This application is a U.S. National Stage entry of PCT Application No. PCT/EP2016/052810, filed on Feb. 10, 2016, which claims priority from PCT Patent Application No. PCT/EP2015/060263, filed May 8, 2015, the contents of which are incorporated herein by reference.
The present invention relates to a method for processing a measuring signal of a pressure measuring cell and to a measuring cell arrangement having a pressure measuring cell.
It is known to measure pressures or pressure differences by applying pressure to a thin membrane and measuring the deflection resulting therefrom. A known and suitable method to measure the deflection of such membranes consists in designing the membrane arrangement as a variable electrical capacitance, the change in capacitance, which correlates with the change in pressure, being evaluated via an electronic measuring system. The capacitance is formed by the thin, flexible membrane surface being arranged at a small distance from a further surface of a body and both mutually opposite surfaces being designed to be electrically conductive. If the membrane and the body consist of non-conductive dielectric material, the surfaces are coated with an electrical coating, for example, as a result of which capacitor electrodes are formed. The membrane and/or the body can also themselves be formed of electrically conductive material, the surfaces again forming the capacitor electrodes in this case. If pressure is applied to the membrane, the distance between the two electrodes changes as a result of deflection, which leads to a change in capacitance that can be evaluated.
Sensors of this kind are produced in large numbers from silicon, for example. Both the flat base body and the membrane often consist entirely of silicon. There are also other embodiments a with combined composition of materials, e.g. silicon with a glass base. The sensors can thus be produced at low cost. Pressure sensors of this type can usually only be used for higher pressure ranges in the range of approximately 10−1 mbar to several bar. A high resolution at lower pressures from approximately 10−1 mbar can no longer be realized with silicon material. Sensors of this kind are not suitable for typical vacuum applications. For the various vacuum processes to be monitored, pressure measurements are often carried out in a vacuum between atmospheric pressure and 10−6 mbar. Such measurements require high sensitivity with high resolution and good reproducibility of the vacuum pressure measurement, which can only be provided by specially designed measuring cells which completely deviate from the design of the high-pressure measuring cell.
Capacitive membrane pressure measuring cells which are made of corrosion-proof materials such as Al2O3 are particularly suitable for vacuum pressure measurement. A known capacitive vacuum measuring cell, which is made substantially completely of ceramics and is largely corrosion-proof, is described in EP 1 070 239 Bl. In order to enable the measurement of very low pressures up to 10−6 mbar with high precision, a very thin ceramic membrane with a thickness of 60 μm is used, for example, is used, which is arranged in a tension-free and symmetric manner in a ceramic housing.
The distance of the capacitor electrodes or the membrane surfaces from the surface of the housing body lies preferably in the range of 2 to 50 The diameters of such membrane pressure measuring cells lie preferably in the range of 5 to 80 mm. The thus formed capacitances to be measured lie in the range of 10 pF to 32 pF. Thanks to new electronics, it is now possible to measure capacitances in a range of 5 pF to 1000 pF. The measured capacitance is used as a measure for the pressure to be measured. This capacitance changes accordingly under a pressure-dependent deflection of the membrane, by means of which the pressure applied to the membrane can be detected. This measurement of the capacitance must take place highly precisely and is not easy to carry out in the case of very low capacitance values because the low capacitances lead to the consequence that the changes in capacitance caused by the changes in the pressure are extremely small. As a result, the electrical signals generated or derived therefrom are exceptionally low and thus susceptible to disturbances.
Correspondingly high demands are thus placed on the signal processing systems for processing pressure signals according to the comments made above.
Furthermore, filter algorithms are used for optimizing the properties of the measured pressure signals for further use, e.g. for controlling the pressure in process chambers. This is an attempt to provide a filter algorithm which simultaneously achieves two contradictory objectives for processing pressure signals. Firstly, a transient response, for example after a step-like change in the measuring signal, should be completed as rapidly as possible, i.e., the output signal of the filter should lead as quickly as possible to a stable output signal. As a result, any necessary action due to a change in pressure can be initiated as rapidly as possible. Secondly, a potential noise signal must be suppressed as strongly as possible by the filter algorithm. This therefore requires a filter that is as fast as possible according to the first condition, whereas a slow filter is instead desirable according to the second condition.
Numerous efforts are known to provide a filter algorithm and thus a transfer function for a filter for processing the measuring signal so as to achieve the two contradictory objectives. The known filter algorithms are based on compromises, which in the present application in pressure measurement using highly sensitive sensors, do not lead to satisfactory results.
U.S. Pat. No. 5,838,599 describes a variant for a filter, which permits both short transient responses during a rapid change in the input signal and a good reduction in the noise signal components in the input signal in the steady state.
Furthermore, reference is made to US 2013/0016888 A1, which discloses a complex computational method with a linear filter for eliminating noise.
It is the object of the present invention to provide a simple method for processing a measuring signal in which a distinct suppression of the noise signal is achieved, but which simultaneously allows a rapid reaction to relevantly changing measuring signals.
This object is achieved by the features of claim 1. Advantageous embodiments and a measuring cell arrangement comprising a pressure measuring cell are provided in the further claims.
The method according to the invention for determining a pressure in a pressure cell consists in
determining a measuring signal that is at least proportional to a measured pressure in the pressure cell,
generating an output signal from the measuring signal using a filter unit comprising a transfer function by at least reducing and preferably eliminating a noise signal in the measuring signal,
determining a change over time of the measuring, and
setting the transfer function as a function of the change over time of the measuring signal.
In one embodiment of the method according to the invention, the pressure in the pressure cell is adjusted at least proportionally to the output signal. A closed control system that is extremely stable and robust is thus obtained.
The output signal is linear and thus excellently suited as the actual value for modern controllers (state controller).
In one embodiment of the method according to the invention, a transfer function has, at least in a first order, a low pass characteristic, the time constant thereof being adjusted as a function of the change over time of the measuring signal.
In further embodiments of the method according to the invention consist, an average value of the measuring signal is determined, a difference signal is determined by calculating the difference between the measuring signal and the average value of the measuring signal, and the change over time of the measuring signal is derived at least from the difference signal.
In further embodiments of the method according to the invention, the average value of the multiple substrate is determined, using an exponential average value filter, which is defined for a time-discrete measuring signal by
fn=β1·xn+(1−β1)·fn-1
where f is the time-discrete output signal, β1 is a variable, x is the time-discrete measuring signal, and n is a time-dependent index, the variable β1 having in particular a value between 1 and 0, particularly preferably between 1 and 0.1, and very particularly preferably between 0.85 and 0.95.
In further embodiments of the method according to the invention, the change over time of the measuring signal is determined by formation of an average value of the difference signal.
In further embodiments of the method according to the invention, the change over time of the measuring signal is determined using an exponential average—value filter, which is defined for a time-discrete difference signal by
Δxn=β2en+(1−β2)ΔXn-1
where Δxn is the time-discrete change in the measuring signal, β2 is a variable, e is the time-discrete difference signal, and n is a time-dependent index, the variable β2 having in particular a value between 1 and 0, particularly preferably between 0.5 and 0.01, very particularly preferably between 0.05 and 0.15.
In further embodiments of the method according to the invention, the time constant of the transfer function of a time-discrete system is defined by
where ΔT corresponds to the sampling interval in the time-discrete system and α is a variable those value is at least proportional to the change over time of the measuring signal, but does not go below a minimum value of αmin, and does not exceed a minimum value of αmax, the minimum value αmin being preferably between 0.0 and 0.1, particularly preferably between 0.0 and 0.01, and the minimum value αmax being in particular between 0.3 and 1.0.
In still further embodiments of the method according to the invention, the transfer function is defined by the formula
yn=α·xn+(1−α)·yn-1
where y is the time-discrete output signal, x is the time-discrete measuring signal, a is a variable whose value depends on the change over time of the measuring signal, and n is a time-dependent index.
In still further embodiments of the method according to the invention, the measuring signal is processed in a fast path in order to generate an output pulse, the output pulse of the fast path being active at least as long as the measuring signal change measured during at most three sampling intervals is greater than the noise measured in the same period in the measuring signal or in the measuring signal change.
In still further embodiments of the method according to the invention, the measuring signal is also processed in a slow path in order to generate a switching signal, the switching signal of the slow path being active at least as long as the change in the measuring signal measured for longer than 2*TS is greater than the noise measured in the measuring signal or in the measuring signal change in the same time period, TS being a predetermined pulse width of the output pulse, and the variable α obtains a value depending on an OR operation between the output pulse and the switching signal.
In still further embodiments of the method according to the invention, the variable α assumes either the value α1 or the value α2 at least after a predetermined transition time after a switching process, the value for α1 being in particular in the range of 0.01 to 0.9 and the value for α2 being in particular in the range of 0.0001 to 0.01.
In still further embodiments of the method according to the invention, switching from a value α1 to a value α2 takes place over a timespan Fin and/or switching from a value α2 to a value α1 takes place over a timespan Fout.
The invention further relates to a measuring cell arrangement comprising a pressure cell and a membrane pressure measuring cell operatively connected to the pressure cell, which membrane pressure measuring cell generates a pressure-dependent measuring signal which is applied to a filter unit having a transfer function in order to generate an output signal, it being possible to determine a change over time of the measuring signal and to set the transfer function as a function of the change over time of the measuring signal.
In one embodiment of the measuring arrangement according to the invention, that the output signal can be used for adjusting the pressure in the pressure cell, in particular for adjusting the pressure in a process chamber.
In one embodiment of the measuring arrangement according to the invention, the transfer function has, at least in a first order, a low pass characteristic, it being possible to adjust the time constant thereof as a function of the change over time of the measuring signal.
In further embodiments of the measuring arrangement according to the invention, an average value of the measuring signal can be determined, a difference signal can be determined by calculating the difference between the measuring signal and the average value of the measuring signal, and the change over time of the measuring signal can be derived at least from the difference signal.
In further embodiments of the measuring arrangement according to the invention, the average value of the measuring signal can be determined using an exponential average-value filter, which is defined for a time-discrete measuring signal by
fn=β1·xn+(1−β1)·fn-1
where f is the time-discrete average value of the measuring signal, β1 is a variable, x is the time-discrete measuring signal, and n is a time-dependent index, the variable β1 having in particular a value between 1 and 0, particularly preferably between 1 and 0.1, more particularly preferably between 0.85 and 0.95.
In further embodiments of the measuring arrangement according to the invention, the change over time of the measuring signal can be determined by formation of an average value of the difference signal.
In further embodiments of the measuring arrangement according to the invention, the change over time of the measuring signal can be determined using an exponential average-value filter, which is defined for a time-discrete difference signal by
Δxn=β2en+(1−β2)Δxn-1
where Δxn is the time-discrete change over time of the measuring signal, β2 is a variable, en is the time-discrete difference signal and n is a time-dependent index, the variable β2 preferably has in particular having a value between 1 and 0, particularly preferably between 0.5 and 0.01, more particularly preferably between 0.05 and 0.15.
In further embodiments of the measuring arrangement according to the invention, the time constant of the transfer function of a time-discrete system is defined by
where ΔT corresponds to the sampling interval in the time-discrete system and α is a variable whose value is at least proportional to the change over time of the measuring signal, but does not go below a minimum value αmin and does not exceed a maximum value αmax, the minimum value αmin being preferably between 0.0 and 0.1, particularly preferably between 0.0 and 0.01, and the minimum value αmax being in particular between 0.3 and 1.0.
In further embodiments of the measuring arrangement according to the invention, the transfer function is defined by the formula:
yn=α·xn+(1−α)·yn-1
where y is the time-discrete output signal, x is the time-discrete measuring signal, α is a variable whose value depends on the change over time of the measuring signal, and is a time-dependent index.
In further embodiments of the measuring arrangement according to the invention, the measuring signal is applied to a fast path in order to generate an output pulse, the output pulse of the fast path being active at least as long as the measuring signal change measured during at most three sampling intervals is greater than the noise measured in the same period of time in the measuring signal or in the measuring signal change.
In further embodiments of the measuring arrangement according to the invention, the measuring signal is also applied to a slow path in order to generate a switching signal, the switching signal of the slow path being active at least as long as the change in the measuring signal measured for longer than 2*TS is greater than the noise measured in the measuring signal or in the measuring signal change in the same time period, TS being a minimum pulse width of the output signal, and the variable α acquires a value depending on an OR operation between the output pulse and the switching signal.
In further embodiments of the measuring arrangement according to the invention, the variable α assumes either the value α1 or the value α2 after a predetermined transition time following a switching process, the value for α1 being in particular in the range of 0.01 to 0.9, and the value for α2 being in particular in the range of 0.0001 to 0.01.
In further embodiments of the measuring arrangement according to the invention, a transition unit is provided between the filter unit and the decision unit, in which transition unit switching from a value of al to a value of α2 takes place over a timespan Fin and/or switching from a value of α2 to a value α1 takes place over a timespan Fout.
It is pointed out that the above embodiments can be combined in any manner desired. This excludes only the combinations of embodiments that would by combination lead to a contradiction.
Embodiments of the present invention are explained in more detail below with reference to drawings, in which:
It is also conceivable—in a simplified embodiment of the present invention—that the output signal y of the signal processing unit 4 is not used for controlling the pressure in a process chamber. In this case this is not a closed system but an open system. Here, a pressure is measured in a pressure cell of any desired type similarly to in the process chamber according to
The invention now relates again with consideration of the embodiments according to
The output signal y of the signal processing unit 4 is processed further in the control unit 5 for example by a so-called P-, PI-, PID or state controller. The controller implemented in the control unit 5 is responsible in particular for optimal tracking of the control signal s for the valve actuator 6 or for the valve 7.
In principle, the statements regarding processes in the signal processing unit 4 and the block diagrams thereof apply both to the embodiments in a closed system and to the embodiments in an open system.
As is clear from
The filter unit 10 has a filter characteristic that is defined in a time-discrete system according to the following equation, for example:
yn=α·xn+(1−α)·yn-1
Here, y is the time-discrete output signal, x is the time-discrete measuring signal, n is a time-dependent index, and a is a variable whose value decisively determines the time constant of the filter unit 10. The object of the present invention is that of optimally setting the value for the variable α in such a way that a noise signal in the measuring signal x is suppressed as far as possible or even eliminated, but at the same time a changing pressure in the process chamber is identified so as to be able to react thereto with the appropriate speed.
The mentioned equation with the variable α has, as the filter characteristic for suppression of the noise signal portion, a low pass characteristic, where the time constant T can be defined for a first-order filter as follows:
The choice of values for the variable α is decisive for the present invention. If the measuring signal x receives only a noise signal in the event of a stable pressure value, the value of α is to be selected to be as small as possible (αmin), for example 0.01. In this way, the noise signal present in the measuring signal x is maximally suppressed and the filtered output signal y is preferably suited for use in the downstream controller of the control unit 5 (
On the other hand, a change in the measuring signal x based on an actual pressure change in the process chamber must be detected without delay, which makes a different value for the variable α necessary, namely for example a value for a between 0.3 and 1.0 (αmax).
The value for the variable α is adjusted according to the invention depending on the change over time of the measuring signal x, which is explained below in detail.
The difference signal e is a measure for the change over time of the measuring signal x and is used in this embodiment according to the invention for setting the value for the variable α in the filter unit 10 (
The smoothing unit 13 implemented by means of an exponential average-value filter is defined by the recursive formula
fn=β1·xn+(1−β1)·fn-1
where f is the time-discrete output signal, β1 is a variable, x is the time-discrete measuring signal and n is a time-dependent index, the variable β1 having, in the case of the exponential average-value filter for generating the difference signal f, a value in particular between 1 and 0, particularly preferably between 1 and 0.1, more particularly preferably between 0.85 and 0.95.
The calculation unit 11 according to
en=fn−xn
Consequently, the same definitions apply; see above formulations, as already given for the first stage. Individually the value for the variable β, which was accordingly referred to as β2, has a different value: the variable β2 preferably obtains, in the case of the exponential average-value filter for determining the change over time of the measuring signal x, a value in particular between 1 and 0, in particular between 0.5 and 0.1, in particular a value between 0.05 and 0.15.
The change over time Δx of the measuring signal x can thus be defined as follows from the time-discrete difference signal e:
Δxn=β2en+(1−β2)Δxn-1
where Δxn is the time-discrete change over time of the measuring signal x, en is the time-discrete difference signal e, and n is a time-dependent index.
In this embodiment of the present invention, the change over time Δx or Δxn obtained hereby of the measuring signal x may also need to be scaled, as has already been explained in connection with the embodiment according to
The change over time Δx of the measuring signal x is scaled with a factor k (as already explained in connection with the embodiments shown in
All of the following specific numerical examples (in particular for the time constant τ) proceed from a typical sampling time ΔT (referred to as the cycle time) of 1 ms. Of course the sampling time ΔT of 1 ms serves only as an example. The sampling time ΔT is fundamentally selected within the scope of the available calculating performance and the necessary reaction time of the entire system.
As is clear from
In terms of quality, the following principles can be formulated with regard to the parameters α1
and α2 of the filter unit 10 (
Measuring signals x that do not change as a function of time (i.e. if no pressure changes are present) can be filtered intensely so as to maintain maximum noise suppression. It has been shown that for the parameter α2, values between 0.0001 (τ≈10 s) and 0.01 (τ≈100 ms) are suitable. A preferred value for the parameter α2 is 0.001 (τ'1 s).
Measuring signals x that do change as a function of time if pressure changes are present) need to be less intensely filtered. In this case, the parameter α1 defines the damping factor. This is therefore typically selected to be greater than the parameter α2. It has been shown that for the parameter α1, values between 0.1 (τ≈100 ms) and 0.9 (τ≈0.1 ms) are suitable. A preferred value for the parameter α1 is 0.1 (τ≈9 ms).
As already mentioned, the slope determination unit 50 initially consists of the two functional blocks “fast” 20 and “slow” (30, the functional block “fast” generating an output signal FC for fast changes and the functional block “slow” 30 generating an output signal SC for slow changes, from which a control signal SW is obtained by an “OR” operation as follows:
SW=FC OR SC
The result of an active control signal SW—as follows from the flow diagram of
The functional block “fast” 20 detects and reacts within a sampling interval ΔT (where the sampling interval ΔT is in turn 1 ms, for example) to fast changes of the measuring signal x, but is relatively insensitive to slow or constant measuring signal changes. The slow or constant measuring signal changes are detected by the functional block “slow” 30.
The boundary between slow and fast measuring signals x is indicated by the functional block “fast” 20:
If the frequency of the measuring signal x is smaller than
this is a slow measuring signal x from the standpoint of the functional block “fast” 20; otherwise it is a fast measuring signal x. The meaning of these statements and the resultant reaction will be examined in detail in connection with the explanations of the functional blocks 20 and 30.
The output signal αx of the calculation unit 11 is sent to a value unit 21, in which the value of αx is determined and sent to an addition unit 25. In a further value unit 22, the value of the difference signal e likewise determined in the calculation unit 11 is obtained. The value signal |e| is then again smoothed in an average-value filter 23 with the parameter β3 according to the following formula:
hn=β3·|en|+(1−β3)·hn-1
the output signal hn being sent to the additional unit 25 after scaling with the factor CF in a multiplication unit 24, in which additional unit the
difference between the value signal Δx and CF·h is determined. The result is sent to a threshold value detector 26, which produces a trigger when a predetermined threshold value is exceeded, which trigger is sent to a monoflop 27. The monoflop 27, which is formed for example as a retriggerable monoflop, generates an output pulse CF after receipt of a trigger at the input, the length of which output pulse can be set over the pulse width TS. In this regard, “retriggerable” means that a trigger arriving during the time process restarts the internal time of the monoflop 27 each time and the active switching state is accordingly extended in time.
As already explained, the signal αx constitutes a measure for the change in the measuring signal x. By filtering of the amount of the difference signal e with the average value filter 23 and subsequent scaling with the factor CF, the signal CF·h is obtained. This is now a measure for the “basic noise” of the measurement of the measuring signal change Δx. By comparing the signals CF·h and the amount of Δx, the binary control signal “trigger” is thus obtained, which is used to control the monoflop 27.
It has been shown that the damping factors β1 and β2 and β3 should have in particular the following values:
For β1 in a range of 0.1 to 0.001 (τ≈9 ms to 1 s), in particular 0.01 (τ≈100 ms) as a typical value; for β2 in the range of 01 to 0.001 (τ≈9 ms- . . . 1 s), in particular 0.01 (τ≈100 ms) as a typical value; and for β3 in the range of 0.01 to 0.0001 (τ≈100 ms to 10 ms), in particular 0001 (τ≈1 s) as a typical value.
Proceeding from the pressure monitoring and pressure adjustment system shown in
For measuring signals x which have frequencies smaller than
the functional block “fast” 20 (
One embodiment for the functional block “slow” 30 (see
the frequencies typically being smaller than 1 Hz, assuming a pulse width TS of 500 ms, for example. The functional block “slow” 30 calculates a switching signal SC as an output signal as follows:
SS is a measure for the change in the measuring signal x over a longer time period, which for example is longer than 2·TS (i.e., double the pulse width TS) and thus typically amounts to seconds, and where SSN is a measure for the noise of the measuring signal x. Both SSN and SS are determined using the average-value filters of the type already described. The transfer function of the average-value filter has been explained in connection with the description of the filter unit 10 of
SS is obtained with the further average-value filters 35 and 38 (
It has been shown that the damping factors β5 and β6 should have in particular the following values:
For β5 in the range of 0.01 to 0.0001 (r 100 ms to 10 s), in particular 0.001 (τ≈1 s) as a typical value; and for β6 in the range of 0.1 to 0.0001 (τ=100 ms to 10 s), in particular 0.001 (τ≈1 s) as a typical value.
The signal SS calculated in the manner just described is substantially a measure for the sum of the change in the measuring signal x and the noise of the measuring signal x. The independent signal SSN is now calculated from (slow) changes of the measuring signal x by a high pass filter 31 and a further average-value filter 33. This is thus a measure for the noise of the measuring signal x, and by comparison with the signal SS, the desired switching signal SC according to the conditions indicated above is obtained.
It has been shown that the damping factors β4 should lie in a range, for example, of 0.005 to 0.00005 (τ≈200 ms to 20 s), in particular should be equal to 0.0005 (τ≈2 s).
The output signal of the average-value filter 33 is connected for scaling to a multiplier unit 34, to the second input of which a scaling factor CS is applied in order to generate the output signal SSN. It has been shown that the scaling factor CS has a value of 50, for example.
The object of the high pass filter 34 is that of separating noise and slow changes in the measuring signal x. Assuming that the noise of the measuring signal is distributed normally over the assessable frequency range of 0- . . . 1 kHz (with a typical sampling interval ΔT of 1 ms), a high pass filter 34 according to the following configuration has proven to be suitable:
filter type: high pass filter
design method: elliptical
sampling frequency: 1 kHz
cutoff frequency in pass band: 400 Hz
oscillations in pass band: 3 dB
cutoff frequency in stop range: 250 Hz
damping in stop range: 73 dB
Under these conditions, a fourth-order high pass filter is produced, which can be calculated and implemented easily, i.e. with reasonable outlay.
In the following, the function of the transition unit 51 is explained: the two additional parameters Fin and Fout define two timespans, which are used in switching the damping factor of α1 to α2 or vice versa, depending on the transition direction either the timespan Fin or the timespan Fout being definitive depending on the transition direction. If the switch has to be made from α2 to α1 (i.e. a pressure change occurs), the timespan Fin is used during which a soft transition from α2 to α1 is carried out. In the reverse direction—i.e. when stable pressure conditions again dominate after a pressure change—the switch must be from α1 to α2. According to this, embodiment this likewise no longer takes place abruptly, but within the timespan defined by Fout. Again a “softer” transition from α1 to α2 takes place.
It has been shown that for the two timespans Fin or Fout, for example, the following values are suitable:
For the timespan Fin in the range of 0 to 100 ms, in particular 10 ms as a typical value; and for the timespan Fout in the range of 0 to 10 s, in particular 1 s is a typical value.
Filing Document | Filing Date | Country | Kind |
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PCT/EP2016/052810 | 2/10/2016 | WO | 00 |
Publishing Document | Publishing Date | Country | Kind |
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WO2016/180547 | 11/17/2016 | WO | A |
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0612149 | Aug 1994 | EP |
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Number | Date | Country | |
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20180259360 A1 | Sep 2018 | US |