Polyester Guqin String Trial #21

This string trial is the next iteration for an experimental twisted core polyester guqin string for string #6. Both the number of primary twists as well as the primary and secondary twist weights were slightly increased for this trial from the previous one. This trial also successfully produced a working string like the previous trials as well. Tonally, it is nearly identical from the previous trials, and a paper will be written on the comparative analysis of these trials and the changes in timbre based on the small iterative changes made per trial. Further iterations will attempt to push the primary and secondary twist weights higher, as this string survived the twist process with the specified weights below without issue.

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.


Material: Polyester

Thread: Barbook’s Weaverbird Polyester #15 Brown

Thread Diameter (in.): 0.0048″

Theoretical Calculated Twisted Substrand Diameter (in.): 0.0199″

Theoretical Calculated Twisted Total Diameter (in.): 0.043″

Thread Strength: 1.5lbs

# of Substrands: 3

# of Threads per Substrand: 12

Total Thread Count: 36

# of Primary Twists: 2025

Twist Angle (degrees): 45

Substrand Twist Direction: Clockwise

String Twist Direction: Clockwise

Primary Twisting Tension: 5lbs

Secondary Twisting Tension: 7lbs

Starting Length (in.): 120″

Ending Length (in.): n/a


1. Linear Spectrum Harmonic Content Graphs


2. Autocorrelation


3. Spectrograms (Window 4096)


4. Spectrograms (Window 2048)


5. Spectrograms (Window 512)


  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. 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.