EP0859966A2

EP0859966A2 - Method for fixing the position, with respect to the direction and range, of a target with an ultrasonic transducer

Info

Publication number: EP0859966A2
Application number: EP96945703A
Authority: EP
Inventors: Valentin Magori; Peter-Christian Eccardt; Heinrich Ruser; Martin Vossiek
Original assignee: Siemens AG
Current assignee: Siemens AG
Priority date: 1995-11-07
Filing date: 1996-11-04
Publication date: 1998-08-26
Also published as: DE19541459A1; WO1997017624A2; JPH11504430A; WO1997017624A3

Abstract

The invention relates to a method for fixing the position, with respect to direction and range, of a target using an ultrasonic transducer. The advantage of this measuring method is that it operates using only one ultrasonic transducer. A directionally selective sensor system can be produced with a minimum amount of technical outlay by activating the transducer in different operating modes.

Description

description

Method for determining the location and direction of a measurement object with an ultrasound transducer

The invention relates to a method for determining the location and distance of a measurement object with an ultrasound transducer.

From V. Magori, H. Walker, Ultrasonic Presece Sensors with Wi¬ de Range and High Local Resolution, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, Vol. UFFC-34, No. 2, March 1987 is known, to use a so-called RU 80 ultrasonic transducer as a proximity sensor. Typical applications for this are object detection, object height determination, monitoring of assembly lines, collision control, level measurement or detection of the presence of people. A so-called rear-sharp ultrasonic transducer, for example the RU 80 transducer described in the publication, is suitable for these applications. The narrow main sound lobe of approximately 5 °, as can be seen from FIG. 6 of the publication, is typical of this transducer.

However, if the location of the measurement object is not only to be determined in terms of distance, but also in terms of direction, then, as in A. Macovski, “Ultrasonic Imaging Using Arrays, Proceedings of the IEEE, Vol. 67, No. 4, API, described to use an ultrasonic transducer array, such as shown in Figure 1 of the document. Such an array has the disadvantage that it consists of several individual converters that have to be operated separately. In addition to the high cost, this results in complex control and an increased space requirement due to the design of the sensor. The assembly is more complicated than that of a single converter system. Furthermore, a scan system that uses mechanically moved transducers is known from E. Krestel, Imaging Systems for Medical Diagnostics, 2 ed. Berlin, Munich: Siemens AG, 1988. In addition to the effort for the mechanical movement of the transducers, the disadvantages here are the wear and tear and the associated susceptibility to faults and the necessary maintenance effort.

The object of the invention is to provide a method for determining the position and direction of a measurement object with a single, stationary ultrasound transducer.

The assembly and arrangement of such a system can advantageously be carried out in principle in the same way as with conventional ultrasonic single-transducer systems.

In contrast to a phased array, the space requirement is less and the control is simpler.

The object is achieved by a method according to claim 1.

Advantageous further developments result from the subclaims.

If a broadband transmission signal is used according to claim 2, the measurement rate can be increased due to the short signal duration.

It is advantageous to use the similarity criteria specified in claim 5 to determine the similarity of the target signal and the filter output signal, since these are determined by electronic measuring circuits (see, for example, U. Tietze and C. Schenk, semiconductor circuit technology, 9th edition Berlin , Heidelberg, New York: Springer-Verlag, 1990, pp. 852-885) or can also be easily determined by software and are highly informative. The fuzzy logic used in claim 6 to determine the filter output signal that comes closest to the target signal has the advantage of being easily adaptable to the ambient conditions. Furthermore, the fuzzy logic is highly flexible.

The method according to claim 7, in which a neural network is used, offers the advantage that the evaluation rules and similarity criteria need not be known explicitly, but can be learned by the neural network in a training phase.

The fuzzy logic used in claim 10 to compare the filter signals has the advantage of being easily adaptable to the ambient conditions. Furthermore, the fuzzy logic is associated with a high degree of flexibility.

The method according to claim 11, in which a neural network is used to compare the filter signals, offers the advantage that the evaluation rules and similarity criteria do not have to be known explicitly, but can be learned by the neural network in a training phase.

Narrow-band signal components with different frequencies, which are transmitted sequentially (compare claim 12), have the advantage over the broadband transmission signal that subsequent narrowband filtering to split the broadband received signal can be omitted.

The invention is explained in more detail below with reference to several figures. It shows

FIG. 1 shows the dependency of an RU 80 converter on the excitation frequency and the solid angle, FIG. 2 shows the spectral transfer function of the RU 80 converter with the send / receive direction 0 °,

FIG. 3 shows the spectral transfer function of the RU 80 converter with a send / receive direction of -3 °,

FIG. 4 shows the spectral transfer function of the RU 80 converter with a send / receive direction of -6 °,

Figure 5 shows the spectral transfer function of the RU 80 converter with a send / receive direction of -10 °.

FIG. 6 shows an exemplary measuring arrangement,

7 above the impulse response of the converter in the time domain, in the second diagram from above the representation in the frequency domain, in the third diagram from above the transfer function of the Wiener filter and below the received signal after Wiener filtering in the time domain,

FIG. 8 shows the directional characteristic of the RU 80 converter at 75 kHz,

FIG. 9 shows the directional characteristic of the RU 80 converter at 80 kHz,

FIG. 10 shows the directional characteristic of the RU 80 converter at 91 kHz,

FIG. 11 four evaluation results of the Wiener filtering with a rod as a measurement object,

FIG. 12 four evaluation results of the Wiener filtering with a plate as a measurement object.

FIG. 13 shows an example of the shape of a broadband transmitter, FIG. 14 shows a block diagram of a possible embodiment of the method according to the invention, and

FIG. 15 shows a block diagram of a second possible embodiment of the method according to the invention.

In the three-dimensional diagram shown in FIG. 1, the frequency in kHz and the solid angle in degrees are indicated on the two abscissas. The amplitude is plotted on the ordinate.

The diagram relates to a razor-sharp ultrasonic transducer of the type RU-80, as described in the article V. Magori et al, Ultrasonic Presence Sensors with Wide Range and High Local Resolution, IEEE Transactions and Ultrasonics, Ferroelectrics and Frequency Control, Vol. UFFC-34, No. 2, March 1987. The RU converter consists of a composite of a piezoceramic and a material with low acoustic impedance. This transducer is tuned in such a way that the radial resonance of the piezoceramic interferes constructively with the thickness resonance of the composite of ceramic and matching material. By attaching an aluminum ring, the thickness resonance is continued beyond the diameter of the piezoceramic. Due to the large transducer diameter compared to the wavelength, it is possible to achieve a very good directivity of the ultrasonic transducer.

It can be seen from the diagram that the ultrasonic transducer described has the global maximum at a solid angle of 0 ° and a resonance frequency of approximately 80 kHz. As can be seen from the diagram, the converter has different eigenmodes which can be described by the superposition of fundamental and harmonics of the radial and thickness resonances. The transducer was tuned so that there is a surface deflection on the useful frequency Edge slightly decreasing amplitude and constant phase without disturbing overlaps with radial resonances resulted.

The converter is usually operated in the narrow band on the useful mode (79 kHz) in order to achieve a defined directional behavior with little sidelobes.

In addition to the useful mode, there are also vibration modes whose surface deflection differs fundamentally from the forms of vibration at the useful frequency.

The directional diagrams resulting from the surface deflections of the ultrasonic transducer, cf. Figures 8, 9 and 10 are thus strongly dependent on the signal frequency. 8, 9 and 10, the radiation angle and the amplitude in the radial direction are plotted on the circumference. The directional behavior shown in FIG. 8 is obtained at a transmission signal frequency of 75 kHz. The main lobe of the measured ultrasonic transducer is approximately 3 °. Furthermore two side lobes are formed at approx. 10 and 355 °. If the converter is operated at 80 kHz, cf. 9, the amplitudes of the secondary maxima increase. The directional characteristic decreases. If the ultrasonic transducer is operated at 91 kHz, cf. Figure 10, the number of secondary sound lobes increases significantly. A clear main sound lobe is no longer given.

FIGS. 2 to 5 show the measured spectrum of the ultrasonic transducer, which results from the arrangement of a reflector at a solid angle of 0, 3, 6 or 10 degrees. The measured spectra differ significantly.

Knowledge of the transmission spectra expected from different solid angles is used to determine the direction. Possible selection procedures are described below. A reflector R is positioned at different spatial angles φ with respect to the ultrasonic transducer USW The signal is excited by a sine burst with a frequency that changes continuously over time (= chirp) or changes suddenly (= frequency hop codes). A sine burst with a sudden change in frequency is advantageous if the vibration modes of the ultrasonic transducer are far apart. The loss of energy can thereby be reduced. A possible excitation signal is shown in FIG. 13.

Likewise, the converter can be excited sequentially with a number of n sine bursts of different frequencies. The advantage here is that by evaluating and comparing the n sequential received signal components of different frequencies (which correspond to a broadband signal in total), one can deduce the solid angle of the reflection, provided that the frequency-dependent directional behavior of the transducer is known.

The converter of the type RU80 has a usable transmission behavior for the frequency range from 70 to 90 kHz. Its resonance frequency is 80 kHz.

Example 1:

Compare FIGS. 14 and 15. The method according to the invention works as follows:

A reference object R is set up at a defined location in relation to the ultrasound transducer USW, ie the distance of the reference object to the ultrasound transducer USW and the spatial angle φ are known. Now the ultrasound transducer USW is excited with a broadband signal SS, also called a transmission signal, and is thus caused to emit ultrasound waves. The ultrasound waves are partially reflected on the reference object R and received again by the ultrasound transducer USW. This received signal, which is also referred to as a reflected reference signal SROn, is used together with the location of the reference object. The procedure described above is repeated for different locations. This results in n reference signals SROn (n = number of stored reference signals), which will later be used to select the parameters of the Wiener filter.

If a measurement object MO, the location of which is still unknown, is now brought into the beam path of the ultrasound transducer USW, the ultrasound transducer USW is in turn prompted with the broadband transmission signal SS to emit ultrasound waves, which are partially reflected on the measurement object MO and received by the ultrasound transducer USW. This received ultrasound signal SMO is fed to Wiener filters WFn as an input signal. The transfer functions of the Wiener filter WFn are characterized by the reference signals SROn. The number n of reference signals SROn determines the number of Wiener filters WFn to which the measurement signal SMO is fed.

The filter output signals SWFn present at the Wiener filter outputs are then compared with a target signal W (ω), which corresponds to the window function (will be explained in more detail below).

Instead of comparing the filter output signals SWFn with the target signal W (ω), the filter output signals SWFn can also be compared with a so-called reference filter output signal SARef. In this case, a reference signal SROn is fed to a Wiener filter WFn, the transfer function of which is specified by precisely this reference signal SROn. Alternatively, the measurement signal SMO can also be fed to a Wiener filter, the transfer function of which is predetermined by this measurement signal. The basic aim here is to generate a reference output signal SARef at the output of the Wiener filter, with which the filter output signals SWFn present at the other Wiener filter outputs can be compared. The filter output signals SWFn can be compared with the target signal W (ω) or the reference output signal SARef, for example by means of fuzzy logic (see FIG. 14) or a neural network (see FIG. 15).

Features that can be used to compare the target signal W (ω) or the reference output signal SARef with the filter output signals SWFn are as follows:

l. Symmetry of the filter output signal SWFn, the axis of symmetry being placed in the main maximum of the filter output signal SWFn.

2. Width of the filter output signal SWFn, whereby not the entire width of the filter output signal, but the width of the main peak, which contains the global maximum, is used.

3. The area under the envelope of the filter output signal SWFn.

4. The quotient from the area under the main peek to the rest of the area of the filter output signal,

5. Evaluation in window areas with several reflectors,

6. The level and position of further secondary maxima in the filter output signal,

7. mean value in the signal and noise range,

8. Average value for the entire received signal.

Possible evaluation strategies are a suitable weighting of these features, a combined evaluation with the next bar classifier or fuzzy rules or an assignment to object classes (membership classes) in neural networks.

The features that can be used to compare the filter output signals SWFn with the target signal W (ω) or the reference output signal SARef are to be related to the respective application. Depending on the application, further features may have to be used.

The proposed Wiener filter acts like a matched filter for large signals and as a correlation filter for small signals (noise). If the measurement signal SMO corresponds to the reference signal SROn, this results in a maximum narrow output signal SWFn at the output of the Wiener filter.

The filter output signal SWFn, which comes closest to the target signal W (ω) or the reference output signal SARef, is used to infer the reference signal SROn relevant for generating this filter output signal SWFn. Since the location is also stored for this reference signal SROn, the location is thus determined.

The Wiener filter has the following transfer function I (ω):

Kω) = S ^* (ω) • W (ω)

S (ω) ^• S (ω) + - Φ- * ^■ Φ

in which:

S (ω) = frequency response of the ultrasonic transducer, φ _s = spectral power density of the signal, Φ _n = spectral power density of the noise,

S * (ω) = conjugate complex frequency response of the converter, W (ω) = window function = target function

The quotient Φs / φ _n as a measure of the signal-to-noise ratio can be for the frequency range of interest, which is determined by the adapted window function W (ω) is cut out to be assumed to be constant.

FIG. 7 shows the signals as they are generated successively in time. The pulse response of the ultrasound transducer USW in the time domain and below in the frequency domain is shown in FIG. 7 above. Again below this, the transfer function of the Wiener filter is shown as an example. It is characterized by the reference signal SROn. The bottom diagram shows the filter output signal SWFn in the time domain after the Wiener filtering.

Example 2:

As in embodiment 1, a reference object R is set up at a defined location with respect to the ultrasound transducer USW, i.e. the distance of the reference object to the ultrasonic transducer USW and the solid angle φ are known.

In contrast to exemplary embodiment 1, the ultrasound transducer USW is now excited with a narrow-band signal SS, also called a transmission signal, and is thus caused to emit ultrasound waves. This means that the converter sequentially sends out a number of n sine bursts of different frequencies.

The ultrasonic waves are partially reflected on the reference object R and received again by the ultrasonic transducer USW. The received signal has a total of a broadband signal. This received signal, which is also referred to as the reflected reference signal SROn, is stored together with the location of the reference object. The above process is repeated for different locations. This results in n reference signals SROn (n = number of stored reference signals), which will later be used to select the parameters of the Wiener filter. If a measurement object MO is brought into the beam path of the ultrasound transducer USW whose location is still unknown, the ultrasound transducer USW is again prompted with the narrow-band transmission signal SS to emit ultrasound waves, which are partially reflected on the measurement object MO and received by the ultrasound transducer USW. This received ultrasonic signal SMO has n sequential received signal components of different frequencies.

The shape of the measurement signal SMO and the shapes of the reference signals SROn can be used directly for evaluation. A Wiener filter is no longer necessary. Based on the shape of the reference signal SROn, which comes closest to the shape of the measurement signal SMO, the location of the measurement object can be concluded.

Evaluation criteria for this can be:

1. Difference in the magnitude spectrum between the reference signal SROn and the measurement signal SMO.

2. Difference in the characteristic amplitudes (for example the three most pronounced amplitudes which are given by the vibration modes of the ultrasound transducer).

3. Signal width of the measurement signal SMO based on the signal widths of the reference signals SROn

4. Basically all characteristics that describe the form of the signals.

Execution example 3:

It can be sent in broadband and filtered in narrowband. The advantage is that compared to embodiment 2, measurements can be carried out more quickly because the transmission signal duration is shorter. However, it is a narrow band Filtering for frequency separation necessary. The number of filters depends on the application.

Individual reflectors can be recognized at different angles.

An intelligent ultrasound level sensor with directionally selective echo evaluation can be implemented as an application. For example, fixed targets and deposits on the wall can be recognized in a silo.

The method can also be used in robotics, for example for obstacle detection in the direction of travel and to the side thereof.

The method can also be used in traffic engineering for vehicles as a reversing protection or as a parking aid.

The method can also be used to determine the position of an object on a conveyor belt.

Claims

claims

1. Method for determining the direction and distance of a measurement object with an ultrasound transducer,

1.1 in which the ultrasonic transducer (USW) is excited with a transmission signal (SS) for reference measurement l.l.l,

1.1.2 a reference signal (SROn) reflected by a reference object (RO) is received at the ultrasound transducer (USW) and stored with the associated location, 1.1.3 steps 1.1.1 and 1.1.2 for different locations of the reference object (RO ) be repeated,

1.2 in which the ultrasound transducer (USW) is excited with the transmission signal (SS),

1.3 when the measurement signal (SMO) reflected by the measurement object (MO) is received and stored on the ultrasound transducer (USW),

1.4 in which an evaluation of the shape of the measurement signal (SMO) and the shapes of the reference signals (SROn) is used to infer the direction and the distance.

2. The method according to claim 1, in which the transmission signal (SS) is a broadband signal.

3. The method according to claim 1 or 2, in which the evaluation of the shape of the measurement signal (SMO) and the shapes of the reference signals (SROn) occurs in that the shape of the measurement signal (SMO) is compared with the shapes of the reference signal (SROn) becomes.

4. The method as claimed in claim 1 or 2, in which the evaluation of the shape of the measurement signal (SMO) and the shape of the reference signals (SROn) occurs as a result,

that filter output signals (SWFn) are formed by means of the measurement signal (SMO) supplied to Wiener filter (WFn), the transmission properties of which are predetermined by one of the reference signals (SROn),

- That the reference signal (SROn) that corresponds to the filter output signal (SWFn) that comes closest to a target signal (W (ω)) is used to infer the location of the measurement object (MO).

5. The method according to claim 4, in which the symmetry of the filter output signals (SWFn) is maximized and / or the width of the output signals (SWFn) is determined in order to determine the filter output signal (SWFn) that comes closest to the target signal (W (ω)) whose maximum or / and the area under the envelope of the output signal (SWFn) or / and the quotient of area below the maximum to the rest of the area of the output signals (SWFn) is used.

6. Method according to claim 4 or 5, in which the filter output signal (SWFn) closest to the target signal (W (ω)) is determined by means of fuzzy logic.

7. The method according to claim 4 or 5, in which by means of a neural network the target signal (W (ω)) coming next filter output signal (SWFn) is determined.

8. The method according to claim 2,

- in which the measurement signal (SMO) is filtered with several narrow-band filters and the filter signals (SMOn) are stored, - in which the filter signals (SMOn) are related to one another and to the behavior of the transducer in order to determine the location of the measurement object ( MO) to close.

9. The method according to claim 8, in which the time-related position and / or the amplitude and / or the area under the envelope of the measurement signal (SMO) is used to compare the filter signals (SMOn).

10. The method according to claim 8 or 9, in which the comparison of the filter signals (SMOn) is carried out by means of fuzzy logic in order to conclude εo on the location of the measurement object (MO).

11. The method according to claim 8 or 9, in which the comparison of the filter signals (SMOn) is carried out by means of a neural network in order to conclude εo on the location of the measurement object (MO).

12. The method according to claim 1 or 3 - 7, in which the transmission signal (SS) has narrow-band signal components which occur sequentially and which differ by their frequency.