Final Design

1. Overview of Final Solution

Figure 1. Flowchart illustrating overall design solution

2. CAD of Final Design

Figure 2. CAD model of final design solution

3. Functional Components

3.1 Fluidic chamber

Fluidic Chamber

The fluidic chamber shown in Figure 6 served several purposes, but primarily it was used for the observation of the test objects. Installed on both ends were 10-32 nozzles as fittings for the tubing system. The bottom nozzle served as the entrance (or inlet) nozzle where the flow is induced by the pump. At the top, a shutoff valve was fitted to the exit nozzle to allow for the easy insertion of test objects or organisms via a pipette equal to or less than 2mm in diameter

The fluidic chamber is a rectangular pipe modeled after a standard laboratory cuvette that is 10 mm wide on the side faces and 80mm tall. Both the front and back faces of the chamber are machined from water corrosion-resistant acrylic that is optically clear to provide for adequate lighting and imaging, and the side, top, and bottom faces are 3D-printed from (material). Inside the chamber at 30mm height is a 3D-printed diffuser in order to create a more uniform distribution of flow. The design of the diffuser was carefully analyzed for optimal flow, a 5mm width of 5% velocity gradient. The positioned height of the chamber is also adjustable using a 3D-printed mounting system.

Figure 3. CAD of Final Chamber Design

3.2 Test Object and Fluid

Test Object and Fluid

Due to complications of using live plankton, test objects were created to simulate plankton sinking velocities in strictly the vertical direction. High-density polyethylene (HDPE) is a plastic with density 0.94 g/cm3. This is sold in 1/8 inch (3.175 mm) diameter spheres by McMaster-Carr. Since the density of fresh water is 0.998 g/cm3, distilled water was mixed with 70% isopropyl alcohol solution (0.8523 g/cm3) for the purpose of density reduction. Forces of gravity (FG), buoyancy (FB) and drag (FD) were introduced within the fluid dynamics analysis of the sinking rate, and with integration over the chamber length, a relation between the water density and the ball’s velocity when entering the field of view was generated

3.3 Camera

Camera

The camera’s primary function was to capture images of the sinking object in order to perform image processing and determine the object’s position in real-time. A Logitech 2.0 web camera with a resolution of 2592 x 1944 monochrome and a lens of 3mm – 15mm provided imaging at a framerate of 30 fps. The field of view was experimentally determined to be 7 mm by 10 mm and the resulting pixel size is 5 µm/pixel and the size of the chamber was designed accordingly.

Figure 4. Logitech 2.0 Camera

3.4 Peristaltic Pump

Peristaltic Pump

According to its specifications, the peristaltic pump shown in Figure 5 had flow rate capabilities between 0.002 ml/min and 32 ml/min; the required flow rate of the fluidic treadmill system, based on the typical velocities of plankton, was 6 ml/min. The pump tubing had an inner diameter of 2.4mm and acted as the inlet at the bottom of the chamber, secured by an M3 tapped nozzle, as well as the exit for the fluid at the top of the chamber. Water exiting the chamber was dumped into a large reservoir tank outside the apparatus. This served to eliminate pressure differences within the chamber and prevented bubbles from forming within the fluid. Bubbles can hinder the observation of objects in the chamber, and negatively affect the velocity profile of the flow.

Figure 5. Peristaltic Pump

3.5 Image Processing

Image Processing

C++ and openCV library were used for imaging as well as the method for tracking the position of the object. The code applied a threshold to create better contrast in the image, clearly defining the shape of the object. It used blob analysis for object fitting and determining the centroid of the image based on image size which allowed tracking to be performed. It also found the vertical distance between the centroid and a reference position, which it sent as feedback information to the pump using the control algorithm.

A user interface (UI) was also developed to allow users to adjust the background subtraction, threshold, contrast, white balance, and saturation. Although the image processing was used on the HDPE spheres for the prototype testing, it is also capable of tracking any shape (hence “blob” analysis) or organism that fits in the observation chamber.

Figure 6. Image Processing Result

3.6 Pump Flow Velocity Control

Pump Flow Velocity Control

The pump flow speed was controlled using RS-485 serial communication through a direct connection to a PC. The control code was written in MATLAB, which took in the result of the image processing as an input. It subsequently implemented a position control algorithm to adjust the flow speed of the pump and stabilize the position of the object in the center of the image. Figure 7 is a block diagram of the control system used for the pump. The controlled plant represents the test object or organism in the system. The sensor/transducer is the camera, and the feedback is a result of the image processing code.

Figure 7 Feedback Controller