Vibration-based monitoring is an efficient approach to assess the reliability and performance of industrial machine applications. To meet the requirements of long range, low cost, low power, and high-accuracy synchronous acquisition in Internet of Things (IoT)-based vibration condition monitoring, a new multichannel micro-electromechanical system (MEMS)-based low-power wide-area network (LPWAN) incorporating LoRa with NB-IoT is proposed in this paper. This approach adopts a multichannel LoRa and NB-IoT gateway and multiple wireless MEMS-based LoRa nodes to construct the LPWAN for machine vibration monitoring in plants. Furthermore, Google cloud server and computing system are also able to facilitate the remote IoT-based communication. Finally, evaluations of proposed approach in machine vibration test and data synchronization test on electrical machinery are validated, showing that the proposed multichannel LPWAN monitoring approach has the abilities of high-precision data synchronous collections, big-data storage, and data stream uploading in a wide monitoring area in comparison with wired system and ordinary wireless sensor network-based system. This paper is conducted to provide new insights into how a LPWAN is designed in vibration monitoring for synchronous acquiring sensing data accurately and carrying out remote network communication efficiently, and further giving advisable reference to the LPWAN in more machine vibration monitoring scenarios.

In traditional airplane monitoring system (AMS), data sensed from strain, vibration, ultrasound of structures or temperature, and humidity in cabin environment are transmitted to central data repository via wires. However, drawbacks still exist in wired AMS such as expensive installation and maintenance, and complicated wired connections. In recent years, accumulating interest has been drawn to performing AMS via airborne wireless sensor network (AWSN) system with the advantages of flexibility, low cost, and easy deployment. In this review, we present an overview of AMS and AWSN and demonstrate the requirements of AWSN for AMS particularly. Furthermore, existing wireless hardware prototypes and network communication schemes of AWSN are investigated according to these requirements. This paper will improve the understanding of how the AWSN design under AMS acquires sensor data accurately and carries out network communication efficiently, providing insights into prognostics and health management (PHM) for AMS in future.

For a power supply of a low-voltage, low frequency, and pulsed current load such as the transmit and receive module (T/R module) of the solid-state radar, its output power is pulsed and input power is required to be constant. To balance the power difference and maintain a constant output voltage, the value of the storage capacitance is usually very large. In this article, a novel two-stage pulsed power supply is proposed. The intermedia bus capacitance is used as the storage capacitor to balance the power. An interleaved half-bridge converter with a wide voltage gain is adopted, so that the voltage of the storage capacitance can vary in a wide range, which greatly reduces the value of the storage capacitance. To suppress the fluctuation of the input current, a voltage feedforward control and a current preregulation control are proposed. Furthermore, the efficiency of the pulsed power supply is discussed. The comparative study shows an efficiency advantage of the two-stage scheme. Finally, a prototype with the output peak power of 2 kW, the average power of 325 W, and the pulse repetition frequency of 150-300 Hz is assembled and tested to verify the validity of the proposed two-stage pulsed power supply and its control methods.

Owing to its unique, concealment and easy customization by combining different wrist and hand gestures, high-density surface electromyogram (HD-sEMG) is recognized as a potential solution to the next generation biometric authentication, which usually adopts a wireless body sensor network (BSN) to acquire the multi-channel HD-sEMG biosignals from distributed electrode arrays. For more accurate and reliable classification, biometric authentication requires the distributed biosignals to be sampled simultaneously and be well aligned, which means that the sampling jitters among the arrays need to be tiny. To synchronize data sampling clocks of a cluster of BSN nodes for biometric authentication, this article modifies the packet-coupled oscillators protocol by using a dynamic controller (D-PkCOs). This protocol only involves one-way single packet exchange, which reduces the communication overhead significantly. For the purpose of maintaining precise sampling of these BSN nodes subject to drifting clock frequency and varying delays, the dynamic controller is designed via the $H_\infty$ robust method, and it is proved that all the BSN nodes’ sampling jitters are bounded. The experimental results demonstrate that the D-PkCOs protocol can keep the sampling jitters less than a microsecond in a 10-node IEEE 802.15.4 network. The application of D-PkCOs to the BSN shows that the HD-sEMG signal with a high signal-to-noise ratio is obtained, which leads to better gesture classification performance.

Traditional wired monitoring systems exhibit huge limitations in blast wave monitoring. To meet the requirements of long range, low cost, weight reduction, increased ease of installation maintenance and big-data transmission in blast wave monitoring, a new distributed linear-spatial-array (D-LSA) sensing system based on Low-Power Wide-Area Network (LPWAN) is proposed in this paper. This approach adopts a Multi-Channel LoRa and NB-IoT Air-blast Gateway (M-CLNAG) and multiple FPGA-based Wireless Pressure LoRa Nodes (FWPLN) to construct a large-scale LPWAN for blast wave monitoring. The empirical models of dynamic parameter calculation (peak overpressure, duration of the positive phase and impulse) on the basis of D-LSA sensing system are redesigned for blast wave monitoring as well. Furthermore, we have evaluated the errors between the measured data from D-LSA sensing system and data from the redesigned empirical models. Finally, the wireless quality performance in terms of Received Signal Strength Indication (RSSI) and packet receive rate (PDR) for blast wave monitoring is also verified. This paper is conducted to provide new insights into how a sensing system integrating with LPWAN is designed in blast wave monitoring for acquiring dynamic parameters accurately and carrying out remote network communication efficiently, and further opening an door for wireless sensor network (WSN) in more blast wave monitoring scenarios.

Vibration-based condition monitoring among all the components of the aircraft structure is an important approach to improve the flight safety before any component in aircraft reaches resonance. This paper presents multichannel and multihop low-power wide-area network (MCMHL) architecture suitable for vibration monitoring on aircraft. First, microelectro mechanical system-long Range (LoRa)-based sensor node architecture in light of hardware cross-layer algorithm is proposed for implementing the tradeoff among hardware cost, power consumption, and performance. To achieve high accuracy of synchronous acquisition, multihop slot segmenting scheduling and multichannel data communication algorithm are proposed. In addition, the beacon transmission delay, of beacon between sink and sensor nodes is calculated, and further synchronization compensation algorithm is designed. The experiments of the proposed approach in aircraft vibration test and data synchronization test on aircraft skin are validated, showing that the proposed MCMHL approach has these abilities of data synchronous collections, remote communication, and data stream uploading in a wide monitoring area.