We have both made considerable progress in their respective areas of focus in relation to the project.
Max:
Through an initial multimeter test of the first prototype of the generator, I found that the generator was producing voltage with alternating current. I also discovered through this test that there was a negligible amount of current being produced by the generator. To solve the first problem, converting the ac current to dc, I researched a component provided to us by Mr. Lin called a DC Rectifier. By utilizing the information I found I was able to construct a circuit that successfully converted the current to DC. The next step was to analyze this electricity with a oscilloscope. The graphs of the scope showed a large amount of interference which we will try and filter out on the next attempt at getting a data reading. With the information I was able to extract I came to the conclusion that the amount of wire we have wrapped around the doughnut provides us with 100 millivolts. A quick estimation revealed that we could fit four to five of these sections of wire on the doughnut. By adding these and doubling the thickness of each section we could potentially generate a full volt of electricity.
At this point two main problems are where we will focus our attention. The first is that even with the DC rectifier the multimeter was still not able to read any current in the generator. The second is that to maintain the amount of voltage I was achieving in the test, the ball would move much faster than a walking leg would be able to rotate it. We have not discussed a solution to the first problem because it is probably due to a low power generation. The second problem however is our main concern. In order to solve this we will use a program which I am still trying to obtain call maplesim. This program will allow us to implement the formula that Allen has been working on to create a model that will optimize the generator shape to cater to the motion of the leg. We will also construct a robot leg that we can use to uniformly test every new generator prototype we make.
Allen:
I have been working with the Kinovea video analysis software to acquire a rough estimate of the amount of kinetic energy yielded by the human walking motion, which could then be converted to power. The approach to determining rotational kinetic energy has varied; originally, I had been attempting to take the angle change of the entire leg to calculate angular velocity, but after conferring with Max and Mr. Lin, a better approach would be dividing the walking motion into two segments: one from hip to knee and the second from knee to ankle. This week, I have been honing in on the first segment. Although there is an angle tool in Kinovea with tracking capabilities, the data wouldn’t export to Excel. So, I has resorted to simple trigonometry; assuming that the length of each segment is fixed, the walking motion can be described in the form of an isosceles triangle, with two of the legs being equal (the length of the measured segment) and the base being that actual path of the knee marker.
Using that method of thinking, I divided the walking motion of a video clip (which he and Max had taken earlier on a treadmill, using neon green stickers as trackers) into 9 walking cycles. To find the third side, I found the slope of the tangent line for the path of the knee marker. This slope will be used to calculate the distance between the absolute extrema for each cycle graph, which will essentially be the third side of the triangle. Now, with three sides of a triangle, I can use the Law of Cosine to find the angle of each cycle’s triangle at its widest point. Using the Intermediate Value Theorem, because the motion of the knee is a continuous function, I can assume that there is a point in that function in which the angle is 0 radians - that is why finding the third side with the absolute extrema can be used to find the angle change, as the “longest” triangle will essentially describe the largest angle and consequently the total angle change.
I will find the average angular velocity for each cycle, and use that value - along with the moment of inertia for the hip-knee segment - to calculate a rough estimate of the rotational kinetic energy for that segment. I then will repeat the process for the second segment (knee to ankle). Since the motion of the knee isn’t purely rotational, I will also use Kinovea to calculate the translational kinetic energy for each segment, which should be a lot easier and require much less trigonometry. I will then send this out to Dr. Philip Martin of the Department of Kinesiology at Iowa State for an expert opinion, and if all bodes well, I will move on to working alongside Max with the MapleSim (or a similar tool) software, as well attempt to build a simple robot that uses segments to mimic gait motion to use during the testing phase of the project. A robot should yield more consistent results than a human, but first, a more optimally-shaped generator will need to be created, which will be the next phase.
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