for implementing bearing dynamic fault detection and recognition. Third, a health phase segmentation strategy and 3D key spectrums are developed to form a PDA methodology for implementing bearing health phase assessment and degradation pattern analysis. Comprehensive evaluations and comparisons on eighteen sets of bearing degradation vibration signals demonstrate the validity of the proposed framework, as well as its great practical application prospects.

An RF-PCE Hybrid Surrogate Model for Sensitivity Analysis of Dams

Quantification of structural vibration characteristics is an essential task prior to perform any dynamic health monitoring and system identification. Anatomy of vibration in concrete arch dams (especially tall dams with un-symmetry shape) is very complicated and requires special techniques to solve the eigenvalue problem. The situation becomes even more complicated if the material distribution is assumed to be heterogeneous within the dam body (as opposed to conventional isotropic homogeneous relationship). This paper proposes a hybrid Random Field (RF)–Polynomial Chaos Expansion (PCE) surrogate model for uncertainty quantification and sensitivity assessment of dams. For different vibration modes, the most sensitive spatial locations within dam body are identified using both Sobol’s indices and correlation rank methods. Results of the proposed hybrid model is further validated using the classical random forest regression method. The outcome of this study can improve the results of system identification and dynamic analysis by properly determining the vibration characteristics.

A Wearable Capacitive Sensor Based on Ring/Disk-Shaped Electrode and Porous Dielectric for Noncontact Healthcare Monitoring.

Wearable sensors are gradually enabling decentralized healthcare systems. However, these sensors need to be closely attached to skin, which is unsuitable for long‐term dynamic health monitoring of the patients, such as infants or persons with burn injuries. Here, a wearable capacitive sensor based on the capacitively coupled effect for healthcare monitoring in noncontact mode is reported. It consists of a ring‐shaped top electrode, a disk‐shaped bottom electrode, and a porous dielectric layer with low permittivity. This unique design enhanced the capacitively coupled effect of the sensor, which enables a high noncontact detectivity of capacitance change. When an object approaches the sensor, its capacitance change (ΔC/C i = −38.7%) is 3–5 times higher than that of previously reported sensors. Meanwhile, the sensor is insensitive to the stretching strain and pressure (ΔC/C i < 5%) due to the unique ring‐shaped electrode and the incompressible closed cells of the porous dielectric material, respectively. Finally, various human physiological signals (pulse and respiratory) are recorded in noncontact mode, where a person wears loose and soft clothes implanted with the sensor. Thus, it is promising to build smart healthcare clothes based on it to develop wearable decentralized healthcare systems.

Cardiovascular function dynamics in healthy Kazakhstan residents participating medical and environmental investigations who work under extreme conditions (Emergency Ministry personnel)

The purpose of the investigation was to study group dynamics of seasonal changes in the autonomic nervous and cardiovascular functions in apparently healthy men who occupationally deal with frequent stressful situations (field personnel and firefighters of the Almaty Emergency Management Department (EMD), Emergency Ministry of the Republic of Kazakhstan (EM RK). The investigation was conducted according to the program of parallel medical and environmental investigations within the framework of the Mars-500 project in the city of Almaty, based on the support from the Kazakh National Medical University with respect to terminology based on using the prenosological approach which allows one to assess states in between the norm and pathology. Results of the year-long investigation demonstrated seasonal variations in the functional state of body with identification of groups up to prenosological ones, which could be associated with specific occupational factors and arduous duty, as it follows from the Almaty EMD operational summary (autonomic balance shifting toward prevalence of the sympathetic control during spring and summer arduous duties, and toward the parasympathetic control under quiet duty conditions during wintertime). These observations testify to the importance of dynamic health monitoring concerning apparently healthy people who are occupationally exposed to chronic psycho-emotional strain for prenosological diagnosis and timely preventive intervention.

A Bluetooth-Based Portable Design Device with Wireless Power Module for Electrocardiogram and Respiration Measurement

This paper presents compact design and implementation of a portable device for application of continuous Electrocardiogram(ECG) and respiration measurement in the field of dynamic health monitoring. Bluetooth technique is used for data transmission between portable device and acquisition node such as computer or smart phone, given its advantages of low power consumption and easy wireless connection. The device also includes a wireless power module for charging the lithium polymer battery with the charging current up to 300mA, which makes power supply much more conveniently. Measurement of ECG and respiration is implemented by two electrodes layout solution and ADS1292R which enable the system design at significantly reduced size(60mm*40mm), power, and overall cost. Experiments are carried out with appropriate work parameters as sample rates and resolution. The results show that our device can accurately acquire the ECG and multiple respiration states..

On providing the continuity of dynamic observation of students on the basis a medical institution of the university

Aim. To improve measures aimed at ensuring the continuity of the dynamic health monitoring of students on the basis of medical institutions of the University. Methods. On the basis of the technology «client-server», which is oriented on the management system of the Firebird databases, developed was an information-analytical system of dynamic observation of the health of students. Results. This system presumes a specific algorithm for the medical examination, first of all the screening methods: psychological testing, measurement of anatomical and physiological parameters, obtaining of the medical history, physical examination, cardiorhythmography and routine clinical and laboratory tests. With the help of original methods the medical information system provides a complex report on the state of health of the student and on the risks of the most common diseases in this age group. Conclusion. Health care providers of medical institutions of a University can use the developed system for dynamic monitoring of the health of the students.

Optical fiber sensors for static and dynamic health monitoring of civil engineering infrastructures: Abode wall case study

Nowadays, structural health monitoring is a fundamental tool to control the civil infrastructures lifetime. Raw earth masonry structures (as adobe, rammed earth, among other techniques) were very common in many regions of the World. With the introduction of reinforced concrete structures in the construction industry, the adoption of traditional masonry systems, and adobe in particular, rapidly declined. However, an important number of the adobe buildings in the world are of cultural, historical and architectural recognized value, presently, about 30% of the World population lives in raw earth buildings.In this paper, the monitoring of an adobe masonry structure with an optical fiber accelerometer and a network of thirteen multiplexed displacement sensors is reported. The measurements were made during a destructive test on a full-scale wall. The measured values showed a decrease of 48% in the structure first natural frequency value, between the initial situation and after the cyclic test. Our results demonstrated that optical sensors can be useful in static and dynamic monitoring of large raw earth masonry structures.

End-to-End Mechanical Calibration of Strain Channels in Dynamic Health Monitoring Systems

The U.S. Air Force invented a calibration technique that allows one person to perform multiple, mechanical end-to-end calibrations of structural dynamics measurement systems. In Order to define the vibrations and acoustics environment, often an aircraft or engine structural health monitoring system collects airframe or engine structural integrity data. A recommended practice is to perform an end-to-end mechanical calibration of the system. This means a full calibration of instrumentation from the physical input to the transducer to the output where the analog or digital signal is normally analyzed. It is difficult to stimulate mounted and embedded transducers with a known physical input, especially strain gages bonded to a structure. This new technique uses a remote control structural exciter (RCSE) to stimulate transducers in structures, with a measurable input level, and the output signal is communicated to the data storage device of the structural health monitoring system. The Air Force demonstrated this patented technique by using accelerometers in the laboratory. This paper investigates this new technique to evaluate and calibrate strain gages mounted on structure. A reference piezoelectric strain gage measures the input. A typical system may include dynamic strain gages connected to a battery operated data acquisition system. This paper describes the invention and looks at potential field applications to insure data integrity of strain data in structural health monitoring data acquisition systems on aging commercial and military vehicles. Also, the paper describes a planned design of experiments to evaluate the use of remote control structural exciters for mechanical end-to-end calibration of strain gages in measurement systems.