CN103928065B - A kind of reactor inner part critical heat flux method of real-time based on sonic sensor - Google Patents

Abstract

A kind of reactor inner part critical heat flux method of real-time based on sonic sensor, for in fusion reactor heap towards plasma source components the first wall, fission-type reactor reactor fuel assembly unusual service condition occurs time the real-time monitoring of critical heat flux (Critical heat flux, CHF) event；Due to the fact that and use sound wave to monitor the CHF event that Gao Rehe parts produce in real time, there is the significant advantages such as real-time is good, monitoring range is big, precision is high, overcome and when using thermocouple monitoring CHF event, need the restriction that measuring point quantity is many, data are delayed in acquisition, be only capable of measuring limited portions, it also avoid the defects such as Temperature Distribution that slin emissivity is low, change parasitic reflection big, high is caused when using infrared detection CHF event is uncertain, solve the difficult problem that reactor inner part critical heat flux is monitored in real time.

Description

A kind of reactor inner part critical heat flux method of real-time based on sonic sensor

Technical field

The present invention relates to a kind of reactor inner part critical heat flux method of real-time based on sonic sensor, belong to advanced Nuclear reactor thermohydraulics field.

Background technology

The thermonuclear reaction of the advanced reactor such as fusion reactor, fission-type reactor produces high nuclear heat power density, the such as fusion of its incore component Towards plasma sheath, the first wall of divertor in heap heap, fission-type reactor reactor fuel assembly needs the cold of definite quality flow rate But nuclear heat is discharged in agent flowing, cools down incore component.When there is the most expected operating mode in reactor operation, as fusion reactor etc. from Daughter ruptures, fission-type reactor overpower etc., beyond under the very high power density hot-fluid effect running license, and covering, divertor First wall, reactor fuel assembly coolant flow passages, will appear from the critical heat flux (Critical heat flux, CHF) during unusual service condition Event, high power density hot-fluid can make parts wall temperature raise rapidly (such as fusion reactor incore component covering, divertor the first wall, Fission-type reactor fuel rod clad), heat transfer deterioration, causes defluidization, loses the accidents such as cold, cut, if monitoring not in time and having taked The counter-measure of effect, even causes the catastrophic failures such as core meltdown, it will cause the most serious consequence.

Existing reactor generally uses thermoelectricity occasionally thermal infrared imager to monitor the parts being likely to occur critical heat flux.Use thermoelectricity During even monitoring CHF event, the thermal time constant having due to incore component causes acquisition temperature data delayed, and parts are numerous There is measuring point quantity many, be only capable of measuring the defects such as local limited portions.When using thermal infrared imager monitoring CHF event, due to The parts surface emissivity detected is low, range of temperature big, and heat radiation height, parasitic reflection etc. cause Temperature Distribution the most true Qualitative greatly, cause monitoring accuracy to decline.For solving the problem of the reactor real-time accurate measurements of inner part critical heat flux, this Invention proposes to use sonic sensor to monitor the CHF event that high thermal force parts produce in real time.The method have real-time good, The significant advantages such as monitoring range is big, precision is high, occur monitoring CHF event in real time, and take the measure that successfully manages to have weight Act on.

Summary of the invention

Present invention solves the technical problem that and be: overcome the deficiencies in the prior art, it is provided that a kind of reactor based on sonic sensor Incore component critical heat flux method of real-time, in fusion reactor heap towards plasma source components the first wall, fission-type reactor heap The real-time of critical heat flux event when unusual service condition occurs in core fuel assembly is monitored；This method solve employing thermocouple monitoring Need the restriction that measuring point quantity is many, data are delayed, be only capable of measuring limited part during CHF event, it also avoid employing red During outer detection CHF event, puberty rate in surface is low and changes the technology such as Temperature Distribution that parasitic reflection big, high caused is uncertain and lacks Fall into.

The technical solution used in the present invention is: a kind of reactor inner part critical heat flux based on sonic sensor is monitored in real time Method, Main Basis incore component produces the sonic detection principle of critical heat flux, uses sound wave monitoring critical heat flux experimental system Realize.Described sound wave monitoring critical heat flux experimental system includes turbine flowmeter 1, heating system 2, experimental section the 3, first sound Wave sensor 4, needle-valve 5, rising tone wave sensor 6, eddy-current flowmeter 7, diaphragm valve 8, data acquisition unit 9, power Spectrometer 10, computer 11.Cooling pipe equipped with turbine flowmeter 1 is connected with experimental section 3, the outflow end of experimental section 3 Pipe installing the first sonic sensor 4 and needle-valve 5, a flow of cooling water passage in building block；Another is with experimental section 3 Diaphragm valve 8 and eddy-current flowmeter 7, the cooling of analogy incore component many groups PARALLEL FLOW are installed on parallel cooling water pipeline One of aquaporin, the end that confluxes of two pipelines installs rising tone wave sensor 6；Data acquisition unit 9 is connected to by data wire First sonic sensor 4 and rising tone wave sensor 6, data acquisition unit 9 outfan one tunnel is connected with Power spectrum 10, Another road is connected with computer 11.

Implement step as follows:

The flow of S1: turbine flowmeter 1 experiments of measuring section 3 press water, needle-valve 5 regulates the flow of experimental section 3 in-channel water. First sonic sensor 4 obtains the turbulent flow of flow of cooling water, water velocity change, drives pump, effusion meter, valve and pipeline Turning reasons for its use noise signal, the parasitic disturbances signal that high power density hot-fluid heater block structure produces, high power is close Degree hot-fluid Heating Experiment section 3 makes the acoustic signals that manifold pressure blister nuclear boiling produces, and these signal frequencies are all 0～20KHz Within the scope of；

S2: diaphragm valve 8 regulation enters the ratio of two groups of parallel channels press waters, and eddy-current flowmeter 7 is measured flat with experimental section 3 The flow of row of channels cooling water, rising tone wave sensor 6 is installed on the end that confluxes of two groups of cooling water flow conduits, obtains acoustic signals；

S3: data acquisition unit 9 Real-time Collection the first sonic sensor 4 and rising tone wave sensor 6 signal, these signals Frequency all within the scope of 0～20KHz, row number signal processing of going forward side by side.Digital signal processing is: a road signal warp Fast Fourier transform (FFT), is weighted selecting by adding Hanning window, processes in conjunction with Welch time average method, send It is analyzed to Power spectrum 10, it is thus achieved that the power spectral density (PSD) of signal, monitoring background noise and acoustic wave energy signal； Another road is the time-domain signal through FFT, forms pending digital signal by 52KHz frequency sampling.Due to noise The acoustic signals frequency that when signal and CHF, nucleateboiling produces is all within the scope of 0～20KHz, and nucleateboiling during CHF The acoustic signals frequency produced is 200～800Hz, and the band filter through 200～333Hz selects, and filters off other frequency After background noise, deliver to computer 11.Computer 11, by inverse fast fourier transform (IFFT), is transformed into frequency-region signal, Carry out root mean square calculation (RMS) again, it is thus achieved that acoustic wave energy signal；Auxiliary arranges the heating of high power density hot-fluid and produces complex boiling Sound wave door signal when rising, when CHF event occurs, the heating of high power density hot-fluid makes experimental section 3 inwall nucleateboiling institute When the acoustic wave energy produced exceedes this door signal, can determine that CHF event occurs, thus monitoring experimental section 3 appearance in real time CHF event.

Carry out Digital Signal Processing by computer 11, analyze acoustic power spectrum density and acoustic wave energy signal, and be aided with critical Hot-fluid door signal, there is critical heat flux (CHF) event during unusual service condition in real-time monitoring experimental section 3.

In described step S3, it is weighted selecting by Hanning window, is that the first sonic sensor 4 and the second sound wave are sensed The long discrete series signal that device 6 obtains becomes limited length sequence signal, uses DSP program MATLAB file Middle hanning program is realized by computer.

In described step S3, when the process of Welch time average method is to use Hanning window to sequence signal segmentation, it is allowed to every One section of window has the overlapping of part, and in utilization DSP program MATLAB file, pwelch.m program is by computer Realize, the relatively big produced spectrum distortion of sidelobe when rectangular window selects can be improved.By to a series of conversion process of signal with Calculate, it is thus achieved that power spectral density distribution (PSD) of signal.

Present invention advantage compared with prior art is: use sound wave to monitor the CHF event that Gao Rehe parts produce in real time, There is the significant advantages such as real-time is good, monitoring range is big, precision is high, needs when overcoming employing thermocouple monitoring CHF event Measuring point quantity is many, data are delayed, be only capable of measuring the restriction of limited portions, table when it also avoid employing infrared detection CHF event Surface launching rate is low and changes the defects such as Temperature Distribution that parasitic reflection big, high caused is uncertain, solves inside reactor The difficult problem that part critical heat flux is monitored in real time.

Accompanying drawing explanation

Fig. 1 is the sound wave monitoring critical heat flux experimental system figure used in the present invention；

Fig. 2 is the sonic detection schematic diagram that incore component produces critical heat flux.

Detailed description of the invention

Provide the detailed description of the invention of the present invention below in conjunction with the accompanying drawings, to describe technical scheme in detail.

The specific embodiment of the invention is to use the sound wave monitoring critical heat flux experimental system shown in accompanying drawing 1.

The present invention use sound wave monitoring critical heat flux experimental system include turbine flowmeter 1, heating system 2, experimental section 3, First sonic sensor 4, needle-valve 5, rising tone wave sensor 6, eddy-current flowmeter 7, diaphragm valve 8, data acquisition unit 9, Power spectrum 10, computer 11.Cooling water pipeline equipped with turbine flowmeter 1 is connected with experimental section 3, experimental section 3 Outflow end Pipe installing the first sonic sensor 4 and needle-valve 5, a flow of cooling water passage in building block；Another is therewith Being provided with diaphragm valve 8 and eddy-current flowmeter 7 on parallel cooling water pipeline, the parallel cooling water of many groups of analogy incore component leads to One of road, the end that confluxes of two pipelines installs rising tone wave sensor 6；Data acquisition unit 9 is connected to first by data wire Sonic sensor 4 and rising tone wave sensor 6, data acquisition unit 9 outfan one tunnel is connected with Power spectrum 10, separately One tunnel is connected with computer 11.

A coolant flow passage in S1: turbine flowmeter 1, experimental section 3 and needle-valve 5 building block, analogy incore component One of the cooling-water duct that many groups are parallel (such as divertor target plate or fuel assembly cooling-water duct), wherein turbine flowmeter 1 is surveyed The flow of amount experimental section 3 press water, uses needle-valve 5 to regulate the flow of experimental section 3 passage.First sonic sensor 4 obtains The reasons for its use noise signals such as the change of the turbulent flow of flow of cooling water, water velocity, driving pump, effusion meter, valve and turning, The parasitic disturbances signal structurally produced during high power density hot-fluid heater block, high power density hot-fluid Heating Experiment section 3 Making the acoustic signals that inner-walls of duct press water nucleateboiling produces, the frequency of these signals is all within the scope of 0～20KHz；

Another parallel cooling-water duct in S2: diaphragm valve 8, eddy-current flowmeter 7 building block, many groups of analogy incore component One of parallel cooling-water duct (such as divertor target plate or fuel assembly cooling-water duct), wherein diaphragm valve 8 regulates entrance two The ratio of group parallel channels press water, eddy-current flowmeter 7 is measured and the flow of experimental section 3 parallel channels cooling water.The rising tone Wave sensor 6 is installed on two groups of cooling water flow conduits and confluxes end, obtains acoustic signals, by Digital Signal Processing, analyzes sound wave Power spectral density and acoustic wave energy signal, and it is aided with critical heat flux door signal, there is unusual service condition in monitoring experimental section 3 in real time Time critical heat flux (CHF) event；

S3: data acquisition unit 9 Real-time Collection the first sonic sensor 4 and rising tone wave sensor 6 signal, its frequency domain is believed Number frequency is within the scope of 0～20KHz.Signal processing is as follows: a road signal classics fast Fourier transform (FFT), It is weighted selecting by adding Hanning window, and combines the process of Welch time average method, deliver to Power spectrum 10 and be analyzed, Obtain the power spectral density (PSD) of signal, monitoring background noise and acoustic wave energy signal；Another road is when FFT Territory signal, forms pending digital signal by 52KHz frequency sampling.Owing to when noise signal and CHF, nucleateboiling produces Raw acoustic signals frequency is all within the scope of 0～20KHz, and the acoustic signals frequency that during CHF, nucleateboiling produces exists 200～800Hz, the band filter through 200～333Hz selects, and after filtering off the background noise of other frequency, delivers to calculate Machine 11.Computer 11, by inverse fast fourier transform (IFFT), is transformed into frequency-region signal, then carries out root mean square calculation (RMS), it is thus achieved that acoustic wave energy signal produced by nucleateboiling in experimental section 3；Auxiliary arranges the heating of high power density hot-fluid Sound wave door signal when producing nucleateboiling, when CHF event occurs, in high power density hot-fluid Heating Experiment section 3 makes wall The produced acoustic wave energy of nucleateboiling exceedes this door signal, can determine that CHF event occurs, thus monitoring experimental section 3 in real time The CHF event occurred.

In described step S1, produce the sonic detection schematic diagram of critical heat flux according to accompanying drawing 2 incore component, work as reactor operation When there is the most expected operating mode, (huge can flow (the every square metre of GJ magnitude) of such as Fusion Reactor Core Plasma disruption is in pole Divertor the first wall, fission-type reactor reactor core overpower operation etc. it is applied in the short time (millisecond yardstick)), permitted beyond running Can very high power density hot-fluid effect under, high power density nuclear heat heat flux distribution that experimental section 3 outer wall is born is uneven, from Entrance is to CHF event position occur, and it is straight that cooling water and wall heat exchange show as forced-convection heat transfer, nucleateboiling heat exchange respectively To developing into CHF event.Critical heat flux makes incore component runner wall inner cooling water Bubble fraction roll up, and wall conducts heat Deteriorate rapidly, wall burnout failure will be produced；

In described step S1, the sound wave that the change of the turbulent flow of flow of cooling water, water velocity produces, drive pump, flow agent, valve The reasons for its use noise signals such as door and turning, transmit in flow working medium water；High power density hot-fluid heater block structure is produced Raw parasitic disturbances signal, though this signal intensity relatively big in pipeline configuration transmission attenuation fast, but be prone to transmission to experiment First sonic sensor 4 of section 3 pipeline outflow ends, and then the acoustic wave energy signal that impact identification nucleateboiling produces.To installation In the rising tone wave sensor 6 of the end that confluxes, due to distance experimental section 3 farther out, parasitic disturbances signal transmission decay rapidly, to it Affect less.In the range of background above noise and interference signal frequency are almost distributed 0～2KHz, and high power density hot-fluid adds Hot experimental section 3 makes pressure blister nuclear boiling produces in wall frequency of sound wave mostly 200～800Hz, can use corresponding ripple The band filter of section filters off noise signal and interference signal, as used the band filter of 200～333Hz to select in experiment The acoustic signals that nucleateboiling produces, thus filter off noise signal and the interference signal of other frequency range；

In described step S3, the process to the acoustic signals gathered is to use classical fast fourier transform or inverse transformation, will letter Number be transformed to time-domain signal or frequency-region signal, use Hanning window to select during key area and be weighted processing, and with the Webster time Averaging method combines, and calculates the power spectral density distribution in 0～20KHz frequency range.

Concrete process is as follows:

(1) classical fast fourier transform is defined as (1) formula, and inverse fast fourier transform is defined as (2) formula, adopts respectively Realize by computer by fft and ifft program in DSP program MATLAB file.

$X\left(k\right)=\underset{n=01}{\overset{N-1}{\mathrm{\Σ}}}x\left(n\right)W_N^{\mathrm{nk}}k=\mathrm{0,1},...,N-1,W_N=e^{-j\frac{2\mathrm{\π}}{N}}---\left(1\right)$

$x\left(n\right)=\frac{1}{N}\underset{k=0}{\overset{N-1}{\mathrm{\Σ}}}X\left(k\right)W_N^{-\mathrm{nk}}n=\mathrm{0,1}...,N-1---\left(2\right)$

(2) Hanning window selects to be weighted during key area processing, and long discrete series signal is become limited length sequence signal, Its window function ω (n) can be expressed as (3) formula, use in DSP program MATLAB file hanning program by Computer realizes.

$\mathrm{\ω}\left(n\right)=0.5+0.5\cos \left(\frac{2\mathrm{\πn}}{N}\right),n=-\frac{N}{2},...,0,...,\frac{N}{2}---\left(3\right)$

(3) Welch time average method

Welch method is to x_NDuring (n) segmentation, each section of window can be allowed to have the overlapping of part, be designated as when using Hanning window d₂N (), can improve the relatively big produced spectrum distortion of rectangular window sidelobe, use DSP program MATLAB file Middle pwelch.m program is calculated by computer, and the power spectrum of each section is (4) formula.

${\hat{P}}_{\mathrm{PER}}^i=\frac{1}{\mathrm{MU}}{\left|\underset{n=0}{\overset{M-1}{\mathrm{\Σ}}}{x}_n^i\left(n\right)d_2\left(n\right)e^{-\mathrm{j\ωn}}\right|}^2---\left(4\right)$

M is every segment length, and U is normalization factor.

Non-elaborated part of the present invention belongs to technology as well known to those skilled in the art.

Although describe the specific implementation method of the present invention above, it will be appreciated by those of skill in the art that these are only Illustrate, on the premise of without departing substantially from the principle of the invention and realization, these embodiments can be made numerous variations or repair Changing, therefore, protection scope of the present invention is defined by the appended claims.

Claims (3)

1. a reactor inner part critical heat flux method of real-time based on sonic sensor, it is characterised in that: foundation Incore component produces the sonic detection principle of critical heat flux, uses sound wave monitoring critical heat flux experimental system to realize；Described sound wave Monitoring critical heat flux experimental system includes the first turbine flowmeter (1), heating system (2), experimental section (3), the first sound wave Sensor (4), needle-valve (5), rising tone wave sensor (6), the second eddy-current flowmeter (7), diaphragm valve (8), data Harvester (9), Power spectrum (10), computer (11)；Cooling pipe and reality equipped with the first turbine flowmeter (1) The section of testing (3) is connected, the outflow end Pipe installing the first sonic sensor (4) of experimental section (3) and needle-valve (5), composition A flow of cooling water passage in parts；On another cooling water pipeline paralleled with experimental section (3), diaphragm valve (8) is installed With the second eddy-current flowmeter (7), the cooling water pipeline paralleled with experimental section (3) is the cold of incore component many groups PARALLEL FLOW But one of aquaporin, the flow of cooling water passage of experimental section (3) and the remittance of cooling water pipeline paralleled with experimental section (3) Stream end installs rising tone wave sensor (6)；Data acquisition unit (9) is connected to the first sonic sensor (4) by data wire With rising tone wave sensor (6), data acquisition unit (9) outfan one tunnel is connected with Power spectrum (10), another road It is connected with computer (11)；

Implement step as follows:

The flow of the S1: the first turbine flowmeter (1) experiments of measuring section (3) press water, needle-valve (5) regulation experimental section (3) The flow of flow of cooling water in-channel water；First sonic sensor (4) obtains the turbulent flow of flow of cooling water, water velocity changes, Driving pump, first-class gauge, needle-valve and pipeline turning reasons for its use noise signal, high power density hot-fluid heater block is tied The parasitic disturbances signal that structure produces, high power density hot-fluid Heating Experiment section (3) makes inner-walls of duct press water nucleateboiling produce Acoustic signals, the frequency of these signals is all within the scope of 0～20KHz；

S2: diaphragm valve (8) regulation enters the flow of cooling water passage of experimental section and the cooling water pipe paralleled entering experimental section The ratio of road press water, the second eddy-current flowmeter (7) is measured the cooling water pipeline paralleled with experimental section (3) and is cooled down water Flow, rising tone wave sensor obtains acoustic signals；

S3: data acquisition unit (9) Real-time Collection the first sonic sensor (4) and rising tone wave sensor (6) signal, The frequency domain of these signals all within the scope of 0～20KHz, row number signal processing of going forward side by side；Digital signal processing is: one Road signal fast fourier transformed (FFT), is weighted selecting, in conjunction with Welch time average method by adding Hanning window Process, deliver to Power spectrum (10) and be analyzed, it is thus achieved that the power spectral density (PSD) of signal, monitor background noise harmony Wave energy signal；Another road is the time-domain signal through FFT, forms pending number by the sampling of 52KHz sample frequency Word signal；Owing to the acoustic signals frequency of nucleateboiling generation when noise signal and critical heat flux CHF is all 0～20KHz Within the scope of, and the acoustic signals frequency that during CHF, nucleateboiling produces is 200～800Hz, the band through 200～333Hz leads to Wave filter selects, and after filtering off the background noise of other frequency, delivers to computer (11)；Computer (11) passes through quick Fourier Leaf inverse transformation (IFFT), is transformed into frequency-region signal, then carries out root mean square calculation (RMS), it is thus achieved that acoustic wave energy signal；Auxiliary Helping and arrange sound wave door signal when the heating of high power density hot-fluid produces nucleateboiling, when CHF event occurs, high power is close The acoustic wave energy that degree hot-fluid Heating Experiment section (3) makes inner-walls of duct press water nucleateboiling produce exceedes this door signal, can sentence Determine CHF event to occur, thus monitor the CHF event that experimental section (3) occurs in real time；

Carry out Digital Signal Processing by computer (11), analyze acoustic power spectrum density and acoustic wave energy signal, and be aided with Critical heat flux door signal, monitors critical heat flux (CHF) event when unusual service condition occurs in experimental section (3) in real time.

A kind of reactor inner part critical heat flux side of monitoring in real time based on sonic sensor the most according to claim 1 Method, it is characterised in that: it is described that to be weighted selection by Hanning window be the first sonic sensor (4) and the second sound wave to be sensed The long discrete series signal that device (6) obtains becomes limited length sequence signal, uses DSP program MATLAB In file, hanning program is realized by computer.

A kind of reactor inner part critical heat flux side of monitoring in real time based on sonic sensor the most according to claim 1 Method, it is characterised in that: described Welch time average method processes when using Hanning window to sequence signal segmentation, it is allowed to each Section window has the overlapping of part, uses pwelch.m program in DSP program MATLAB file real by computer Existing, improve the relatively big produced spectrum distortion of sidelobe when rectangular window selects, by a series of conversion process of signal and calculating, Obtain power spectral density distribution (PSD) of signal.