CN109301687B - Laser automatic frequency stabilization system based on intelligent saturated absorption spectrum identification technology - Google Patents
Laser automatic frequency stabilization system based on intelligent saturated absorption spectrum identification technology Download PDFInfo
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01S—DEVICES USING THE PROCESS OF LIGHT AMPLIFICATION BY STIMULATED EMISSION OF RADIATION [LASER] TO AMPLIFY OR GENERATE LIGHT; DEVICES USING STIMULATED EMISSION OF ELECTROMAGNETIC RADIATION IN WAVE RANGES OTHER THAN OPTICAL
- H01S3/00—Lasers, i.e. devices using stimulated emission of electromagnetic radiation in the infrared, visible or ultraviolet wave range
- H01S3/10—Controlling the intensity, frequency, phase, polarisation or direction of the emitted radiation, e.g. switching, gating, modulating or demodulating
- H01S3/13—Stabilisation of laser output parameters, e.g. frequency or amplitude
- H01S3/136—Stabilisation of laser output parameters, e.g. frequency or amplitude by controlling devices placed within the cavity
- H01S3/137—Stabilisation of laser output parameters, e.g. frequency or amplitude by controlling devices placed within the cavity for stabilising of frequency
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01S—DEVICES USING THE PROCESS OF LIGHT AMPLIFICATION BY STIMULATED EMISSION OF RADIATION [LASER] TO AMPLIFY OR GENERATE LIGHT; DEVICES USING STIMULATED EMISSION OF ELECTROMAGNETIC RADIATION IN WAVE RANGES OTHER THAN OPTICAL
- H01S3/00—Lasers, i.e. devices using stimulated emission of electromagnetic radiation in the infrared, visible or ultraviolet wave range
- H01S3/10—Controlling the intensity, frequency, phase, polarisation or direction of the emitted radiation, e.g. switching, gating, modulating or demodulating
- H01S3/11—Mode locking; Q-switching; Other giant-pulse techniques, e.g. cavity dumping
- H01S3/1106—Mode locking
- H01S3/1112—Passive mode locking
- H01S3/1115—Passive mode locking using intracavity saturable absorbers
Abstract
The invention provides a laser automatic frequency stabilization system based on a saturated absorption spectrum intelligent identification technology, which comprises a laser closed-loop locking circuit and an automatic relocking circuit. The closed-loop locking loop consists of an atomic absorption gas chamber, a frequency discriminator based on a saturated absorption spectrum and a feedback controller, and realizes the closed-loop locking of the laser frequency; the automatic relocking loop combines a mode recognition technology in artificial intelligence with a classical photoelectric technology, so that the working state of the laser can be accurately and automatically tuned, and a locking point in a saturated absorption spectrum can be searched. When the laser frequency is in a locking state, the laser closed-loop locking circuit keeps working to realize the locking of the laser frequency; when the laser frequency is in the unlocked state, the relock loop relocks the laser frequency through a series of automated operations. The one-key automatic locking and the automatic relocking after the unlocking of the laser frequency can be realized, and the method has the characteristics of strong function, high intelligent degree, strong robustness and wide applicability. The invention is applied to the field of laser frequency stabilization.
Description
Technical Field
The invention relates to the field of laser frequency stabilization, in particular to an automatic laser frequency stabilization system based on a saturated absorption spectrum intelligent identification technology.
Background
The birth of the laser promotes a series of scientific and technological progress. In order to obtain laser meeting the requirements, that is, the line width of the laser is required to be narrow, and the frequency stability is required to be high, researchers research a laser closed-loop frequency stabilization system. The typical laser closed loop frequency stabilization system consists of three parts, namely a reference frequency, a frequency discriminator and a feedback controller. Reference frequencies that are widely used are the transition frequencies of atoms or molecules and the characteristic frequencies of the optical resonator. The most important difference is the difference in the frequency discrimination method. The transition frequency of atomic molecules is used as a reference frequency, a frequency discrimination signal is often obtained from an absorption spectrum or a dispersion spectrum of the atomic molecules, and researchers design a plurality of frequency discrimination methods and frequency stabilization technologies thereof, such as a modulation spectrum frequency stabilization technology, a Modulation Transfer Spectrum (MTS) frequency stabilization technology, a bias spectrum frequency stabilization technology, a magnetic dichroism frequency stabilization technology, and the like. The transmission and reflection characteristics of a high Q F-P cavity have similar characteristics to atomic absorption lines, with extremely narrow line widths, and a typical frequency stabilization technique based on a F-P cavity is a PDH (Pound-Drever-Hall) frequency stabilization technique.
The laser closed-loop frequency stabilization technology has the outstanding results after years of development and is widely applied to many research fields, but the technology has obvious defects, and mainly reflects the instability of a laser frequency stabilization system, namely the unlocking phenomenon is easy to occur. This is because the effective frequency locking range of the above-mentioned laser closed-loop frequency stabilization technique is usually narrow, and when the laser system suffers inevitable interference, the laser frequency jumps out of the effective frequency locking range and causes lock release. The phenomenon seriously limits the application scenes of the laser closed-loop frequency stabilization system, such as long-time, field complex environment, unattended operation, satellite-borne experiments and the like.
Disclosure of Invention
Aiming at the problem of unlocking phenomenon of a laser closed-loop frequency stabilization system in the prior art, the invention aims to provide a laser automatic frequency stabilization system based on a saturated absorption spectrum intelligent identification technology, which can realize automatic locking of laser frequency and automatic relocking after unlocking and has the characteristics of intelligence, strong function, strong robustness and wide applicability.
In order to achieve the purpose, an automatic frequency stabilization system is constructed on the basis of a laser closed-loop frequency stabilization system, a mode identification technology in artificial intelligence is combined with a classical photoelectric technology, a saturated absorption spectrum intelligent identification technology is designed on the basis of a support vector machine, the output mode and the working state of a laser can be accurately and automatically tuned, a locking point in a saturated absorption spectrum is searched, and automatic frequency locking and automatic relocking after unlocking of the laser are achieved. The specific scheme is as follows:
referring to fig. 1, an automatic laser frequency stabilization method based on the intelligent saturated absorption spectrum identification technology is a dual-loop control structure, and the working mechanism thereof is
The frequency locking state monitor monitors the working state of the frequency stabilization system in real time:
if the laser frequency is in a lockable state, the laser closed-loop locking loop keeps working, so that the emission frequency of the laser is locked at a target frequency value;
if the laser frequency is in the unlocking state, an automatic relocking loop is started, and the laser is adjusted to a good single-mode working state according to the intelligent saturated absorption spectrum identification technology, namely the laser has a wide mode-hopping-free tuning range. And identifying all lockable points in the saturated absorption spectrum, namely absorption peaks corresponding to hyperfine transition frequencies of atoms, and determining target locking points in all lockable points according to target frequency values. And then, Tuning the laser frequency to a preset effective frequency locking Range according to the target locking point and reactivating a laser closed loop locking circuit, namely realizing the relocking after the laser frequency is unlocked, wherein the good single-mode output state, namely the laser has a Wide mode-hopping Free Tuning Range (WMFTR) state.
Through the above mechanism, the laser frequency is always in an automatic cycle of "lock, relock after loss of lock, lock …" in the automatic frequency stabilization system.
As a further improvement of the above technical solution, the laser closed-loop locking circuit keeps working, and the process of locking the laser frequency at the target frequency value specifically includes:
a1, acquiring a saturated absorption signal and a frequency discrimination signal of the laser in the current state in real time;
a2, calculating the control quantity of the laser according to the frequency error by a feedback control algorithm;
and A3, performing feedback correction on the output frequency of the laser according to the control quantity.
As a further improvement of the above technical solution, the relock loop specifically includes:
b1, automatically adjusting the drive current of the laser to change the output mode of the laser, so that the frequency range of the output mode of the laser comprises the laser frequency to be locked;
b2, automatically adjusting the control parameters of the laser to adjust the laser to WMFTR state, it can be determined whether the laser is in WMFTR state by Saturated Absorption Spectrum (SAS). Specifically, the process is automated and intelligentized based on an intelligent identification technology of a saturated absorption spectrum, the intelligent identification technology of the saturated absorption spectrum divides the saturated absorption spectrum into two types by designing an intelligent classifier, respectively represents whether a laser is in a WMFTR state, and finally adjusts the laser to be in the WMFTR state represented by a standard saturated absorption spectrum;
b3, searching and locating all lockable points in the standard saturated absorption spectrum, namely locating an absorption peak corresponding to each hyperfine transition frequency in the saturated absorption spectrum, and scaling the laser frequency to an effective frequency locking range corresponding to the target lock point based on the absorption peak.
As a further improvement of the above technical solution, in step B2, the intelligent identification technology of the saturated absorption spectrum includes offline processing and real-time processing, and specifically includes:
b21, in the off-line processing, collecting a plurality of saturated absorption spectrums as samples under various conditions, and marking the working state of the laser corresponding to each sample to form a training sample set;
b23, extracting a feature vector from each saturated absorption spectrum sample according to a feature extraction algorithm to form a feature vector training set;
b24, constructing a classifier, training the classifier by using a feature vector training set, and carrying out error test on the classification result of the sample and the labeled true value so as to optimize the parameters of the classifier;
and B25, acquiring a saturated absorption spectrum signal in real time in real-time processing, extracting a feature vector according to the feature extraction algorithm same as that in the step B23, classifying the real-time saturated absorption spectrum by using the classifier optimized in the step B24, and determining whether the laser works in a WMFTR state or not according to a classification result.
As a further improvement of the above technical solution, in step B23, the extracting a feature vector from each saturated absorption spectrum sample according to a feature extraction algorithm specifically includes:
b231, extracting fragments with different scales from a standard saturated absorption spectrum (the laser is in a WMFTR state) to be used as a template;
b232, calculating a cross-correlation sequence of each template and the saturated absorption spectrum to be classified, and extracting maximum cross-correlation information from the cross-correlation sequence, namely a maximum value and a corresponding position in the sequence;
b233, the saturated absorption spectrum to be classified and the cross-correlation information of the absorption spectrum and the multi-scale template form the characteristic vector of the saturated absorption spectrum sample.
As a further improvement of the above technical solution, in step B24, the classifier is a support vector machine.
In order to realize the content of the invention, the invention provides an implementation scheme and a device of a laser automatic frequency stabilization system based on a saturated absorption spectrum intelligent identification technology, which comprise a laser, a laser driver, a main processor, a feedback controller, a frequency discriminator and a low-precision wavelength meter. The laser driver is used for controlling and driving the laser, the main processor is used for collecting signals, analyzing the working state of the system and controlling the working process of the system, the frequency discriminator is used for obtaining saturation absorption signals and frequency discrimination signals of atoms, the low-precision wavelength is used for roughly measuring the output frequency of the laser, and the feedback controller is used for carrying out feedback correction on the output frequency of the laser.
As a further improvement of the technical scheme, the program on the main processor comprises a frequency locking state discrimination module, a laser output mode selection module, a real-time SAS intelligent classifier module, an SAS locking point search module and a laser control module.
The invention has the beneficial technical effects that:
the invention discloses an intelligent laser automatic frequency stabilizing system with a double-loop control structure, which comprises a closed-loop locking loop and a one-key automatic relocking loop. The system has powerful functions, and can realize automatic locking of laser frequency and automatic relocking after unlocking through a complete automatic process no matter what state the laser is in. The system innovatively combines a mode recognition technology in artificial intelligence with a typical photoelectric technology, and an intelligent recognition technology based on a saturated absorption spectrum can more accurately and quickly judge and adjust the working state of a laser and search a target locking point, so that an intelligent solution is provided for realizing an automatic frequency stabilization system of the laser. The system can be widely applied to the general application of the automatic frequency stabilization system, and only corresponding modules need to be replaced for different experimental environments and system configurations. Therefore, the system has the characteristics of intellectualization, strong function, strong robustness and wide applicability.
Drawings
Fig. 1 is a schematic diagram of an intelligent laser automatic frequency stabilization system based on a double-loop control structure.
Fig. 2 is a general system layout diagram in an embodiment of the present invention.
Fig. 3 is a schematic diagram of the MTS discriminator in an embodiment of the present invention.
FIG. 4 is a functional block diagram of a method for SAS intelligent identification based on a support vector machine in a specific embodiment of the present invention.
Fig. 5 is a template diagram of feature extraction in an embodiment of the invention.
FIG. 6 shows the result of the training of the SAS intelligent identification technique based on the support vector machine in an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present disclosure more apparent, the present invention is further described in detail below with reference to specific embodiments and the accompanying drawings. It should be noted that, in the drawings or the description, the undescribed contents and parts of english are abbreviated as those well known to those skilled in the art. Some specific parameters given in the present embodiment are only exemplary, and the values may be changed to appropriate values accordingly in different real-time manners.
Referring to fig. 2, in this embodiment, the laser is a 780nm external cavity semiconductor laser, and the laser output from the laser is divided into three beams by two beam splitters, wherein one high-power beam splitter is used as the output of the frequency stabilization system, and two low-power beam splitters are respectively used for the frequency discriminator and the wavelength meter. A wavelength meter (with the precision of 1GHz) roughly measures the laser frequency (Freq) for judging the output mode of the laser; referring to fig. 3, the beam splitting light entering the MTS discriminator is divided into probe light and pump light, and the pump light and probe light modulated by EOM are reversely overlapped in the rubidium (Rb) bubble to undergo modulation transfer. The detection light absorbed by the Rb bubbles is converted into an electrical signal, i.e., a Saturation Absorption Signal (SAS), by a Photodetector (PD), and the saturation absorption signal is demodulated to obtain a Frequency Discrimination Signal (FDS). Freq signals are directly collected to a main processor; the SAS and the FDS are collected by the feedback controller and then transmitted to the main processor.
Referring to fig. 2, the system has a workflow: the frequency locking state monitor judges the locking state of the laser frequency, if the laser is in the locking state, a closed loop A (Cycle A) keeps working, namely the feedback controller calculates a control quantity according to a frequency error signal and performs feedback control on the driving current of the laser and the piezoelectric ceramic (PZT) voltage by two channels; if the laser is in the unlocking state, a re-locking loop (Cycle B) is started, the laser frequency is re-tuned back to the preset effective frequency locking range through a series of automatic control processes, and the Cycle A is activated again to re-lock the laser frequency.
The process of the relocking loop is described in detail below:
b1 for a 780nm external cavity semiconductor laser, there are many different output modes, each mode corresponding to a different output frequency range. For the present embodiment to lock the laser frequency to a certain hyperfine transition frequency on the Rb-D2 transition line, the laser frequency needs to be adjusted to the corresponding mode first, and its frequency range is about 384225< Freq <384238 GHz. The automation of this process is judged by sequentially adjusting the drive current to the laser and by roughly measuring the laser frequency with a low precision wavemeter.
B2 after B1, the current and PZT voltage of the laser need to be adjusted in order to put the laser in proper working condition, which refers to a Wide mode-hopping-free tuning Range (WMFTR) condition for external cavity semiconductor lasers. An effective method for judging whether the external cavity semiconductor laser is in the WMFTR state is to analyze the saturation absorption spectrum SAS thereof, because when the laser is in the WMFTR state, the obtained saturation absorption spectrum has a consistent characteristic, called a standard saturation absorption spectrum, otherwise, the SAS is more or less different from the standard saturation absorption spectrum. Therefore, whether the laser operates in WMFTR can be determined by determining whether the SAS has characteristics consistent with the standard SAS.
Referring to fig. 4, the present embodiment discloses an SAS intelligent recognition technology based on a Support Vector Machine (SVM).
Referring to fig. 5, in the present embodiment, the similarity between the standard SAS and the SAS to be classified is evaluated by the normalized cross-correlation algorithm to extract a partial feature value. The cross-correlation algorithm has the following formula
In the formula (I), the compound is shown in the specification,
Corrxy(m) is the SAS signal (S) to be classifiedx) And standard SAS signal (S)std) Normalized cross-correlation values therebetween.
First, to make the feature extraction process more comprehensive, Corr at different scales needs to be calculatedxy(m) value, this embodiment extracts 5 fragments from a standard SAS signal as templates, T in FIG. 5jAs shown, Rb-D2 saturated absorption spectrum and hyperfine level absorption spectrum of each ground state (F ═ x → F' ═? for groups of hyperfine absorption peaks formed by different x) are respectively correspondedj(m) (j ═ 1,2L 5), its maximum similarity and its corresponding position in the SAS sample sequence, i.e., are calculated
Sj＝max(Corrj(m))
Pj＝{m|Corrj(m)＝Sj}
Further, it is noted that in the Rb-D2 saturable absorption spectrum, at far detuned atomic transition frequencies, atoms hardly absorb the laser lightIt shows a flat line shape in the saturated absorption spectrum, as shown by R in FIG. 5jShown, and therefore the flatness F of the area needs to be calculatedjTo reflect its characteristics. It is worth pointing out that, because the saturation absorption of atoms to laser light changes to some extent under different conditions, such as light intensity fluctuation, alignment of pump light and probe light, temperature change of rubidium bubbles, and the like, in order to accurately evaluate the specificity of the standard SAS, M standard SAS under different conditions are collected in the present embodiment. Finally, M feature vectors FV are extracted from a SAS signal to be classified by the algorithm described abovej(j ═ 1,2,. M), and
FV＝(S1,S2,S3,S4,S5,D1,D2,D3,D4,F1,F2,F3,F4)T
in the formula, Dj＝Pj+1-P1For determining TjRelative position in the SAS sample sequence.
In the pattern recognition technology, a Support Vector Machine (SVM) is a classifier with excellent performance, and the principle thereof is to find an optimal hyperplane in a feature Vector space and separate feature vectors of different classes on two sides of the hyperplane, thereby achieving the purpose of classification. When the SVM is applied, the SVM can be simplified into the following formula
In the formula, alphai,K(·),siAnd b is a parameter of a support vector machine, which can be determined in the process of training the SVM, wherein x is a feature vector, and C (x) is a function interval between the feature vector and a hyperplane, which means that the larger the absolute value of the function interval is, the farther the function interval is from the hyperplane, and the more remarkable the classification effect is.
Referring to fig. 4, the present embodiment designs a 2-level SVM (2L-SVM) classifier in which SVM is the first-level SVMjRespectively to FVjClassifying to obtain a result Cj(FVj) Composing new feature vectors, i.e.
FVsum＝(C1,C2...,CM)T
In this experiment M ═ 4. In the second-stage SVM, the SVMsumFor FVsumClassifying to obtain the final classification result Csum(FVsum)。
In the experiment of this embodiment, several SAS signals were collected under various conditions to form a training sample set and labeled accordingly, that is, the SAS signals were collected under various conditions
D＝{(xi,yi),yi∈{-1,+1}}
The capacity of the sample set D exceeds 700, and the sample set D is acquired when the laser is in different working states.
The result of training the 2L-SVM through the sample set is shown in fig. 6, where the point marked by a blue circle is a-1 sample, the point marked by a green plus sign is a +1 sample, C ═ 1 and C ═ 1 are classification critical lines of the SVM, respectively, and the points on the critical lines are so-called support vectors. In fig. 6, only two-1 samples are wrongly classified within the two critical lines, because it is practically difficult to separate all feature vectors exactly at both sides of the hyperplane, and thus, in theory, when a certain constraint is satisfied, a partially wrong classification result is allowed to exist in the training process of the SVM. In this embodiment, in order to strictly control the false positive rate, the result of the set 2L-SVM classifier is determined as follows
y＝sgn(Csum(FVsum)-1)
The specific embodiment performs real-time test on the 2L-SVM classifier, and shows a good effect consistent with the training process. Therefore, whether the SAS belongs to a standard SAS signal or not can be accurately identified through the SAS intelligent identification method based on SVM design, and whether the laser works in WMFTR state or not is judged.
B3: after the laser is adjusted to the WMFTR state through the intelligent identification SAS signal, the laser frequency needs to be scaled to a set effective frequency locking range, i.e., an absorption peak corresponding to a certain hyperfine transition. Firstly, in the process of feature extraction, canOver-feature element PjTo locate T in saturated absorption spectrumjThe position of the area is calculated, the sweep center and the sweep amplitude of the PZT voltage are calculated, and the SAS is scaled to T containing the frequency to be lockedjAnd (4) a region. Subsequently, by detecting TjThe presence of hyperfine absorption peaks in the regions and sorting them may determine the position of each hyperfine absorption peak, i.e. the position of the lockable point, i.e. the target lock point in the saturated absorption spectrum, based on feature extraction. And then, calculating the sweep frequency center and the sweep frequency amplitude of the PZT voltage again to zoom the laser frequency to be within an effective frequency locking range corresponding to the preset locking point. At this point, the laser frequency can be relocked to the target reference frequency by turning off the frequency sweep and activating the closed loop lock loop.
The foregoing description of the preferred embodiments of the present invention has been included to describe the features of the invention in detail, and is not intended to limit the inventive concepts to the particular forms of the embodiments described, as other modifications and variations within the spirit of the inventive concepts will be protected by this patent. The subject matter of the present disclosure is defined by the claims, not by the detailed description of the embodiments.
Claims (4)
1. A laser automatic frequency stabilization method based on a saturated absorption spectrum intelligent identification technology is characterized in that a double-loop control structure is adopted:
the frequency locking state monitor monitors the working state of the frequency stabilization system in real time:
if the laser frequency is in a locking state, the laser closed-loop locking loop keeps working, so that the laser frequency is locked at a target frequency value;
if the laser frequency is in the unlocking state, starting an automatic re-locking loop, re-adjusting the laser frequency to an effective frequency locking range through three steps of selecting a laser output mode, intelligently identifying and classifying and adjusting the working state of the laser based on a saturated absorption spectrum and determining a target locking point in the saturated absorption spectrum, and activating a closed-loop locking loop to realize the re-locking of the laser frequency;
the operation of the laser frequency in the unlocked state specifically includes:
b1, automatically adjusting the output mode of the laser to make the frequency range of the output mode contain the target frequency value;
b2, automatically adjusting the laser to a good single-mode output state, wherein the good single-mode output state represents that the laser has a wider mode-hopping-free tuning range state, the current laser saturation absorption spectrum is classified by an intelligent identification technology of the saturation absorption spectrum, and the working state of the laser is adjusted and judged according to the classification result, so that the laser works in the wider mode-hopping-free tuning range state represented by a standard saturation absorption spectrum;
b3, searching and positioning a target lockable point in the standard saturated absorption spectrum, and zooming the laser frequency to an effective frequency locking range corresponding to the target lockable point;
in step B2, the intelligent identification technology of the saturated absorption spectrum includes offline processing and real-time processing, and specifically includes:
b21, in the off-line processing, collecting a plurality of saturated absorption spectrums as samples under various conditions, and marking the working state of the laser corresponding to each sample to form a training sample set;
b23, extracting a feature vector from each saturated absorption spectrum sample according to a feature extraction algorithm to form a feature vector training set;
b24, constructing a classifier, training the classifier by using a feature vector training set, and carrying out error test on the classification result of the sample and the labeled true value so as to optimize the parameters of the classifier;
b25, in the real-time processing, acquiring the saturated absorption spectrum signal of the current laser state in real time, extracting the feature vector according to the feature extraction algorithm same as that in the step B23, classifying the real-time saturated absorption spectrum by using the classifier optimized in the step B24, and determining whether the laser works in a wider mode-hop-free tuning range state at the moment according to the classification result.
2. The laser automatic frequency stabilization method based on the intelligent saturated absorption spectrum identification technology as claimed in claim 1, wherein in step B23, the extracting feature vectors from each saturated absorption spectrum sample according to a feature extraction algorithm specifically includes:
b231, extracting fragments with different scales from a standard saturated absorption spectrum as a template, wherein the standard saturated absorption spectrum is the saturated absorption spectrum of the laser in a wider mode-hopping-free tuning range state;
b232, calculating a cross-correlation sequence of each template and the saturated absorption spectrum to be classified, and extracting maximum cross-correlation information from the cross-correlation sequence, namely a maximum value and a corresponding position in the sequence;
and B233, the maximum cross-correlation information of the saturated absorption spectrum to be classified and the multi-scale template forms a characteristic vector of the saturated absorption spectrum.
3. The laser automatic frequency stabilization method based on the intelligent saturated absorption spectrum identification technology of claim 1, wherein in the step B24, the classifier is a support vector machine.
4. A laser automatic frequency stabilization system based on a saturated absorption spectrum intelligent identification technology is characterized by comprising a laser, a laser driver, a main processor, a feedback controller, a frequency discriminator and a low-precision wavelength meter;
the main processor is used for acquiring signals, analyzing the working state of the system and controlling the working process of the system, the frequency discriminator is used for acquiring atomic saturation absorption signals and frequency discrimination signals, the low-precision wavelength is used for roughly measuring the output frequency of the laser, and the feedback controller is a PID (proportion integration differentiation) controller and is used for carrying out feedback correction on the output frequency of the laser;
the program on the main processor comprises a frequency locking state discrimination module, a laser output mode selection module, a real-time saturated absorption spectrum intelligent classifier module, a saturated absorption spectrum locking point searching module and a laser control module;
the frequency discriminator and the feedback controller form a laser closed-loop locking loop according to any one of claims 1 to 3;
the frequency discriminator, the main processor, the laser driver and the wavelength meter form the laser automatic relock loop according to any one of claims 1 to 3.
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