Monitoring Made Easy

Modern data acquisition systems face the challenge of how to manage data that may be coming from a variety of hardware on several different computers. These systems may be in one room or they may be all over the world. The challenges are still the same. You need to securely log the data to a file and then recall it at a later date. As an engineer, you also need to focus on developing the measurement or test aspects of your application, rather than the tools to get those measurements. You can use built-in elements for storing, viewing, and managing data, instead of programming them from scratch, in order to improve your productivity. This article helps you understand the challenges involved with developing a monitoring application.

What is a monitoring application?

A monitoring application involves acquiring data, storing it, and then recalling it at a later point for some type of analysis. There are a variety of reasons that you may need to recall stored data. You can use stored data to analyze a product or process and look for ways to improve it. You can also use it for debugging and localizing problems. Or, the data may be necessary to prove something to a regulatory body at a later date. Though the applications and data vary, it is important to remember that the tools needed to design a monitor the system are quite similar.

Every monitoring system has a handful of core features. First, you need to log the data to a storage location. Second, you must view the data both during and after the acquisition. Third, you need to record alarms or events triggered by the data. Fourth, implementing different types of security on the data should be easy. Fifth, networking should be simple and transparent to you. The LabVIEW platform software includes the LabVIEW Datalogging and Supervisory Control Module, which is a set of tools designed to assist in the development of monitoring applications and shorten development time.

Why do I need data logging?

Data logging is the process of acquiring and storing data. For more complicated applications, it becomes critical to have specialized data logging tools to assist with this process. There are many different ways to store data, and each has advantages and disadvantages. Relational and streaming databases are the two primary types of databases used. Relational databases are more traditional databases often used in business applications. Although extremely flexible, they are not optimal for disk space and fast throughput. In contrast, streaming databases are ideal for storing a large amount of data to a disk very quickly. However, you cannot define tables or other structures, eliminating much of the flexibility. When building your own database, some of the most common challenges are designing easy-to-use, scalable file and data structures. Without the right tools, you can spend hours of time designing and modifying your data structure. The LabVIEW Datalogging and Supervisory Control Module features a built-in streaming database for superior space utilization and throughput.

What is the difference between real-time and historical data visualization?

Logging data to disk is not the only challenge you face when designing these applications. You also need to view the data. There are two different ways to view data. First, you can view data from the server during the acquisition. This is also known as live data. You need to look at live data to monitor the status of a running system. It is important to understand the type of server you are connecting to and choose a software package that will help you communicate easily. One of the most common servers is OLE for process control (OPC). Finding a software package with a built-in OPC server/client can save valuable development time.

The second way to view data is after it has been stored in a file, also known as historical visualization. Use this data for post-acquisition analysis and presentations. The challenges associated with this are similar to logging the data. Without the right tools, you must know the file and data structures before analyzing and viewing the data. Choosing a software development tool that does this for you can save time.

The LabVIEW Datalogging Supervisory Control Module builds on the LabVIEW analysis and presentation functions to make this easy with built-in OPC connectivity and visualization for real-time and historical data.

How do I manage my alarms and events?

Usually when acquiring a large amount of data or data over a long period of time, you care about the changes in the data. You can monitor these changes using alarms and events. It is important to preserve the history of these alarms and events, so you can analyze them at a later date. Key features you need when working with alarms include generating an alarm, storing it according to the appropriate data, recalling it and all of the relevant information after the acquisition. Relevant information may include the time the alarm triggers, the person who acknowledged it, and the time of acknowledgement. With the LabVIEW Datalogging Supervisory Control Module, you can configure and monitor alarms using a wizard, so you can focus on the causes of alarms, rather than programming an alarm infrastructure yourself.

What about security?

Handling large amounts of data often raises security questions. Who should have access to the data and to what parts? Should everyone be able to modify the file or database? Probably not. Developing your own security code can be time consuming and cumbersome. By defining your needs up front, you can choose tools to help you develop security code. The LabVIEW Datalogging Supervisory Control Module helps you define different types of users and restrict their access to specific controls on the application and specific parts of the data.

How is networking handled?

As your data acquisition system grows, you can store the data on different local computers and monitor it centrally. Or, you can store the data on one central server. The most difficult challenge is communicating with live data. To ease this communication process, it is important to integrate your software tools with the operating system's native networking technology as transparently as possible. Your networking tools should maximize throughput and tolerate disruptions in the network. OPC is an industry standard that is designed to communicate with a variety of instruments. It may not operate at the performance you need for higher speeds though. The LabVIEW Datalogging Supervisory Control Module has built-in networking for optimal throughput.

Conclusion

National Instruments has LabVIEW tools that can help you design scalable monitoring applications easily and quickly. The LabVIEW Datalogging Supervisory Control Module addresses these concerns, so you can spend more time building your applications and less time worrying about programming the tools.

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