Vibration detection

October 4, 2018ripplesiotData visualisation, IOT in factories, IOT in manufacturing, IOT sensors, IOT solutions

Early warning systems for factories

To measure vibrations we may measure displacement, velocity or acceleration using displacement sensors, velocity sensors or accelerometers. Among them, Accelerometer sensor is commonly used for vibration analysis and is capable of measuring machine accelerations, tilt, and vibration or shock. Condition monitoring and Predictive maintenance are the 2 relevant vibration monitoring applications that we have developed for industrial monitoring in factories.

MEMS is the latest technology of microscopic devices, particularly those with moving parts. With the advancement in electronic chip design, industrial IOT, MEMS sensors are preferred over Piezoelectric Sensors.

Low cost (Eg..MEMS- 50$ , Piezoelectric- 1000$)
Higher Accuracy & Ultra-low noise
High Frequency (not as high as piezo, but more than enough for what we need)
Compatible with IoT platforms
Low Power (can work on battery)
Based on smart factory concept

In an earlier IOT blog post, we have detailed about the need to monitor vibration of equipment to reduce breakdowns and unscheduled maintenance. Here are some of the factors which determines accuracy in machine behaviour.

Sensitivity

Sensitivity is the most important parameter of an accelerometer which means show accurate is the sensor output . It is specified in mV/G. (Eg. 1 mV/G, 100 mV/G ).

Range / Vibration Amplitude

Range means the range of vibration amplitudes which the accelerometer is capable to measure and is expressed like +-2g.

Bandwidth

Range of frequencies which the sensor can capture. A motor working at 1500 rpm (normal) require a sensor with minimum 1500 rpm bandwidth to capture abnormal vibrations.

Number of Axis

In order to detect vibrations sensors should be deployed on a proper machine point mounted in X,Y, or Z axis directions. In the market, sensors to capture vibrations at only 1 axis or all 3 axis at same time are present.

Noise

In order to capture ultra low motions in machines, ultra noise sensors are used. Piezoelectric sensors are widely used in industry due to low noise but in second generation, MEMS sensors with lower noise magnitude compared to Piezo electrics is been recently developed and we have implemented these solutions in our industrial monitoring and anomaly detection products.

Sampling Frequency

This means how many records the sensor captures in one second and it’s expressed in Hz. For a 1500 rpm motor sampling frequency should be at least 50 Hz.

Mounting Options

It determines how to mount sensor to the target machine surface. 4 mounting methods include: Handheld or probe tips, Magnetic, Adhesive and Stud mount. Stud mount is used for permanent and other mounts for temporary installations.The various mounting methods affect the measurable frequency of the accelerometer. Our condition monitoring solutions for factories are a mix of magnetic and adhesive based.

IOT & machine intelligence

September 13, 2018ripplesiotData visualisation, IOT in factories, IOT solutionsIOT chemical industry, IOT in biotechnology, IOT in manufacturing, IOT pharmaceutical industry, IOT smart factories, Retrofit IOT solutions

Data visualisation & diverse legacy machines

In this ever shifting world of technology, change is the only constant. It is believed that close to three billion people are online at a given time in today’s world and by 2020 close to 50 million devices are expected to be digitally interlinked by Internet of Technology.

So what does the IOT buzzword mean ? Well for starter, Internet of things creates a network of connected objects ranging from computers, smart phones, electronics, industrial machinery and appliances.

Retrofit IOT and machine intelligence

Industrial IOT has found its application mainly in manufacturing industries and shop floors as data from various types of machines can be monitored, integrated and analyzed for spotting maintenance issues and thereby enhancing the overall efficiency of the industry. Legacy plant and machinery can be “connected” to machine intelligence and data visualisation tools using our retrofit IOT products for factories.

As part of product research and development work, we have met several plant managers of global giants in manufacturing industries across Asia Pacific and the Indian subcontinent. Most of them believe that enabling machine to machine communication through a fully networked value chain helps in increasing the overall productivity of the plant.

The production logic can be fine tuned with the help of these Retrofit IOT enabled intelligent machines, allowing operational managers to reduce human intervention by a substantial factor. The IOT enabled technology also allows them to monitor and operate these machines even from a remote locale.

Data visualisation & legacy equipment

In a factory, the machines can range from 30-40 year old legacy ones to the ultra-modern all technology incorporated ones. What Ripples IoT monitoring solutions bring to the table is to acquire the data parameters from each of these machines and put them in a single platform for machine data analyzing and visualisation.

Obtaining data from legacy machines are particularly complex, as there are no data output options or proper documentation available from the same. With the help of wireless sensors that can be implanted non-intrusively, factors such as over-heating and excess vibrations etc. can be tracked proactively for such machines.

Some machines will have a RS-485 port to access the data, which can be connected to a controller module and from there data can be pushed to a cloud or server. Similarly we also have expertise in handling almost all legacy protocols such as BACNet, ModBus etc. along with latest wireless technologies like ZigBee, BLE and RFID.

So be it any kind of machines, old or new, we can help you gather all its data under one roof by enabling machine intelligence. We can help you create dashboards and visualization tools as per your needs and wants. For more details, please put in a message for a demo.

IOT gateway programming

August 23, 2018ripplesiotData visualisation, IOT solutions

Flask as middleware for IOT solutions

Flash middleware development India ; Flask IOT gateway programming
A few months ago, our R&D team was on the lookout for a flexible tool-kit that can act as a middleware in our IoT gateway development practices. The main requirement was that it should push the data to a REST API framework and the users should have the flexibility to use it any way they want.

We had thought about the ever so popular Django framework initially but decided to zero in on Flask, just because it was light-weight and delivered a better performance. Compared to other frameworks, Flask’s documentation was much intuitive

Flask is an extremely popular micro web framework that works on a minimal infrastructure and does not need any specific libraries or tools. Written in Python language, Flask is compact and robust to setup and hardly you will find an unused functionality therein. In our solution architecture, Flask API acts as a middleware and gives us the liberty to connect with the end client that supports REST protocol.

Our IoT powered industrial monitoring solutions handle a large amount of real-time data transfer. So, it was important to have a middleware entity that uses minimal infrastructure and give us maximum performance. The data comes through the sensors are handled by MQTT infrastructure and stored in InfluxDB time-series database.

The API would read the data from the database and the same can be used by third party platforms like OpenHab 2 or KepWare. We have worked extensively in OpenHab 2 platform and found it to be an extremely useful tool for data handling & visualization.

Another feature of Flask we liked very much is its ability to function both in cloud and on-premise setup. In an on-premise model, Flask can be deployed in a local WSGI server. It also has good authentication policies and supports open authentication frameworks. When the API is configured, we can access it directly from the browser and can be used to make API requests such as GET, PUT, POST & DELETE.

We can safely say that Flask delivered a consistent and an improved performance as a middleware for our IoT gateway.