The detection and analysis of the growth process of synthetic diamond single crystals under high temperature and high pressure primarily utilized Acoustic Emission (AE) detection technology. Here is the detailed detection and analysis process:
1. Construction of the Detection System
 Core Equipment: An AE detection system was built using  multi-channel acoustic emission instrument ,.
 System Components: This AE instrument is an eight-channel AE instrument controlled by a PCI bus, mainly comprising a computer, an AE signal acquisition and processing card, preamplifiers, sensors, and acquisition and analysis software. The system was equipped with 8 R6α type sensors and 8 1220A type preamplifiers.

2. Diamond Synthesis Experimental Method
 Synthesis Materials: Powder metallurgy iron-based catalyst and specialized graphite sheets for synthetic diamond were used.
 Assembly Method: The synthetic blocks were assembled using a sheet-stacking method.
 Synthesis Equipment: The assembled blocks were placed in an HPHT Hydraulic Cubic Press for conventional diamond single crystal growth.

3. Sensor Installation and Signal Export
 Signal Export: Due to the high pressure, the internal components of the press (steel ring, anvils, synthetic blocks, and the graphite and catalyst sheets within them) were compressed into an approximate continuous medium. Therefore, a waveguide was used to export the AE signals generated by the diamond single crystal growth inside the synthesis chamber.
 Waveguide Connection: One end of a self-made metal waveguide was tightly connected to the steel ring of the press.
 Sensor Installation: The AE sensor was installed at the other end of the waveguide, and high-temperature grease was used as a coupling agent to ensure the sensor could sensitively detect AE signals during diamond growth.
 Noise Suppression: To eliminate electromagnetic signals generated by the current passing through the front and rear anvils of the six-sided top press (which acts as a heating anvil) from affecting AE signal acquisition, the 8 sensors of the AE instrument were arranged asymmetrically on the remaining 4 anvils. This setup facilitated localized detection of AE sources.

4. AE Detection Hardware Settings
  Threshold: The fixed threshold was set to 40 dB.
  Gain Settings: The preamplifier gain was 40 dB, and the system main gain was 20 dB.
  Trigger and Recording: Pre-triggers were all 32μs, and the recorded data length was 1024 points. Peak Definition Time (PDT), Hit Definition Time (HDT), and Hit Lockout Time (HLT) were 300μs, 600μs, and 1000μs respectively.
  Filtering and Sampling: The band-pass filter's frequency range was set to 1–400 kHz, and the sampling frequency was 3 MHz.
5. Data Acquisition
  Acquisition Time: Since the diamond synthesis process is long, a consistent acquisition time window was chosen. The AE signal acquisition time region was selected as 160–320 s after the second pressure increase during diamond synthesis.
  Comparative Analysis: Within this time region, AE signals and their variation patterns were compared for cases with and without diamond single crystal growth.

6. AE Signal Analysis Methods
 Characteristic Parameter Analysis (Energy Method):
    This study used the energy method as a characteristic parameter to analyze AE signals.
    Energy value refers to the magnitude of energy obtained within a given measurement time, and energy per unit time is called energy rate. The energy analysis method directly measures the signal's amplitude (or RMS value) and duration, reflecting the characteristics of AE energy.
    By comparing the energy-time curves for diamond growth and non-growth (as shown in Figure 2 and Figure 3 in the source, though not provided in text, it describes the content), it was found that there was a clear AE signal background during diamond synthesis, and the AE signal energy showed a decreasing trend with increasing synthesis time. In contrast, when no diamond growth occurred, the AE signal background was lower, and the energy change was minimal. This indicates that significant AE signals were generated during diamond single crystal growth, and these signals changed corresponding to the growth.
    Noise Treatment: The experimental environment was complex with diverse noise sources. Even after spatial filtering to remove some noise, some signals with larger energy still existed, such as those generated by the cubic-anvil press during pressure compensation. These noise signals needed to be distinguished during analysis.

Waveform Analysis (Wavelet Transform):
    AE signal processing techniques based on waveform analysis obtain information about the AE source by recording the signal's time-domain waveform and its associated spectrum and correlation functions.
    This study primarily employed wavelet transform as the signal processing method. Wavelet transform is a time-frequency analysis method for signals, possessing multi-resolution analysis capabilities, able to characterize local features of signals in both time and frequency domains.
    Time-Domain Waveform: From the time-domain waveform diagrams (like Figure 4 in the source, content described), there was no significant difference in AE signals between diamond growth and non-growth. Both showed a signal with large amplitude and consistent frequency generated by the press itself, identified as noise.
    Spectrum Analysis: Fast Fourier transform was performed on AE signals with and without diamond growth to obtain amplitude spectra and power spectra (like Figure 5 in the source, content described). The results showed that AE signals with diamond growth had increased low-frequency information, primarily concentrated in the 1–200 kHz frequency band. There was no significant difference in the 200–400 kHz frequency band. This indicates that the AE signal of diamond single crystal growth is a low-frequency signal.
7. Conclusion
AE detection technology can effectively collect AE signals generated during diamond single crystal growth.
By analyzing characteristic parameters of AE signals, such as energy and spectrum, using signal processing methods like wavelet transform, it is possible to distinguish between the presence and absence of diamond growth and different stages of diamond single crystal growth.
The research results confirmed that the AE signal reflecting diamond single crystal growth is a low-frequency signal, mainly concentrated in the 1–200 kHz frequency band. This provides a reference for setting the operating frequency of filters in subsequent experiments.