Method and system for detecting weak signals and harmonics based on compression-enhanced stochastic resonance

Abstract

The application discloses a method and system for detecting weak signals and harmonics based on compression-enhanced stochastic resonance, comprising a vacuum system, a trapped field, a laser system, a fluorescence collection system and an external signal; the vacuum system comprises a vacuum cavity, an ion pump and a suction pump, a calcium atom furnace and a surface electrode ion trap for trapping calcium ions are arranged in the vacuum cavity; the trapped field comprises a radio frequency trapped field and a direct current trapped field, the radio frequency trapped field is composed of a radio frequency signal source, a power amplifier and a spiral resonant cavity; the direct current trapped field comprises a direct current high-voltage power supply, a 6733 board card and an amplification chip; the fluorescence collection system comprises an imaging mirror, a CCD camera and a photomultiplier tube; the external signal comprises a driving signal, a compression signal and a signal to be detected. The application uses the compression signal to replace the external random noise, triggers the ion to have periodic phase change with the signal to be detected, changes the intensity of the compression signal, makes the signal to be detected and the bistable system reach the best matching, and maximizes the signal-to-noise ratio and the detection of harmonics.

Description

Technical Field

[0001] This invention relates to the field of weak electric field signal and harmonic detection technology, specifically to a method and system for detecting weak signals and harmonics based on compression-enhanced random resonance. Background Technology

[0002] Weak signal detection aims to extract reliable and useful information from strong noise backgrounds, and its technological evolution and applications are continuously expanding into multiple fields. In scenarios such as inertial navigation, structural health monitoring, low-frequency communication, and basic physics experiments, the detected objects are often not only weak in amplitude but also frequently submerged in background noise, accompanied by complex interferences such as temperature drift, mechanical vibration, and stray fields, resulting in extremely low original signal-to-noise ratios. This challenge is also profoundly reflected in the precision monitoring of power systems: harmonic analysis has evolved from basic power quality assessment to a key means of diagnosing potential faults and warning of operational risks. Harmonics are not only a sign of power quality degradation but also the root cause of equipment overheating, malfunctions, and even resonant faults. Accurately capturing those weak harmonic components that are deeply embedded in the noise background and difficult to identify has become a prerequisite for assessing the health status of the system and ensuring the safe, stable, and efficient operation of the power system.

[0003] Faced with the aforementioned common detection challenges, traditional methods centered on noise suppression, such as matched filtering, adaptive filtering, Kalman filtering, and wavelet transform, are still applicable under medium to high signal-to-noise ratio conditions. However, when the target signal spectrum overlaps with the noise spectrum, or when the system has phase noise, channel inconsistency, and timing jitter, these methods not only fail to effectively extract useful components but may also weaken them. Furthermore, they typically rely on long integration times, limiting their real-time performance and applicability.

[0004] Stochastic resonance theory provides a new nonlinear enhancement path for weak signal detection (2017 Phys. Rev. Lett. 119, 234101. Phase Stochastic Resonance in a Forced Nanoelectromechanical Membrane). In bistable systems, when the weak signal, noise intensity, and system parameters are matched, some noise energy can be transferred to the signal, inducing an observable response and thus improving the output signal-to-noise ratio. Existing methods mostly trigger bistable switching by applying external white noise. While feasible in the laboratory, this approach suffers from problems such as difficulty in long-term calibration of the applied noise intensity and spectral shape, and the potential introduction of additional heating and decoherence.

[0005] Trapped ion systems, with their long coherence time, low loss, and optical readout capabilities, provide a highly sensitive platform for weak signal detection. (The last sentence appears to be incomplete and possibly refers to a separate topic: "using a single...") For example, ions undergo simple harmonic motion within a surface electrode ion trap, and forced vibration can be achieved by applying electrical drive near their intrinsic frequencies. As the drive amplitude scans, the system transitions from a coherent vibrational state to a cloud state, forming a bistable region within a specific parameter range, which can be effectively described using a Duffing-type nonlinear model. This bistable characteristic lays the physical foundation for the nonlinear amplification and detection of weak signals.

[0006] Unlike stochastic resonances induced by externally applied random noise, in stochastic resonances enhanced by a squeezing effect, the squeezing effect manifests as flattening the noise circle in phase space into a noise ellipse, thereby suppressing noise fluctuations in the target dimension and correspondingly enhancing them in the conjugate dimension. Applying a certain amount of pressure to the trapped ions... The compressed signal can be used to equivalently modulate the trapping potential field of the surface electrode ion trap, thereby achieving directional compression of ion motion noise; especially when the phase difference between the compressed signal and the ion vibration is approximately... When the phase direction noise is suppressed, the effect is most significant. Summary of the Invention

[0007] This invention aims to address the difficulties in detecting weak signals caused by complex and diverse background noise, low signal-to-noise ratio, and sensitivity of the operating point in existing technologies. It provides a method and system for detecting weak signals and harmonics based on compression-enhanced stochastic resonance. This scheme uses a single trapped ion as a carrier. By applying a driving signal with the same frequency as the ion's intrinsic frequency, the ion undergoes forced vibration in the nonlinear region of the ion trap. As the driving intensity changes, the ion's vibrational state switches between coherent vibrational state and cloud state. Finally, a compression signal twice the intrinsic frequency is applied to the ion to construct a deterministic noise redistribution mechanism, transforming the phase space noise from an equidirectional distribution into an oriented noise ellipse. By setting an appropriate driving intensity to place the ion in the bistable region, the strength of the weak signal to be measured, the compression signal, and the bistable threshold response are optimally matched, achieving signal-to-noise ratio enhancement and signal amplification without adding random noise. Compared to traditional noise-assisted stochastic resonance, the compression effect-assisted method of this invention does not require the introduction of new noise sources, significantly enhances the stability and repeatability of the system, reduces the risk of additional heating and decoherence, shortens the integration time, and improves the ability to identify weak signals mixed with noise spectra. This provides an engineerable and calibrable solution for high-sensitivity detection in complex environments. Most importantly, the compression effect-enhanced stochastic resonance can measure multiple harmonics, making a significant contribution to ensuring the safe, stable, and efficient operation of modern power systems.

[0008] The present invention is achieved by at least one of the following technical solutions.

[0009] A system for detecting weak signals and harmonics based on compression-enhanced stochastic resonance includes a vacuum system, a confinement field, a laser system, a fluorescence acquisition system, and an applied signal;

[0010] The vacuum system includes a vacuum chamber, an ion pump, and a suction pump. The ion pump and suction pump are used to maintain the vacuum in the vacuum chamber. A calcium atom furnace for generating calcium atoms and a surface electrode ion trap for trapping calcium ions are placed in the vacuum chamber.

[0011] The trapping field includes a radio frequency trapping field and a DC trapping field. The radio frequency trapping field is connected to the radio frequency electrode of the surface electrode ion trap through a vacuum cavity to generate a radial trapping electric field. The DC trapping field is used to generate an axial trapping electric field and to control the ion position and compensate for micro-motion.

[0012] The laser system includes an ionizing laser and a cooling laser. The ionizing laser is used to ionize calcium atoms produced in a calcium atom furnace. Ion-cooling lasers are used to cool ions;

[0013] The fluorescence acquisition system is used to acquire data for ion imaging and fluorescence counting;

[0014] The external signal includes a driving signal, a compressed signal, and a signal under test. The driving signal is used to generate a bistable state, the compressed signal is used to improve the signal-to-noise ratio and amplify the signal under test, and the signal under test is configured to modulate the driving signal.

[0015] Furthermore, an inverted viewing window is provided on the vacuum cavity, directly opposite the surface electrode ion trap, for optical imaging.

[0016] Furthermore, a small hole is provided at the position of the calcium atom furnace directly opposite the ion trapping point of the surface electrode.

[0017] Furthermore, the radio frequency trapping field includes a radio frequency signal source, a power amplifier, and a spiral resonant cavity. The radio frequency signal source is used to output the primary radio frequency signal required for trapping calcium ions. The primary radio frequency signal is input into the power amplifier to amplify the power of the primary radio frequency signal. The spiral resonant cavity couples the amplified primary radio frequency signal to the radio frequency electrode of the surface electrode ion trap.

[0018] Furthermore, the DC confinement field includes a DC high-voltage power supply, a data acquisition card, and an amplification chip; the DC high-voltage power supply is used to power the amplification chip, the output terminal of the data acquisition card is connected to the input terminal of the amplification chip to control the output of the amplification chip, and the output terminal of the amplification chip is connected to the corresponding electrode of the surface electrode ion trap through the DC wiring port on the vacuum cavity.

[0019] Furthermore, ionizing lasers include 423nm lasers, 732nm lasers, and 780nm lasers.

[0020] Furthermore, the cooling lasers include 866nm and 397nm lasers.

[0021] Furthermore, the fluorescence acquisition system includes an imaging mirror, a camera, and a photomultiplier tube. The imaging mirror is located behind the inverted window of the vacuum cavity and transmits the fluorescence emitted by the ions to the camera and the photomultiplier tube, thereby realizing the data acquisition of ion imaging and fluorescence counting.

[0022] Furthermore, the driving signal, compressed signal, and the signal under test are generated by two signal sources. One signal source is a dual-channel signal source with phase synchronization between the two channels, used to generate the driving signal and the compressed signal respectively. The driving signal is used to generate a bistable signal, and the compressed signal is used to improve the detection signal-to-noise ratio and amplify the signal under test. The other signal source is a single-channel signal source used to generate the signal under test. The two signal sources are connected to the same reference signal.

[0023] The method for implementing the system for detecting weak signals and harmonics based on compression enhancement stochastic resonance includes the following steps:

[0024] Step 1: The calcium atom furnace is heated by electric current, causing calcium atoms to vaporize and be ejected into the trapping region. An ionization laser strips the outer electrons of the calcium atoms ejected from the furnace to generate calcium ions, which are then trapped in the three-dimensional trapping potential field generated by the surface electrode ion trap. Subsequently, the ions are Doppler cooled by a cooling laser to form calcium ions that can be stably trapped. Finally, a DC trapping field pushes the ions away from the center of the surface electrode ion trap to the edge of the surface electrode ion trap, trapping the ions in a region with strong nonlinear potential field, maximizing the width of the hysteresis loop in the stable trapping region.

[0025] Step 2: Input the driving signal with the same frequency as the ion vibration onto the ion through the electrode of the surface electrode ion trap, drive the ion to undergo forced vibration and become a coherent vibration state, adjust the driving signal intensity to make the ion in a nonlinear state, and obtain the hysteresis loop of ion fluorescence count as a function of driving intensity by scanning the amplitude of the driving signal.

[0026] Step 3: Set the modulation type of the driving signal channel to external modulation and the modulation type to amplitude modulation. Use the signal under test to perform amplitude modulation on the driving signal, and finally input it into the surface electrode ion trap together with the driving signal.

[0027] Step 4: Collect fluorescence signals using a fluorescence acquisition system, analyze and extract the information of the signal to be measured, and calculate the signal-to-noise ratio of the signal to be measured and its harmonics;

[0028] Step 5: Input the compressed signal into the surface electrode ion trap, and acquire the test signal information after the compressed signal is input through the fluorescence acquisition system;

[0029] Step 6: Change the strength of the compressed signal to obtain the signal-to-noise ratio relationship between the output signal-to-noise ratio and the strength of the compressed signal;

[0030] Step 7: Under optimal compression strength, perform step 4 to obtain the final frequency and amplitude of the weak signal to be measured.

[0031] Compared with the prior art, the present invention has the following advantages:

[0032] This invention utilizes compressed signals to replace random noise to induce random resonance, selecting the optimal compression intensity corresponding to the signal under test. This successfully extracts weak signal information from high background noise, significantly improving the signal-to-noise ratio while enhancing system stability and repeatability, reducing the risks of additional heating and decoherence, shortening integration time, and improving the ability to identify weak signals aliased with noise spectra. This provides an engineerable and calibrable solution for high-sensitivity detection in complex environments. Most importantly, the compression-enhanced random resonance can measure multiple harmonics, making a significant contribution to ensuring the safe, stable, and efficient operation of modern power systems.

[0033] This invention utilizes the compression effect to significantly enhance the detection capability of stochastic resonance for weak signals, greatly improving the signal-to-noise ratio of signal detection. The compression-enhanced stochastic resonance successfully detected weak signals and their harmonics. Attached Figure Description

[0034] Figure 1 This is a flowchart illustrating the method for detecting weak signals and harmonics based on compression-enhanced stochastic resonance in this embodiment.

[0035] Figure 2 This is a schematic diagram of the system for detecting weak signals and harmonics based on compression enhancement random resonance in the embodiment.

[0036] Figure 3 This is a schematic diagram of the structure of the ion trap into which the driving signal, compression signal, and test signal are input in the embodiment.

[0037] Figure 4 The example shows the hysteresis loop plot of ion radiation fluorescence as a function of driving signal intensity.

[0038] Figure 5 This is a time-domain waveform diagram of fluorescence counting without compressed signal input in the embodiment.

[0039] Figure 6 This is an FFT spectrum diagram without compressed signal input in the embodiment.

[0040] Figure 7 The time-domain waveform of fluorescence counting is shown in the embodiment with the optimal compressed signal strength input.

[0041] Figure 8 The FFT spectrum is the input signal strength for the optimal compressed signal in this embodiment.

[0042] Figure 9 The image shows the time-domain waveform of fluorescence counting when the compressed signal is too strong during the embodiment.

[0043] Figure 10 This is the FFT spectrum of the compressed signal input in the embodiment.

[0044] Figure 11 This is a graph showing the change in signal-to-noise ratio with compression intensity in the example. Detailed Implementation

[0045] To facilitate understanding and implementation of the present invention by those skilled in the art, the present invention will be further described in detail below with reference to examples. The implementation examples described herein are only for illustration and explanation and are not intended to limit the present invention.

[0046] Example 1

[0047] The system for detecting weak signals and harmonics based on compression-enhanced stochastic resonance in this embodiment includes a vacuum system, a confinement field, a laser system, a fluorescence acquisition system, and an external signal.

[0048] The vacuum system includes a vacuum chamber, an ion pump, and a suction pump, wherein the ion pump and suction pump are used to maintain the vacuum in the vacuum chamber at 10. -9 The vacuum chamber contains a calcium atom furnace for generating calcium atoms and a surface electrode ion trap for trapping calcium ions. An inverted window is set on the vacuum chamber, directly opposite the surface electrode ion trap, for optical imaging.

[0049] In this embodiment, the calcium atom furnace is a hollow cylinder 30mm long, 2mm in outer diameter, and 1.9mm in inner diameter. A 1mm hole is drilled at the position of the calcium atom furnace directly opposite the trapping point of the surface electrode ion trap. The 1mm hole directly opposite the trapping point facilitates the precise injection of subsequently vaporized calcium atoms into the trapping area.

[0050] The confinement field mainly includes radio frequency confinement field and DC confinement field.

[0051] The radio frequency (RF) trapping field consists of an RF signal source, a power amplifier, and a helical resonant cavity. The RF signal source outputs the primary RF signal required to trap calcium ions. However, the signal power generated by the source is relatively low, so the primary RF signal is input to a 2W power amplifier to amplify its power. Since the electrodes of the surface electrode ion trap act as capacitors, AC signals cannot be directly input. To successfully generate an RF trapping electric field on the surface electrode ion trap, a helical resonant cavity couples the amplified primary RF signal to the RF electrode of the surface electrode ion trap. The output of the helical resonant cavity is connected to the RF electrode of the surface electrode ion trap through an RF wiring port on the vacuum cavity to generate a radial trapping electric field.

[0052] The DC trapping field consists of a DC high-voltage power supply, a data acquisition card, and an amplification chip. The data acquisition card is a 6733 board, and the amplification chip is an OPA462 chip. The DC high-voltage power supply powers the amplification chip. The output of the 6733 board is connected to the input of the OPA462 chip to control its output. The signal output from the OPA462 chip is connected to the corresponding electrode of the surface electrode ion trap through a DC connection port on the vacuum chamber, used to generate an axial trapping electric field, control ion position, and compensate for micro-motion.

[0053] The laser system includes ionizing lasers and cooling lasers. The ionizing lasers include 423nm, 732nm, and 780nm lasers, used to ionize calcium atoms produced in a calcium atom furnace. Ion cooling lasers, including 866nm and 397nm lasers, are used for cooling ions. All five types of lasers mentioned above are directly generated by commercial lasers. Ionizing calcium atoms produced in a calcium atom furnace into calcium ions is an existing technology, as is cooling.

[0054] The fluorescence acquisition system includes a 20x magnifying imaging mirror, a camera (CCD), and a photomultiplier tube (PMT). The 20x magnifying imaging mirror is located behind the inverted window of the vacuum cavity, transmitting the fluorescence emitted by ions to the camera and photomultiplier tube to achieve data acquisition for ion imaging and fluorescence counting.

[0055] The external signals include a drive signal, a compressed signal, and the signal under test (DUT). These signals are generated by two signal sources. One source is a dual-channel source with phase synchronization between the two channels, used to generate the drive signal and the compressed signal respectively. The drive signal is used to generate a bistable signal, and the compressed signal is used to improve the detection signal-to-noise ratio and amplify the DUT. For ease of description, this source is designated as signal source number one. The other source is a single-channel source used to generate the DUT. For ease of description, this source is designated as signal source number two. Signal source number two is connected to the same reference signal as signal source number one. Figure 3As shown, the driving signal is simultaneously applied to electrodes SE2 and SE3 of the surface electrode ion trap, and is radiated onto the ions by electrodes SE2 and SE3; the compression signal is input to the ions by electrode SE1 of the surface electrode ion trap; the signal to be measured output by the second signal source is used as an external modulation signal to be connected to the first signal source to modulate the intensity of the driving signal, and is finally input into the surface electrode ion trap together with the driving signal.

[0056] Ions trapped in surface electrode ion traps under the influence of the trapping field, laser light, and applied signals can be effectively theoretically modeled using a Duffing-type nonlinear model. The differential equations of motion are as follows:

[0057] (1);

[0058] in This represents the displacement of an ion from its equilibrium position. The first derivative of the displacement of an ion from its equilibrium position represents the ion's velocity. The second derivative of the displacement of the ion from its equilibrium position represents the acceleration of the ion. Indicates time, For ion mass, is the natural vibrational frequency of the ion. To cool the friction coefficient generated by the laser, These are nonlinear coefficients. For compressive strength, This represents the difference between the phase of the compression signal and the phase of the ion motion; the measured signal acts as the amplitude modulation signal of the driving signal, forming a common signal, and the force generated is... , Let's consider the thermal noise of the system. Taking into account the thermal noise of amplitude and phase in the Duffing oscillator, the solution to equation (1) can be written as:

[0059] (2);

[0060] in, This represents the average value of the ion amplitude. and These represent the amplitude and phase changes over time, respectively. For ease of study, the following will... Projected onto two orthogonal components and The changes in the two components over time are denoted as follows: and Equation (2) can be mathematically rewritten in the following form:

[0061] (3);

[0062] The two orthogonal components can be written as slowly varying envelope functions of the ion amplitude and phase, i.e.

[0063] (4);

[0064] So, and The standard deviation can be written as and .in and The standard deviation of ion amplitude and phase.

[0065] Force generated by external signal and thermal noise It can also be written in the form of same-frequency components:

[0066] (5);

[0067] (6);

[0068] in , They represent exist and Components in direction, , They represent exist and Components in direction.

[0069] Substituting the projected result back into the differential equation of motion of the ion, under the slow-varying approximation, the second derivative is neglected. and And the influence of higher-order terms (second harmonics and above) on ions. and The equations of motion for the components can be written as the following two formulas:

[0070] (7);

[0071] (8);

[0072] in , They represent respectively to and The first derivative of . From the above equation, it can be seen that the compressed signal for and The coefficient of friction varies with the component, resulting in different effects. Increased in quantity times, while The amount of food has been reduced. Times. When no compression signal is injected. , and This represents a stationary random process under thermal noise, where the system is in and Noise in a particular direction is defined by temperature as follows:

[0073] (9);

[0074] in, , Indicates in and The variance in the two component directions. Boltzmann's constant, Let be the temperature of the ions. From the above equation, it can be seen that the measured ion noise is related to the ion vibration frequency. Under the application of a compression signal, the change in the friction coefficient causes a change in the ion vibration frequency. The system in... and The noise in the direction becomes:

[0075] (10);

[0076] (11);

[0077] in , The compressive strength and compression phase are respectively hour, and The variance in the directions of the two components. Then... The value range of is (0, 1). Combining this with the result without compression, we can know that the compression ratio of the compressed signal in terms of amplitude and phase is:

[0078] (12);

[0079] (13);

[0080] in , These represent the compression ratios of amplitude and phase, respectively. , These represent the compressive strength and compression phase, respectively. At that time, the variance of ion amplitude and phase, , These represent the variances of the ion amplitude and phase, respectively, when the compressive strength is zero.

[0081] In summary, when no compression signal is added... The system has the same noise in both components, when the compressed signal is added (when... The noise in the phase direction is reduced to half its original value, while the noise in the amplitude direction is amplified, exhibiting an extremum and displaying an elliptical distribution in phase space. By changing the intensity of the compressed signal, the distribution strength of the noise in the amplitude direction is altered, thereby inducing random resonance and amplifying the signal under test.

[0082] In this embodiment, by changing the intensity of the compressed signal generated by the first signal source, the noise intensity in the amplitude dimension is controlled, thereby matching the optimal noise intensity required for the system to randomly resonate with the probe signal.

[0083] Example 2

[0084] A method for detecting weak signals and harmonics based on compression-enhanced stochastic resonance, implemented using the system for detecting weak signals and harmonics based on compression-enhanced stochastic resonance described in Example 1, includes the following steps:

[0085] Step 1: Stable trapped calcium ions are generated in a vacuum cavity and trapped in a region with strong nonlinear potential field by a DC trapping field.

[0086] The vacuum chamber is maintained at 10 using a vacuum chamber, an ion pump, and a suction pump. -9 Under ultra-high vacuum on the order of Pa, a calcium atom furnace loaded with calcium powder is placed in a vacuum chamber. A 1 mm hole is drilled at the position of the calcium atom furnace directly opposite the trapping point of the surface electrode ion trap. The calcium atom furnace is heated by electric current, causing the calcium atoms inside to vaporize and be ejected into the trapping region. An ionization laser strips the outer electrons of the ejected calcium atoms to generate calcium ions, which are then trapped in the three-dimensional trapping potential field generated by the surface electrode ion trap. Subsequently, the ions are Doppler cooled by 397 nm and 866 nm lasers to form stably trapped calcium ions.

[0087] By increasing the voltage of electrodes EE2 and EE3 and decreasing the voltage of electrodes EE1 and EE4 in the surface electrode ion trap using a DC high-voltage power supply, calcium ions are pushed away from the center to the edge of the surface electrode ion trap, trapping the ions in a region with strong nonlinear potential. In this stable trapping region, the width of the hysteresis loop is maximized. As an example, this embodiment selects the dimension of the line connecting electrodes CE3 and CE8 in the surface electrode ion trap, exciting the ions to undergo forced vibration in response to the driving signal. At this time, the natural vibration frequency of the ions... .

[0088] Step 2: Use signal source number one to set an appropriate driving intensity so that the ion is located in the middle of the hysteresis loop.

[0089] The driving signal is generated using signal source number one, and the signal frequency is the same as the ion vibration frequency. The driving signal is input to the ions through electrodes SE2 and SE3 of the surface electrode ion trap, driving the ions to undergo forced vibrations, thus transforming them into a coherent vibrational state. As the driving signal gradually increases, the vibrational amplitude of the ions gradually increases. When the driving signal intensity is too high, the ion state changes from a coherent vibrational state to a cloud state, at which point the fluorescence emitted by the ion radiation drops sharply to near background levels. The hysteresis loop of ion fluorescence count as a function of driving intensity is obtained by scanning the amplitude of the driving signal, as shown below. Figure 4 As shown, the fluorescence curve corresponding to the arrow to the right is scanned from small to large driving signal amplitude, and the fluorescence curve corresponding to the arrow to the left is scanned from large to small driving signal amplitude. An appropriate driving intensity is set so that the ions are located in the middle of the hysteresis loop.

[0090] Step 3: Use the second signal source to generate the signal to be tested to modulate the amplitude of the driving signal and input it into the surface electrode ion trap.

[0091] The signal to be tested is generated using a second signal source. In this embodiment, the frequency of the signal to be tested is [frequency value missing]. The signal strength is 1mV. The modulation type of the drive signal channel generated by signal source one is set to external modulation, and the modulation type is set to amplitude modulation. The signal to be measured is connected to signal source one to perform amplitude modulation on the drive signal, and finally input together with the drive signal into the surface electrode ion trap. Figure 3 A schematic diagram of the signal input is shown.

[0092] Figure 5 and Figure 6 The real-time fluorescence counting time-domain waveform and the FFT spectrum after Fourier transform are shown when only the driving signal and the signal under test are input. At this time, no jump in fluorescence counting is visible in the time domain signal, and no corresponding signal peak appears in the FFT spectrum. It is determined that the signal under test cannot be measured under this condition.

[0093] Step 4: Use a fluorescence acquisition system to acquire fluorescence signals, analyze and extract the information of the signal to be tested, and calculate the output signal-to-noise ratio (SNR).

[0094] The time-domain waveform of ion radiation fluorescence counts is recorded in real time by the PMT in the fluorescence acquisition system. The corresponding FFT spectrum can be obtained through Fourier transform. The highest main signal peak corresponds to the frequency peak of the fundamental signal, and the additional peaks with progressively decreasing heights are the frequency peaks of the corresponding harmonic signals. The signal-to-noise ratio (SNR) of the weak test signal and its harmonics can be obtained by subtracting the average amplitude of the background noise around each corresponding signal peak. In one embodiment, the PMT is set to acquire one fluorescence count point every 20 ms, which is sufficient for the sampling rate required for the test signal, with a total acquisition time of 60 s.

[0095] Step 5: Use signal source 1 to generate a compressed signal and input it into the surface electrode ion trap. Obtain the signal information to be measured after the compressed signal is input through step 4.

[0096] A compressed signal, synchronized with the driving signal and with a frequency twice that of the driving signal, is generated using signal source number one. This compressed signal is then input to the ions via electrode SE1 of the surface electrode ion trap, and the intensity of the compressed signal is set. Step 4 yields the fluorescence counting time-domain waveform and the FFT spectrum after Fourier transform of the input signal. For example... Figure 7 and Figure 8 As shown, regular fluorescence count jumps can now be observed in the time domain plot, and the signal frequency can also be clearly seen in the FFT spectrum. The frequency peaks at the locations and the corresponding harmonic signal peaks are shown in the figure. It can be seen that the 19th harmonic can be measured. Since the signal used in this embodiment is a square wave, only odd harmonics appear in the figure.

[0097] Step 6: Change the strength of the compressed signal input to signal source 1 to obtain the signal-to-noise ratio relationship between the output signal-to-noise ratio and the strength of the compressed signal.

[0098] Change the strength of the compressed signal input from signal source one, and repeat step 4 to obtain the signal-to-noise ratio relationship of the output signal-to-noise ratio as a function of the compressed signal strength, as shown below. Figure 11 As shown, the signal-to-noise ratio first increases rapidly and then decreases slowly with increasing compression intensity. The maximum signal-to-noise ratio at location is approximately 18 dBm; Figure 9 and Figure 10 The diagram shows the time-domain and FFT frequency-domain plots acquired by the PMT when the compression intensity is too high. Although the periodicity of the time-domain plot is not obvious, the signal peaks and a small number of harmonic signals can still be clearly seen in the FFT frequency-domain plot.

[0099] Step 7: Under optimal compression strength, perform step 4 to measure the frequency and amplitude of the weak signal to be measured.

[0100] This embodiment selects the compressed signal strength corresponding to the maximum signal-to-noise ratio. As the optimal compression strength, step 4 is performed to measure the final frequency and amplitude of the weak signal under test.

[0101] Based on this, the present invention proposes to achieve stochastic resonance-type weak signal amplification by replacing external random noise with compressed signal within the framework of single-ion nonlinearity and bistable dynamics: firstly, at the ion intrinsic frequency... Nearby scan driving intensity is used to determine the bistable interval; then, the following is introduced: By compressing the signal and aligning the minor axis of the noise ellipse with the phase axis, phase noise is reduced. Furthermore, enhanced fluctuations in the conjugate quadrant more efficiently trigger the phase transition of ions from the coherent state to the cloud state, ultimately improving the signal-to-noise ratio and threshold response of weakly periodic signals. Compared to traditional noise-assisted stochastic resonance, the compression effect-assisted method of this invention does not require the introduction of an additional noise source, significantly improving system stability and repeatability, reducing the risk of additional heating and decoherence, shortening integration time, and enhancing the ability to identify weak signals aliased with the noise spectrum, such as multiple harmonic components in power systems.

[0102] This invention is particularly suitable for broadband harmonic detection in power systems. It can highly sensitively resolve weak harmonic components embedded in noise backgrounds and provides a solution for highly sensitive, engineerable, and calibrable detection in complex electromagnetic environments through a random resonance mechanism enhanced by compression effect.

[0103] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the scope of protection of the present invention. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the essence and scope of the technical solutions of the present invention.

Claims

1. A system for detecting weak signals and harmonics based on compression-enhanced stochastic resonance, characterized in that, Includes a vacuum system, a confinement area, a laser system, a fluorescence acquisition system, and an external signal; The vacuum system includes a vacuum chamber, an ion pump, and a suction pump. The ion pump and suction pump are used to maintain the vacuum in the vacuum chamber. A calcium atom furnace for generating calcium atoms and a surface electrode ion trap for trapping calcium ions are placed in the vacuum chamber. The trapping field includes a radio frequency trapping field and a DC trapping field. The radio frequency trapping field is connected to the radio frequency electrode of the surface electrode ion trap through a vacuum cavity to generate a radial trapping electric field. The DC trapping field is used to generate an axial trapping electric field and to control the ion position and compensate for micro-motion. The laser system includes an ionizing laser and a cooling laser. The ionizing laser is used to ionize calcium atoms produced in a calcium atom furnace. Ions are cooled by lasers; fluorescence acquisition systems are used to collect data for ion imaging and fluorescence counting. The external signal includes a driving signal, a compressed signal, and a signal under test. The driving signal is used to generate a bistable state, the compressed signal is used to improve the signal-to-noise ratio and amplify the signal under test, and the signal under test is configured to perform amplitude modulation on the driving signal. A driving signal is generated using a signal source, the frequency of which is the same as the vibration frequency of the ion. The driving signal is input to the ion through electrodes SE2 and SE3 of the surface electrode ion trap, causing the ion to undergo forced vibration and become a coherent vibration state. By setting an appropriate driving intensity, the hysteresis loop of ion fluorescence count as a function of driving intensity is obtained by scanning the amplitude of the driving signal, so that the ions are located in the middle of the hysteresis loop. The signal to be measured is generated by the second signal source to modulate the amplitude of the driving signal and input it into the surface electrode ion trap; A compressed signal, which is phase-synchronized with the driving signal and has a frequency twice that of the driving signal, is generated using a signal source. The compressed signal is then input to the ions through the electrode SE1 of the surface electrode ion trap. The intensity of the compressed signal is set, and the fluorescence signal is collected using a fluorescence acquisition system at the intensity of the compressed signal with the highest signal-to-noise ratio. The information of the signal to be measured is analyzed and extracted, and the frequency and amplitude of the weak signal to be measured are finally obtained.

2. The system for detecting weak signals and harmonics based on compression enhancement random resonance according to claim 1, characterized in that, An inverted viewing window is positioned on the vacuum cavity, directly opposite the surface electrode ion trap, for optical imaging.

3. The system for detecting weak signals and harmonics based on compression enhancement random resonance according to claim 1, characterized in that, A small hole is provided at the position of the calcium atom furnace opposite the ion trap trap point of the surface electrode.

4. The system for detecting weak signals and harmonics based on compression enhancement random resonance according to claim 1, characterized in that, The radio frequency trapping field includes a radio frequency signal source, a power amplifier, and a spiral resonant cavity. The radio frequency signal source is used to output the primary radio frequency signal required to trap calcium ions. The primary radio frequency signal is input into the power amplifier to amplify the power of the primary radio frequency signal. The spiral resonant cavity couples the amplified primary radio frequency signal to the radio frequency electrode of the surface electrode ion trap.

5. The system for detecting weak signals and harmonics based on compression enhancement random resonance according to claim 1, characterized in that, The DC trapping field includes a DC high-voltage power supply, a data acquisition card, and an amplification chip. The DC high-voltage power supply powers the amplification chip, and the output of the data acquisition card is connected to the input of the amplification chip to control its output. The output of the amplification chip is connected to the corresponding electrode of the surface electrode ion trap through a DC connection port on the vacuum chamber.

6. The system for detecting weak signals and harmonics based on compression enhancement random resonance according to claim 1, characterized in that, Ionizing lasers include 423nm lasers, 732nm lasers, and 780nm lasers.

7. The system for detecting weak signals and harmonics based on compression enhancement random resonance according to claim 1, characterized in that, Cooling lasers include 866nm lasers and 397nm lasers.

8. The system for detecting weak signals and harmonics based on compression enhancement random resonance according to claim 2, characterized in that, The fluorescence acquisition system includes an imaging mirror, a camera, and a photomultiplier tube. The imaging mirror is located behind the inverted window of the vacuum cavity and transmits the fluorescence emitted by the ions to the camera and the photomultiplier tube, thereby realizing the data acquisition of ion imaging and fluorescence counting.

9. The system for detecting weak signals and harmonics based on compression enhancement random resonance according to any one of claims 1 to 8, characterized in that, The drive signal, compression signal, and signal under test are generated by two signal sources. One of the signal sources is a dual-channel signal source with phase synchronization between the two channels, which is used to generate the drive signal and compression signal respectively. The other signal source is a single-channel signal source used to generate the signal to be tested. Both signal sources are connected to the same reference signal.

10. A method for implementing the system for detecting weak signals and harmonics based on compression enhancement stochastic resonance as described in claim 9, characterized in that, Includes the following steps: Step 1: The calcium atom furnace is heated by electric current, causing calcium atoms to vaporize and be ejected into the trapping region; the ionization laser strips the outer electrons of the calcium atoms ejected from the calcium atom furnace to generate calcium ions, which are then trapped in the three-dimensional trapping potential field generated by the surface electrode ion trap. Subsequently, the ions are Doppler cooled by a cooling laser to form calcium ions that can be stably trapped. Finally, the ions are pushed away from the center of the surface electrode ion trap to the edge of the surface electrode ion trap by a DC trapping field, trapping the ions in a region with strong nonlinear potential field, and maximizing the width of the hysteresis loop in the stable trapping region. Step 2: Input the driving signal with the same frequency as the ion vibration onto the ion through the electrode of the surface electrode ion trap, drive the ion to undergo forced vibration and become a coherent vibration state, adjust the driving signal intensity to make the ion in a nonlinear state, and obtain the hysteresis loop of ion fluorescence count as a function of driving intensity by scanning the amplitude of the driving signal. Step 3: Set the modulation type of the driving signal channel to external modulation and the modulation type to amplitude modulation. Use the signal under test to perform amplitude modulation on the driving signal, and finally input it into the surface electrode ion trap together with the driving signal. Step 4: Collect fluorescence signals using a fluorescence acquisition system, analyze and extract the information of the signal to be measured, and calculate the signal-to-noise ratio of the signal to be measured and its harmonics; Step 5: Input the compressed signal into the surface electrode ion trap, and acquire the test signal information after the compressed signal is input through the fluorescence acquisition system; Step 6: Change the strength of the compressed signal to obtain the signal-to-noise ratio relationship between the output signal-to-noise ratio and the strength of the compressed signal; Step 7: Under optimal compression strength, perform step 4 to obtain the final frequency and amplitude of the weak signal to be measured.

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