This string trial is currently the best iteration for my experimental twisted rope nylon strings for guqin string #5. Each substrand has 2 threads extra than the best trial for string #6, which is trial #24. Primary and secondary twist weight were both also increased as well due to increased overall string strength. Previous attempts were twisted to the breaking point, and iterated just before the breaking point. This string is slightly thicker than the average size for silk 5th strings, which is expected in theory due to the slightly lower density of nylon as compared with silk. This string was a bit tricky to make however, as the twisting rigs started to get stressed due to the increased weight. Further iterations with an increase in twisting weight may require modification to the equipment. Due to the higher weight and more strands used, twist number needed to be reduced, and is right at the maximum for these particular string parameters.
Included in this page are all of the major string parameters that I have obtained so far for this string, as well as all relevant data I have collected and analyzed for this string, including harmonic content data, spectrograms, and autocorrelation graphs. You can enlarge the images by clicking on the thumbnails.
STRING TRIAL #28 PARAMETERS
Thread: Middleburg Thread #15 Nylon Beige
Thread Diameter (in.): 0.0048″
Theoretical Calculated Twisted Substrand Diameter (in.): 0.0195″
Theoretical Calculated Twisted Total Diameter (in.): 0.0421″
Thread Strength: 2lbs
# of Substrands: 3
# of Threads per Substrand: 12
Total Thread Count: 36
# of Primary Twists: 1950
Twist Angle (degrees): 45
Substrand Twist Direction: Clockwise
String Twist Direction: Clockwise
Primary Twisting Tension: 9lbs
Secondary Twisting Tension: 9lbs
Starting Length (in.): 120″
Ending Length (in.): 107″
STRING TRIAL #28 DATA
1. Linear Spectrum Harmonic Content Graphs
3. Spectrograms (Window 4096)
4. Spectrograms (Window 2048)
5. Spectrograms (Window 512)
- Linear Spectrum Harmonic Content Graphs – Shows the harmonic content of each string, graphed along the linear spectrum in terms of frequency to intensity. A very accurate way to easily visualize the harmonics and overtones of each string.
- Autocorrelation – Shows the periodic nature or trends from a given set of data. Autocorrelation can provide a unique look at data, and can reveal repeating patterns from seemingly random datapoints. For this application, it is derived from the original signal and more clearly shows the decaying oscillatory nature of the plucked string.
- Spectrograms (Window 4096) – Shows the spectrogram of each string, with a window setting of 4096. This setting allows one to clearly view all of the harmonics by showing the frequency, intensity, and duration of each harmonic. This graph can be most easily cross-correlated to the linear spectrum harmonic content graphs to compare durations and intensities of harmonics in a string.
- Spectrograms (Window 2048) – Shows the spectrogram of each string, with a window setting of 2048. For this application, I have found that this setting is ideal in viewing the oscillatory instabilities of the guqin string more clearly, which cannot be seen as well in higher window settings. These are seen as wavering lines, which are most noticeably present in the mid-upper harmonics.
- Spectrograms (Window 512) – Shows the spectrogram of each string, with a window setting of 512. For this application, I have found that this setting, while having the lowest frequency band resolution of the three settings, allows one to zoom out on the entirety of the harmonic spectrum, and see how the overall power level and intensity shifts from one string to another, and where the harmonic content is overall most present for a given string.