Study on Vibration Reduction Due to Pile-Raft Foundation for High-Tech Lab Based on Frequency Sweep Test

Evaluation of the vibration reduction of piled-slab is of great significance for the layout of process and power equipment in high-tech facilities. In-situ measurement was performed to study the vibration reduction of the piled-slab of a high-tech lab. Slab vibrations with frequencies of 10 Hz to 60 Hz with steps 5 Hz were induced by an electromagnetic vibration exciter. INV3062U data acquisition device and 941B sensor were used to measure the velocities in the vertical direction at six measurement locations on the slab surface. For single frequency, the measurement results showed that the peak values of the slab vibration velocities generally decayed nonlinearly as the distance increased, however, the attenuations of 25 Hz, 35 Hz, 40 Hz, 50 Hz and 60 Hz slab vibrations were not monotonically.

A Versatile, Low-Power and Low-Cost IoT Device for Field Data Gathering in Precision Agriculture Practices

Spatial and temporal variability characterization in Precision Agriculture (PA) practices is often accomplished by proximity data gathering devices, which acquire data from a wide variety of sensors installed within the vicinity of crops. Proximity data acquisition usually depends on a hardware solution to which some sensors can be coupled, managed by a software that may (or may not) store, process and send acquired data to a back-end using some communication protocol. The sheer number of both proprietary and open hardware solutions, together with the diversity and characteristics of available sensors, is enough to deem the task of designing a data acquisition device complex. Factoring in the harsh operational context, the multiple DIY solutions presented by an active online community, available in-field power approaches and the different communication protocols, each proximity monitoring solution can be regarded as singular. Data acquisition devices should be increasingly flexible, not only by supporting a large number of heterogeneous sensors, but also by being able to resort to different communication protocols, depending on both the operational and functional contexts in which they are deployed. Furthermore, these small and unattended devices need to be sufficiently robust and cost-effective to allow greater in-field measurement granularity 365 days/year. This paper presents a low-cost, flexible and robust data acquisition device that can be deployed in different operational contexts, as it also supports three different communication technologies: IEEE 802.15.4/ZigBee, LoRa/LoRaWAN and GRPS. Software and hardware features, suitable for using heat pulse methods to measure sap flow, leaf wetness sensors and others are embedded. Its power consumption is of only 83 μA during sleep mode and the cost of the basic unit was kept below the EUR 100 limit. In-field continuous evaluation over the past three years prove that the proposed solution—SPWAS’21—is not only reliable but also represents a robust and low-cost data acquisition device capable of gathering different parameters of interest in PA practices.

In COM we trust: Feasibility of USB-based event marking

Modern experimental research often relies on the synchronization of different events prior to data analysis. One way of achieving synchronization involves marking distinct events with electrical pulses (event markers or “TTL pulses”), which are continuously recorded with research hardware, and can later be temporally aligned. Traditionally, this event marking was often performed using the parallel port in standard personal computers. However, the parallel port is disappearing from the landscape of computer hardware, being replaced by a serial (COM) port, namely the USB port. To find an adequate replacement for the parallel port, we evaluated four microcontroller units (MCUs) and the LabJack U3, an often-used USB data acquisition device, in terms of their latency and jitter for sending event markers in a simulated experiment on both Windows and Linux. Our results show that all four MCUs were comparable to the parallel port in terms of both latency and jitter, and consistently achieved latencies under 1 ms. With some caveats, the LabJack U3 can also achieve comparable latencies. In addition to the collected data, we share extensive documentation on how to build and use MCUs for event marking, including code examples. MCUs are a cost-effective, flexible, and performant replacement for the disappearing parallel port, enabling event marking and synchronization of data streams.

In COM We Trust: Feasibility of USB-Based Event Marking

Modern experimental research often relies on the synchronization of different events prior to data analysis. One way of achieving synchronization involves marking distinct events with electrical pulses (event markers or “TTL pulses”), which are continuously recorded with research hardware, and can later be temporally aligned. Traditionally, this event marking was often performed using the parallel port in standard personal computers. However, the parallel port is disappearing from the landscape of computer hardware, being replaced by a serial (COM) port, namely the USB port. To find an adequate replacement for the parallel port, we evaluated four microcontroller units (MCUs) and the LabJack U3, an often used USB data acquisition device, in terms of their latency and jitter for sending event markers in a simulated experiment. Our results show that all four MCUs were comparable to the parallel port in terms of both latency and jitter, and consistently achieved latencies under one millisecond. With some caveats, the LabJack U3 can also achieve comparable latencies. In addition to the collected data, we share extensive documentation on how to build and use MCUs for event marking, including code examples. MCUs are a cost-effective, flexible, and performant replacement for the disappearing parallel port, enabling event marking and synchronization of data streams.

MONITORING AND PREDICTIVE ANALYTICS OF TECHNOLOGICAL EQUIPMENT ON THE BASED OF INDUSTRIAL INTERNET OF THINGS

Произведен обзор технологий в рамках концепции четвертой промышленной революции, рассмотрены примеры реализации новых моделей управления технологическими процессами на базе промышленного интернета вещей. Описано техническое устройство основных подсистем системы мониторинга и контроля, служащей для повышения осведомленности о фактическом состоянии производственных ресурсов в особенности станков и аддитивного оборудования в режиме реального времени. Архитектура предлагаемой системы состоит из устройства сбора данных (УСД), реализующего быстрый и эффективный сбор данных от станков и шлюза, передающего ликвидную часть информации в облачное хранилище для дальнейшей обработки и анализа. Передача данных выполняется на двух уровнях: локально в цехе, с использованием беспроводной сенсорной сети (WSN) на базе стека протоколов ZigBee от устройства сбора данных к шлюзам и от шлюзов в облако с использованием интернет-протоколов. Разработан алгоритм инициализации протоколов связи между устройством сбора данных и шлюзом, а также алгоритм выявления неисправностей в сети. Расчет фактического времени обработки станочных подсистем позволяет более эффективно планировать профилактическое обслуживание вместо того, чтобы выполнять задачи обслуживания в фиксированные интервалы без учета времени использования оборудования We carried out a review of technologies within the framework of the concept of the fourth industrial revolution; we considered examples of the implementation of new models of process control based on the industrial Internet of things. We described the technical structure of the main subsystems of the monitoring and control system to increase awareness of the actual state of production resources in particular machine tools and additive equipment in real time. The architecture of the proposed system consists of a data acquisition device (DAD) that implements fast and efficient data collection from machines and a gateway that transfers the liquid part of information to the cloud storage for further processing and analysis. We carried out the data transmission at two levels, locally in the workshop, using a wireless sensor network (WSN) based on ZigBee protocol stack from the data acquisition device to the gateways and from the gateways to the cloud using Internet protocols. An algorithm was developed for initializing communication protocols between a data acquisition device and a gateway, as well as an algorithm for detecting network malfunctions. Calculating the actual machining time of machine subsystems allows us to more efficiently scheduling preventive maintenance rather than performing maintenance tasks at fixed intervals without considering equipment usage