Energy Harvesting Technologies for Achieving Self-Powered Wireless Sensor Networks in Machine Condition Monitoring: A Review <s> Condition Monitoring Methods Techniques <s> Packaged piezoelectric bi-morph actuators offer an alternative power source for health monitoring using localized vibrational power harvesting. Packaging piezoelectric wafers simplify the integration of piezoelectric ceramic wafers into products and improve the durability of the brittle piezoelectric ceramic material. This paper describes a model for predicting the power harvested from a resonant cantilevered beam piezoelectric power harvester across a resistive load. The model results are correlated with experimental power harvesting measurements made using a commercially available piezoelectric bi-morph actuator. Additionally, experimental power harvesting levels were determined under high root strain conditions and varying command frequencies. Finally, the power production capability of the packaged piezoelectric bi-morph generator was evaluated over millions of cycles at very high root strains levels, representative of the loads expected in an industrial application. Results from the testing indicate that packaged piezoelectric wafer products used in power harvesting devices are very reliable and well suited for harsh industrial application environments. <s> BIB001 </s> Energy Harvesting Technologies for Achieving Self-Powered Wireless Sensor Networks in Machine Condition Monitoring: A Review <s> Condition Monitoring Methods Techniques <s> To enable self-sustaining long-lasting wireless condition monitoring sensors, a small mechanical vibration energy harvester using electromagnetic transduction was constructed and used to harvest vibrations from large industrial pump motors and machine tool. The prototype harvester was roughly the size of a cube with 2.5 cm long sides. Power ranging from 0.2 to 1.5 mW was harvested from 15 to 30 kW water pump motors. For a machine tool, metal cutting vibrations and rapid jog events were explored as possible harvestable sources of energy. Power ranging from 0.9 to 1.9 mW was harvested during facemilling operations, and it was shown that rapid jog events could be harvested. The power levels harvested from the pump motors and machine tools are sufficient to provide the time-averaged power requirements of commercial wireless sensor nodes, enabling sensor nodes to overcome the finite life of replaceable batteries. <s> BIB002 </s> Energy Harvesting Technologies for Achieving Self-Powered Wireless Sensor Networks in Machine Condition Monitoring: A Review <s> Condition Monitoring Methods Techniques <s> Randomly oriented poly(vinylidene fluoride) (PVDF) nanofibre webs prepared by a needleless electrospinning technique were used as an active layer for making mechanical-to-electrical energy harvest devices. With increasing the applied voltage in the electrospinning process, a higher β crystal phase was formed in the resulting PVDF nanofibres, leading to enhanced mechanical-to-electrical energy conversion of the devices. The power generated by the nanofibre devices was able to drive a miniature Peltier cooler, which may be useful for the development of mechanically driven cooling textile. In addition, the needleless electrospinning also showed great potential in the production of nanofibres on a large scale. <s> BIB003 </s> Energy Harvesting Technologies for Achieving Self-Powered Wireless Sensor Networks in Machine Condition Monitoring: A Review <s> Condition Monitoring Methods Techniques <s> Recently, a triboelectric generator (TEG) has been invented to convert mechanical energy into electricity by a conjunction of triboelectrification and electrostatic induction. Compared to the traditional electromagnetic generator (EMG) that produces a high output current but low voltage, the TEG has different output characteristics of low output current but high output voltage. In this paper, we present a comparative study regarding the fundamentals of TEGs and EMGs. The power output performances of the EMG and the TEG have a special complementary relationship, with the EMG being a voltage source and the TEG a current source. Utilizing a power transformed and managed (PTM) system, the current output of a TEG can reach as high as 3 mA, which can be coupled with the output signal of an EMG to enhance the output power. We also demonstrate a design to integrate a TEG and an EMG into a single device for simultaneously harvesting mechanical energy. In addition, the integrated NGs can independently output a high voltage and a high current to meet special needs. <s> BIB004 </s> Energy Harvesting Technologies for Achieving Self-Powered Wireless Sensor Networks in Machine Condition Monitoring: A Review <s> Condition Monitoring Methods Techniques <s> Wireless Sensor Networks (WSNs) is a special category of Wireless Ad-Hoc Networks where low-powered wireless nodes are deployed in specific areas either in a random or predetermined manner, in order to sense an event and transmit the collected data to a central node for processing (sink). Due to the fact that the wireless sensor nodes are low-powered and with limited processing and storage capabilities, they are considered unreliable for use in critical systems. In this paper, through an experimental approach, we show how can WSNs serve applications on critical systems like aircrafts (A/C), without using the existing aircraft wiring for power supply but by harvesting the required energy for charging of their batteries. <s> BIB005 </s> Energy Harvesting Technologies for Achieving Self-Powered Wireless Sensor Networks in Machine Condition Monitoring: A Review <s> Condition Monitoring Methods Techniques <s> An attachable electromagnetic-energy-harvester driven wireless vibration-sensing system for monitoring milling-processes and cutter-wear/breakage-conditions is demonstrated. The system includes an electromagnetic energy harvester, three single-axis Micro Electro-Mechanical Systems (MEMS) accelerometers, a wireless chip module, and corresponding circuits. The harvester consisting of magnets with a coil uses electromagnetic induction to harness mechanical energy produced by the rotating spindle in milling processes and consequently convert the harnessed energy to electrical output. The electrical output is rectified by the rectification circuit to power the accelerometers and wireless chip module. The harvester, circuits, accelerometer, and wireless chip are integrated as an energy-harvester driven wireless vibration-sensing system. Therefore, this completes a self-powered wireless vibration sensing system. For system testing, a numerical-controlled machining tool with various milling processes is used. According to the test results, the system is fully self-powered and able to successfully sense vibration in the milling processes. Furthermore, by analyzing the vibration signals (i.e., through analyzing the electrical outputs of the accelerometers), criteria are successfully established for the system for real-time accurate simulations of the milling-processes and cutter-conditions (such as cutter-wear conditions and cutter-breaking occurrence). Due to these results, our approach can be applied to most milling and other machining machines in factories to realize more smart machining technologies. <s> BIB006 </s> Energy Harvesting Technologies for Achieving Self-Powered Wireless Sensor Networks in Machine Condition Monitoring: A Review <s> Condition Monitoring Methods Techniques <s> As key mechanical components, bearings and gearboxes are employed in most machines. To maintain efficient and safe operations in modern industries, their condition monitoring has received massive attention in recent years. This thesis focuses on the improvement of signal processing approaches to enhance the performance of vibration based monitoring techniques taking into account various data mechanisms and their associated periodic, impulsive, modulating, nonlinear coupling characteristics along with noise contamination. Through in-depth modelling, extensive simulations and experimental verifications upon different and combined faults that often occur in the bearings and gears of representative industrial gearbox systems, the thesis has made following main conclusions in acquiring accurate diagnostic information based on improved signal processing techniques: ::: ::: ::: 1) Among a wide range of advanced approaches investigated, such as adaptive line enhancer (ALE), wavelet transforms, time synchronous averaging (TSA), Kurtogram analysis, and bispectrum representations, the modulation signal bispectrum based sideband estimator (MSB-SE) is regarded as the most powerful tool to enhance the periodic fault signatures as it has the unique property of simultaneous demodulation and noise reduction along with ease of implementation. ::: ::: ::: 2) The proposed MSB-SE based robust detector can achieve optimal band selection and envelope spectrum analysis simultaneously and show more reliable results for bearing fault detection and diagnosis, compared with the popular Kurtogram analysis which highlights too much on localised impulses. ::: ::: ::: 3) The proposed residual sideband analysis yields accurate and consistent diagnostic results of planetary gearboxes across wide operating conditions. This is because that the residual sidebands are much less influenced by inherent gear errors and can be enhanced by MSB analysis. ::: ::: ::: 4) Combined faults in bearings and gears can be detected and separated by MSB analysis. To make the results more reliable, multiple slices of MSB-SE can be averaged to minimise redundant interferences and improve the diagnostic performance. <s> BIB007 </s> Energy Harvesting Technologies for Achieving Self-Powered Wireless Sensor Networks in Machine Condition Monitoring: A Review <s> Condition Monitoring Methods Techniques <s> The automotive engine contains different systems that operate to fulfill the continuous function of the combustion. To insure un-interrupted function and optimal performance, various types of condition monitoring technologies are being used with different new advanced data processing techniques. Based on the results of a comprehensive literature review it was found that there is scarce research dealing with CM technologies and soft computing methods used with automotive engines. Thus, the purpose of this paper is to conduct an up-to-date literature review of the CM technologies used with internal combustion engines and identify the fault detection and diagnostic methods used in this context. Consequently, it was found that literature concentrate on four types of condition monitoring technologies and four operational parameters when it comes to multi-sensor diagnosis of engine systems. The paper also highlights the data processing techniques that is not much utilized in this topic. <s> BIB008 </s> Energy Harvesting Technologies for Achieving Self-Powered Wireless Sensor Networks in Machine Condition Monitoring: A Review <s> Condition Monitoring Methods Techniques <s> Forecasting the output power of solar systems is required for the good operation of the power grid or for the optimal management of the energy fluxes occurring into the solar system. Before forecasting the solar systems output, it is essential to focus the prediction on the solar irradiance. The global solar radiation forecasting can be performed by several methods; the two big categories are the cloud imagery combined with physical models, and the machine learning models. In this context, the objective of this paper is to give an overview of forecasting methods of solar irradiation using machine learning approaches. Although, a lot of papers describes methodologies like neural networks or support vector regression, it will be shown that other methods (regression tree, random forest, gradient boosting and many others) begin to be used in this context of prediction. The performance ranking of such methods is complicated due to the diversity of the data set, time step, forecasting horizon, set up and performance indicators. Overall, the error of prediction is quite equivalent. To improve the prediction performance some authors proposed the use of hybrid models or to use an ensemble forecast approach. <s> BIB009 </s> Energy Harvesting Technologies for Achieving Self-Powered Wireless Sensor Networks in Machine Condition Monitoring: A Review <s> Condition Monitoring Methods Techniques <s> Condition monitoring (CM) of gearbox is a crucial activity due to its importance in power transmission for many industrial applications. Monitoring temperature is an effective mean to collect useful information about the healthy conditions of the gearbox. This study investigates the use of a novel wireless temperature node to monitor and diagnose different faults on a gearbox transmission system under different conditions. The wireless temperature node was fabricated with a novel feature that it is supplied by a thermoelectric generator module mounted on the gearbox house to be monitored so that the measurement system avoids the shortage of using a wired power sources or the requirement for recharging or changing batteries. Moreover, the temperatures from lubricating oils and housing are modelled empirically to implement a model based detection. The results show that this monitoring approach allows a number of common faults: tooth breakage, oil shortage, and shaft misalignment to be separated under different loads, which demonstrates the outstanding performance of the proposed system and thus suitable for online and automated condition monitoring. <s> BIB010 </s> Energy Harvesting Technologies for Achieving Self-Powered Wireless Sensor Networks in Machine Condition Monitoring: A Review <s> Condition Monitoring Methods Techniques <s> Design, modeling, simulation, and vibration testing related to electromagnetic energy harvesters are investigated in this paper. A rail-borne electromagnetic energy harvester with copper-beads spacing is proposed and fabricated, the suitable for harvesting vibration-induced energy of the wheelset/track system. A vehicle-track model considering vehicle traveling load is constructed and numerically solved by fast explicit integration methods. An electromagnetic model is established to predict the induced voltage. The track irregularity power spectrum density is applied as excitation source on the track. Based on the calculation results, both the resonant harvester and the magnetic levitation harvester are designed. The solution utilizes copper beads as radial spacing, which guarantees reliable unidirectional movement of magnets inside a multilayer-multirow coil. Vibration tests are conducted with the proposed track-borne device, and a hydraulic driven system is exploited to generate the realistic wheelset/rail interaction force. The proposed rail-borne energy harvester can be mounted to the track easily and extensively. The magnetic levitation harvester offers an approach for harvesting broadband low-frequency (3–7Hz) wheelset/track interaction with the rail displacement of 0.6 to 1.2 mm. For the resonant harvester, the output power of 119 mW and the output peak-peak voltage of 2.32 V are achieved with the rail displacement of 1.2 mm, the coil height of 48 mm, the load resistance of 45 $\Omega $ , the coil inductance of 105.572 mH, and 3000 numbers of turns. Furthermore, a dc–dc boost converter is proposed, which is capable of converting the alternating voltage of the transducer into 5 V/10-mA dc output at the resonant frequency of 6 Hz, the rail displacement of 2 mm, and the induced voltage of 3.4 V. <s> BIB011 </s> Energy Harvesting Technologies for Achieving Self-Powered Wireless Sensor Networks in Machine Condition Monitoring: A Review <s> Condition Monitoring Methods Techniques <s> Abstract The objective of this study is to develop a prototype for smart monitoring of underground rail transit by local energy generation. This technology contributes to powering rail-side devices in off-grid and remote areas. This paper presents the principles, modeling, and experimental testing of the proposed system that includes two subsystems: (1) an electromagnetic energy generator with DC-DC boost converter (2) a rail-borne wireless sensor node with embedded accelerometers and temperature/humidity sensors and (3) a data processing algorithm based on the Littlewood–Paley (L-P) wavelet. Field testing results, power consumption, L-P wavelet transform methods, and feasibility analysis are reported. One application scenario is described: the electromagnetic energy harvester together with the DC-DC boost converter is used as a local energy source for powering the sensor nodes of a Wireless Sensor Network (WSN), and the abnormal signals of out-of-round wheels are identified based on the measured rail acceleration signals and L-P wavelet analysis. <s> BIB012 </s> Energy Harvesting Technologies for Achieving Self-Powered Wireless Sensor Networks in Machine Condition Monitoring: A Review <s> Condition Monitoring Methods Techniques <s> With the widespread use of electric machines, there is a growing need to extract information from the machines to improve their control systems and maintenance management. The present work shows the development of an embedded system to perform the monitoring of the rotor physical variables of a squirrel cage induction motor. The system is comprised of: a circuit to acquire desirable rotor variable(s) and value(s) that send it to the computer; a rectifier and power storage circuit that converts an alternating current in a continuous current but also stores energy for a certain amount of time to wait for the motor’s shutdown; and a magnetic generator that harvests energy from the rotating field to power the circuits mentioned above. The embedded system is set on the rotor of a 5 HP squirrel cage induction motor, making it difficult to power the system because it is rotating. This problem can be solved with the construction of a magnetic generator device to avoid the need of using batteries or collector rings and will send data to the computer using a wireless NRF24L01 module. For the proposed system, initial validation tests were made using a temperature sensor (DS18b20), as this variable is known as the most important when identifying the need for maintenance and control systems. Few tests have shown promising results that, with further improvements, can prove the feasibility of using sensors in the rotor. <s> BIB013 </s> Energy Harvesting Technologies for Achieving Self-Powered Wireless Sensor Networks in Machine Condition Monitoring: A Review <s> Condition Monitoring Methods Techniques <s> Abstract This paper reports a unique vibration-based electromagnetic energy harvester (VEH) designed to power wireless sensors used for fault monitoring of industrial centrifugal pumps. The design consists of two independent moving parts; the central part and the outer part. The uniqueness of the VEH design exists in its ability to produce higher relative velocity between its two moving parts by isolating vibration from the outer part. The developed prototype produced an open-loop voltage of 3.48 V and a closed-loop voltage of 1.63 V for an optimum load of 700 Ω. This constituted for an average power of 3.8 mW delivered to the load at a natural frequency of 200 Hz and an excitation level of 1 g. The experimentation results were in good agreement with the simulation results as the average percentage error was within an acceptable range of 6.15%. A case study is also presented whereby a ZigBee transceiver is successfully powered from the output generated by the VEH. <s> BIB014 </s> Energy Harvesting Technologies for Achieving Self-Powered Wireless Sensor Networks in Machine Condition Monitoring: A Review <s> Condition Monitoring Methods Techniques <s> Abstract A compact thermoelectric energy harvester is developed to harvest the thermal energy from the hot surface of the gas turbine, providing continuous and reliable power for the sensing and monitoring system in the gas turbine. An experimental prototype is built and the performances of the energy harvester with different electrical load resistances and source temperatures are characterized. A mathematical iterative method, taking account of Thompson Effect, line spacing gap heat leakage, material property variations, and thermal resistance of the ceramic covering layer, is used to analyze the performance of the segmented thermoelectric generator (TEG) module with good accuracy. Based on this model, the temperature profiles and heat fluxes along the thermo-elements, efficiency, and heat leakage through the filling gap material are analyzed. The prototype, with a source temperature of 325 °C, has a voltage output of 2.4 V and power output of 0.92 W, which is more than enough to power a sensor node in the gas turbine. A higher power output can be expected with some improvement on the prototype design. <s> BIB015 </s> Energy Harvesting Technologies for Achieving Self-Powered Wireless Sensor Networks in Machine Condition Monitoring: A Review <s> Condition Monitoring Methods Techniques <s> Abstract Vibrational energy harvesting systems with linear electromechanical generators have been largely studied, due to their simple structures and convenience in application. However, the ambient vibration characteristics such as random, time-varying or low-frequency properties make the linear electromagnetic devices cannot be excited at their resonances, which will greatly affect the energy harvesting efficiency. Some attempts to improve the efficiency of a vibration energy harvesting system involve both expand the operating bandwidth and enlarging the magnitude of power output. To this end, a scissor-like energy harvesting system with equivalent nonlinear damping and linear stiffness has been developed in this study. It has been shown that, due to the beneficial nonlinear damping effects provided by the scissor-like structure, the proposed system can greatly improve the vibration energy harvesting performance in terms of the magnitude of power output and energy harvesting bandwidth. On the other hand, the structure parameters of the proposed system can be modified to achieve more significant energy harvesting performance. Moreover, to achieve tunable resonant frequency of the energy harvesting system, the scissor-like structure has been updated by attaching a new lever-type system. In this way, the energy harvesting performance can be improved by tuning the proposed system according to the properties of the surrounding vibration sources. In this paper, both harmonic and random excitations have been adopted to verify the performance of the proposed energy harvesting system. <s> BIB016
Feature extraction BIB007 Time domain-mean value, variance, root mean square (RMS), kurtosis, skewness, entropy, time synchronous average (TSA) etc.; Modelling BIB008 Numerical modelling; Data modelling. Machine learning BIB009 Neural network, deep learning, expert system, fuzzy logic, support vector machine (SVM), etc. CBM has advantages of enhancing machinery reliability, minimizing the maintenance time, saving the labour costs, improving the operating safety and guaranteeing the work continuity through reducing unscheduled downtime caused by catastrophic failures. But, the cost of purchase and installation for monitoring hardware (like acoustic emission transducers, piezoelectric sensors and data acquisition devices) and software is expensive. To solve this problem, WSNs have been focused and considered to utilize in the machine condition monitoring area because the sensors and wireless sensor nodes are economical, easy to operate, programmable, integrated, portable and with small sizes and low consumption. Additionally, the application of WSNs can avoid the cumbersome cable distribution and harsh environment restrictions and play an essential role in the realization of remote real-time condition monitoring of mechanical systems. However, WSNs have a fatal drawback compared with the conventional wired condition monitoring systems that the prevalent application of WSNs in machine condition monitoring is limited by the finite lifespan and capacity of traditional batteries. It is inconvenient to recharge or replace the exhausted batteries in a remote or inaccessible position, and it leads to the machine condition monitoring interruptions and wastes the labour and resources. Therefore, the wasted energy from machines or surrounding environments is attractive for researchers to harvest for powering the sensor nodes with EH technologies introduced previously. This approach substantially prolongs the life of sensing nodes and reduces maintenance costs of the monitoring system and the environmental contamination. The potential recyclable energy sources in or around mechanical systems and corresponding EH technologies have been discussed in detail in Sections 2 and 3, respectively. Several examples for various EH technologies are successfully applied in the WSN-based machine condition monitoring and these representative cases are demonstrated as follows to illustrate their prospects in self-powered WSNs in remote online machine condition monitoring. As the external energy sources of mechanical systems, light energy and RF energy are seldom harvested in the period of machine condition monitoring. The photovoltaic EH technology is primarily applied for large-scale power generation and infrequently used for machine condition monitoring at present. Only few references can be reviewed here. Wang et al.  designed a multi-source (vibration, heat and light) energy harvester with piezoelectric, thermoelectric and photovoltaic EH technologies to power the WSN based acoustic emission sensing systems to successfully monitor the condition of the fear of a gas compressor. The manufactured prototype can generate 1.56 mW and 3.37 mW from 0.048 g vibration energy and thermoelectric energy of 62°C, respectively. Some researchers have investigated a WSN to detect the acceleration of the helicopter with the sensor nodes fed by the electricity harvested from the environment by a commercial RF energy harvester BIB005 . The distance between the tower antenna and the helicopters is about 76 m and the output DC power is about 70 µW. As a result, the solar energy is suitable to be harvested to power large-scale outdoor machines efficiently and effectively. The indoor light EH and RF EH can be considered as the supplement of other EH technologies. The internal energy sources are available and widely utilized for machine condition monitoring. For example, researchers at the University of Huddersfield designed a thermoelectric generator device, shown in Figure 16 and installed on the surface of the gearbox housing in Figure 4b , to harvest energy from the temperature gradient between the housing of the gearbox and the ambient temperature for powering a WSN system BIB010 . The temperatures of the ambient, gearbox surface and oil were simultaneously captured for the gearbox condition monitoring and fault diagnosis. Wu et al. BIB015 has established a mathematical model for evaluating the performance of the segmented thermoelectric generator by considering multiple parameters and then analyzed its efficiency and feasibility on a gas turbine operating at high temperature. After that, they designed a prototype with the segmented thermoelectric generators based on theoretical analysis to continuously and steadily power the sensing and monitoring system with the energy harvested from the hot surface of the gas turbine. condition monitoring interruptions and wastes the labour and resources. Therefore, the wasted energy from machines or surrounding environments is attractive for researchers to harvest for powering the sensor nodes with EH technologies introduced previously. This approach substantially prolongs the life of sensing nodes and reduces maintenance costs of the monitoring system and the environmental contamination. The potential recyclable energy sources in or around mechanical systems and corresponding EH technologies have been discussed in detail in Sections 2 and 3, respectively. Several examples for various EH technologies are successfully applied in the WSN-based machine condition monitoring and these representative cases are demonstrated as follows to illustrate their prospects in self-powered WSNs in remote online machine condition monitoring. As the external energy sources of mechanical systems, light energy and RF energy are seldom harvested in the period of machine condition monitoring. The photovoltaic EH technology is primarily applied for large-scale power generation and infrequently used for machine condition monitoring at present. Only few references can be reviewed here. Wang et al.  designed a multisource (vibration, heat and light) energy harvester with piezoelectric, thermoelectric and photovoltaic EH technologies to power the WSN based acoustic emission sensing systems to successfully monitor the condition of the fear of a gas compressor. The manufactured prototype can generate 1.56 mW and 3.37 mW from 0.048 g vibration energy and thermoelectric energy of 62 ℃, respectively. Some researchers have investigated a WSN to detect the acceleration of the helicopter with the sensor nodes fed by the electricity harvested from the environment by a commercial RF energy harvester BIB005 . The distance between the tower antenna and the helicopters is about 76 m and the output DC power is about 70 μW. As a result, the solar energy is suitable to be harvested to power large-scale outdoor machines efficiently and effectively. The indoor light EH and RF EH can be considered as the supplement of other EH technologies. The internal energy sources are available and widely utilized for machine condition monitoring. For example, researchers at the University of Huddersfield designed a thermoelectric generator device, shown in Figure 16 and installed on the surface of the gearbox housing in Figure 4b , to harvest energy from the temperature gradient between the housing of the gearbox and the ambient temperature for powering a WSN system BIB010 . The temperatures of the ambient, gearbox surface and oil were simultaneously captured for the gearbox condition monitoring and fault diagnosis. Wu et al. BIB015 has established a mathematical model for evaluating the performance of the segmented thermoelectric generator by considering multiple parameters and then analyzed its efficiency and feasibility on a gas turbine operating at high temperature. After that, they designed a prototype with the segmented thermoelectric generators based on theoretical analysis to continuously and steadily power the sensing and monitoring system with the energy harvested from the hot surface of the gas turbine. According to the aforementioned analysis of mechanical kinetic energy sources, several application examples of the piezoelectric generators are cited to validate the effectiveness and availability in machine condition monitoring and fault diagnosis. In 2005, Plessis et al. BIB001 has evaluated the output power of a packaged piezoelectric generators with the cantilever architecture and monitors machinery health condition with wireless sensor nodes powered by the piezoelectric According to the aforementioned analysis of mechanical kinetic energy sources, several application examples of the piezoelectric generators are cited to validate the effectiveness and availability in machine condition monitoring and fault diagnosis. In 2005, Plessis et al. BIB001 has evaluated the output power of a packaged piezoelectric generators with the cantilever architecture and monitors machinery health condition with wireless sensor nodes powered by the piezoelectric generator. In the same period, Discenzo et al.  has proposed a self-powered WSN to monitor shipboard fluid pump condition in a terrible environment. A piezoelectric harvester is made to charge two lithium batteries to support the acquisition of vibration signals at 1 kHz and subsequent data processing and transmission. In addition, a piezoelectric generator is designed and tested both in the laboratory and on a large-scale turbo generator  . However, the result is not satisfactory because the power (microwatts) obtained on the real turbo generator are much lower than the power (milliwatts) collected in the laboratory. This conclusion explains that the resonant frequency of the piezoelectric generator system should be consistent with that of the mechanical system for optimum performance. Then, some electromagnetic generators applied in the field of machinery are focused to be introduced and discussed. In 2013, Waterbury and Wright BIB002 have investigated an electromagnetic generator, converting electricity from vibrations of large industrial pump motors, to support a self-sustaining wireless condition monitoring system. Another electromagnetic generator was made to scavenge rotating kinetic energy for powering a long-lasting CC2420 with a ZigBee module used for condition monitoring of the metal milling-processes and cutters in BIB006 . In addition, two types of electromagnetic generators are designed based on resonance and magnetic levitation respectively by Gao et al. BIB011 . The two electromagnetic generators are compared in Figure 17 . They are installed on the railway and harvested energy industrial pump motors, to support a self-sustaining wireless condition monitoring system. Another electromagnetic generator is made to scavenge rotating kinetic energy for powering a long-lasting when the train passed through. Additionally, the designers have further studied how to achieve a maintenance-free wireless monitor system with the assistance of a magnetic levitation harvester BIB012 . Another successful case for monitoring the condition of induction machine rotor is designed by Fernandes et al. BIB013 , and the fabricated magnetic generator successfully powered the NRF24L01 module for transferring the temperature characteristic of the motor. generator. In the same period, Discenzo et al.  has proposed a self-powered WSN to monitor shipboard fluid pump condition in a terrible environment. A piezoelectric harvester is made to charge two lithium batteries to support the acquisition of vibration signals at 1 kHz and subsequent data processing and transmission. In addition, a piezoelectric generator is designed and tested both in the laboratory and on a large-scale turbo generator  . However, the result is not satisfactory because the power (microwatts) obtained on the real turbo generator are much lower than the power (milliwatts) collected in the laboratory. This conclusion explains that the resonant frequency of the piezoelectric generator system should be consistent with that of the mechanical system for optimum performance. Then, some electromagnetic generators applied in the field of machinery are focused to be introduced and discussed. In 2013, Waterbury and Wright BIB002 have investigated an electromagnetic generator, converting electricity from vibrations of large industrial pump motors, to support a selfsustaining wireless condition monitoring system. Another electromagnetic generator was made to scavenge rotating kinetic energy for powering a long-lasting CC2420 with a ZigBee module used for condition monitoring of the metal milling-processes and cutters in BIB006 . In addition, two types of electromagnetic generators are designed based on resonance and magnetic levitation respectively by Gao et al. BIB011 . The two electromagnetic generators are compared in Figure 17 . They are installed on the railway and harvested energy industrial pump motors, to support a self-sustaining wireless condition monitoring system. Another electromagnetic generator is made to scavenge rotating kinetic energy for powering a long-lasting when the train passed through. Additionally, the designers have further studied how to achieve a maintenance-free wireless monitor system with the assistance of a magnetic levitation harvester BIB012 . Another successful case for monitoring the condition of induction machine rotor is designed by Fernandes et al. BIB013 , and the fabricated magnetic generator successfully powered the NRF24L01 module for transferring the temperature characteristic of the motor. Compared to the generators operating at extra low frequencies, another electromagnetic generator with the resonance at a fixed frequency of 200 Hz has been explored by Syed et al. BIB014 and installed on an industrial centrifugal pump to successfully power wireless sensors for condition monitoring. In order to overcome the narrow resonance frequency bands of electromagnetic generators, Wei et al. BIB016 designed a nonlinear vibration-based EH system model with a first order lever structure relying on an electromagnetic generator. The in-plane schematic representations of two consecutive operation states are shown in Figure 18 . The advantage of this design is that it may be tuned to a particular source and it has the ability to collect random noise energy. The main disadvantage of these models is the large and bulky volume. Compared to the generators operating at extra low frequencies, another electromagnetic generator with the resonance at a fixed frequency of 200 Hz has been explored by Syed et al. BIB014 and installed on an industrial centrifugal pump to successfully power wireless sensors for condition monitoring. In order to overcome the narrow resonance frequency bands of electromagnetic generators, Wei et al. BIB016 designed a nonlinear vibration-based EH system model with a first order lever structure relying on an electromagnetic generator. The in-plane schematic representations of two consecutive operation states are shown in Figure 18 . The advantage of this design is that it may be tuned to a particular source and it has the ability to collect random noise energy. The main disadvantage of these models is the large and bulky volume. Some investigators are committed to collecting wasted mechanical energy with multiple technology integration. An integrated generator, consisting of six acrylic hexagonal prisms, a cylindrical mass and a magnet (working as six triboelectric harvesters and an electromagnetic one), is designed and installed on an automobile wheel to convert rotational energy of the wheel into electricity in BIB004 . In addition, some engineers designed a system to harvest vibrational, thermal and light energy for establishing a rotating machine monitoring system based on acoustic emission signals BIB003 . ZigBee was selected as the transmission technology in this instance. Most of the models reviewed in this section are designed for monitoring the condition of machine systems with self-powered WSNs. However, the application of EH technologies in other fields is much more practical and prevalent. These designs can give some inspiration for applications of the individual or hybrid EH technologies in machine condition monitoring systems. It can be confirmed that ZigBee is utilized as a transmission method at a higher reliability now. But with the development of Wi-Fi and BLE, especially BLE 5, they will dominate in the market of machine condition monitoring in the future because they have advantages of low power consumption, fast transmission speed, long transmission distance, low cost and high stability.