A modern Data Acquisition System overcomes the limits of traditional stand-alone instrumentation already present in laboratories, mainly dedicated to solving a single specific task or a single measurement. Having a Data Acquisition System, on the other hand, allows the collection, storage and processing of a large amount of heterogeneous information in a safe and efficient manner , which are detected through a network of sensors and subsequently managed and made available through specific software solutions.
A Data Acquisition System, therefore, is the perfect tool for all companies that need to carry out one or more types of measurements and to manage the collected data in the simplest and most effective way .
A Data Acquisition System is an articulated system, composed of a chain of components that perform measurements, digitize the data collected and store them for their future use.
Its function is therefore to “translate” physical information, detectable by sensors, into digital information , which can be managed by a PC and subsequently used to make strategic decisions. To achieve this result, at least four different types of components are required:
A Data Acquisition System therefore starts from a hardware component – sensors – capable of collecting data that are appropriately processed in order to be acquired and managed by software.
The complexity of the system increases according to the number of measurements carried out, the presence of sensors of different types, the speed with which a phenomenon occurs, the need to integrate the data obtained. A Data Acquisition System can become – depending on the needs of the user and the level of development of the software for data processing – a simple or extremely complex system . Consequently it is necessary to design it in such a way that it guarantees extreme flexibility, expandability and a good level of customization.
A modern Data Acquisition System is therefore able to overcome the limits of traditional stand-alone instrumentation, natively allows communication between heterogeneous measures and has the advantage of being able to be customized, simply by customizing the software application that manages it or by adding hardware modules with different types of inputs and outputs.
This allows you to: