DE102021120317A1 - Sensor and method using a sensor - Google Patents

Abstract

Method with a sensor (1) and sensor (1) with at least one sensor element (2) for detecting sensor signals and at least one control and evaluation unit (3) for generating application parameters from the sensor signals, and an output unit (4) for outputting a object detection signal, the control and evaluation unit (3) having at least one filter (5) for filtering the application parameters and outputting filter results, the filter (5) being a filter with an infinite impulse response, the filter (5) being an adaptive filter, and the control and evaluation unit (3) has the filter (5) and is designed to form the object detection signal as a function of the filter results of the filter (5).

Description

The present invention relates to a sensor according to the preamble of claim 1 and a method with a sensor according to the preamble of claim 7.

Sensors should be suitable for a large number of uses and applications and always have a high measurement accuracy. In order to achieve this goal, a sensor must adapt to the application. For this purpose, the sensor determines various application-specific parameters or application-specific parameters and uses these to calculate the desired output variable.

Determining the parameters in this way can be viewed as the process of teaching the sensor to the application. It is desirable that this learning process works as quickly as possible and nevertheless with high accuracy, in order to achieve both rapid commissioning and high measurement accuracy.

A tried and tested means of achieving high measurement accuracy is filtering the measured parameters. The rule here is that the stronger the filter effect, the greater the measurement accuracy.

However, the higher the filter effect, the longer a learning process takes, since each filter involves a time delay. This behavior increases when there are dependencies between the parameters to be determined. Either a weak filter effect is set, which enables a faster learning process but entails low accuracy, or a strong filter effect is set, which requires a long learning process but enables high measuring accuracy.

One object of the invention is to provide a sensor or a method with a sensor for determining application-specific parameters or application-specific parameters, while at the same time a quick learning process and high measurement accuracy should be made possible.

The object is achieved according to claim 1 with a sensor having at least one sensor element for detecting sensor signals and at least one control and evaluation unit for generating application parameters from the sensor signals, and an output unit for outputting an object detection signal, the control and evaluation unit having at least one filter for filtering the application parameters and generating and outputting filter results, the filter being a filter with an infinite impulse response, the filter being an adaptive filter, and the control and evaluation unit having the filter and being designed to form the object detection signal as a function of the filter results of the filter.

The object is further achieved according to claim 7 with a method having a sensor with at least one sensor element for detecting sensor signals and at least one control and evaluation unit for generating application parameters from the sensor signals, and an output unit for outputting at least one object detection signal, the control and Evaluation unit has at least one filter for filtering the application parameters and generating and outputting filter results, the filter being a filter with an infinite impulse response, the filter being an adaptive filter, and the control and evaluation unit having the filter and the object detection signal depending on the filter results of the filter is formed.

The invention describes a method or a sensor with a control and evaluation unit for determining application-specific parameters or application parameters, which at the same time enables a rapid learning process and high measurement accuracy.

The invention allows for a fast and accurate learning process that includes application-specific parameters at the same time, especially when there are dependencies between the application parameters.

The basic idea is that the filter effect is adapted to a learning state and the dependencies of the individual application parameters among one another. It is assumed that the application-specific parameters do not change or only change very slowly. For example, the application parameters only change over a period of hours, days or weeks.

A filter with an infinite impulse response (English infinite impulse response filter, IIR filter or IIR system) is a specific type of filter in signal processing. It designates a linear, shift-invariant filter, also called LSI system (Linear Shift-Invariant). Depending on the specific selection of the filter parameters, this type of filter can deliver an infinitely long impulse response, in contrast to filters with a finite impulse response.

There are various possibilities for rational IIR filters to implement them as a network of addition, multiplication and delay elements. The actual implementation can take place in microcontrollers, digital signal processors or in digital hardware such as FPGAs or ASICs. In principle, different types of transfer functions can be implemented in all IIR filter structures.

An adaptive filter in signal processing is a special analog filter or digital filter that can independently change its transfer function and frequency during operation. For this purpose, the IIR filter is provided with an adjustment network that can change the filter coefficients according to certain rules.

• - mindestens ein Filterwert als Startwert des Filters,
• - mindestens ein Filterwert als Endwert des Filters,
• - mindestens ein Inkrementalwert des Filterwertes und
• - mindestens ein Filterzähler mit einer Anzahl zu bestimmender Werte innerhalb einer Filterstufe sind,

wobei die Anwendungsparameter zyklisch zu verschiedenen Zeitpunkten entsprechend der Anzahl zu bestimmender Werte erfasst werden, und mit dem Filterwert als Startwert des Filters gefiltert werden, und ein aktualisiertes Filterergebnis berechnet wird, wobei die Anwendungsparameter zyklisch zu verschiedenen Zeitpunkten entsprechend der Anzahl zu bestimmender Werte erfasst werden und mit dem aktuellen Filterwert gefiltert werden, wobei die Anwendungsparameter zyklisch so lange zu verschiedenen Zeitpunkten entsprechend der Anzahl zu bestimmender Werte erfasst werden und so lange mit dem aktuellsten Filterwert gefiltert werden bis ein Endwert des Filters erreicht ist, wobei das finale gefilterte Filterergebnis in der Steuer- und Auswerteeinheit zur Berechnung des Objektfeststellungssignals angewendet wird.In a development of the invention, the filter has at least four filter parameters, with the filter parameters

• - at least one filter value as the start value of the filter,
• - at least one filter value as the end value of the filter,
• - at least one incremental value of the filter value and
• - are at least one filter counter with a number of values to be determined within a filter stage,

wherein the application parameters are recorded cyclically at different times according to the number of values to be determined, and are filtered with the filter value as the start value of the filter, and an updated filter result is calculated, wherein the application parameters are recorded cyclically at different times according to the number of values to be determined and are filtered with the current filter value, with the application parameters being recorded cyclically at different times according to the number of values to be determined and filtered with the most recent filter value until an end value of the filter is reached, with the final filtered filter result in the control and evaluation unit for calculating the object detection signal is used.

If the sensor has not yet been taught in for the application (e.g. delivery status), the lowest filter effect, namely the filter value, is selected as the start value of the filter. The control and evaluation unit now determines the application-specific parameters or application parameters n times (n=number of values to be determined within the filter level of the filter counter) and filters them with the lowest filter level, ie the start value of the filter. The filter parameter number of values to be determined within the filter level of the filter counter depends on the complexity of the dependencies. The more complex the dependencies or the more hierarchical levels there are, the higher this filter parameter must be selected so that a steady state results before the filter effect is increased. After the application parameters have been determined n times, the filter effect is increased by an incremental value of the filter value. The larger this filter parameter is, the faster high accuracy is achieved. At the same time, however, reaching the stationary state is delayed. In this filter stage, the application-specific parameters or the application parameters are again determined n times until the filter effect is again increased by an incremental value of the filter value. This procedure is carried out until the maximum filter level, i.e. the filter value as the final value of the filter, is reached.

In a development of the invention, the sensor has a memory unit, the application parameters being stored in the memory unit and the application parameters being read in by the control and evaluation unit when the sensor is switched on.

In order to prevent unnecessary re-teaching for the same application after a sensor restart, the control and evaluation unit persistently saves the filter level and the application parameters in the memory unit and starts after a restart with these parameters and in this filter level.

However, in order to enable rapid re-teaching at the same time if a sensor that has already been taught-in is to be used in a new application with different application parameters, the control and evaluation unit determines the application parameters directly after the restart without a filter effect. If these application parameters deviate from the saved application parameters by more than an adjustable tolerance, all saved application parameters are discarded and the filter level is reset to the start value. The learning process starts again.

In a further development of the invention, the sensor is an inductive or magnetic sensor.

In pneumatic cylinders, a piston position is usually determined via a transmitter magnet attached to the piston, using an inductive or magnetic sensor. The properties such as orientation, magnetization, remanence or geometry of the magnet can vary.

An inductive or magnetic sensor is provided, for example, for the non-contact magnetic detection of linear relative movement of a transmitter magnet along a measuring section. The sensor has, for example, two identical sensor elements, with each sensor element detecting at least one component of a magnetic field of the transmitter magnet, with the sensor elements being arranged at a distance along the measurement path, with the sensor elements each generating a monotonic position signal, each with one value of a value range for one position in each case generate along the measuring section of the encoder magnet, the characteristics of the position signals each having a point symmetry, for example. The distance between the sensor elements is, for example, shorter than the measuring section. The spatial extent of the sensor elements is also shorter than the measuring section, for example.

• - ein Offset von Sensorsignalen,
• - eine Verstärkung offsetkorrigierter Sensorsignale,
• - ein Linearitätsfehler,
• - und/oder Messpunkte der Sensorsignale.

In a further development of the invention, the application parameters are at least

• - an offset of sensor signals,
• - an amplification of offset-corrected sensor signals,
• - a linearity error,
• - and/or measuring points of the sensor signals.

One possible magnetic position sensor is a magnetic position sensor that calculates the relative position of a transmitter magnet to the sensor center using, for example, two sensor elements each with two field components. For example, since the magnetic field is highly non-linear, various application parameters must be determined so that the position can be calculated correctly. In addition, various corrections must be made during the evaluation in the magnetic field so that the position determination has good accuracy.

The following application parameters are determined by the control and evaluation unit. These application parameters are determined when the magnet passes over various characteristic points in the measuring range. For some application parameters, certain conditions must first be met before they can be determined.

Offsets of sensor signals are determined as application parameters. Both individual signals of the two sensor elements must be as symmetrical and congruent as possible. Any offset must be corrected to establish point symmetry

An amplification of offset-corrected sensor signals is determined as an application parameter. It can happen that the negative area of the individual characteristic has a different gain than the positive area. This error must also be compensated for in order to establish point symmetry.

A linearity error is determined as an application parameter.
A special algorithm that has a (calculable) linearity error is used to determine the position between the sensor elements. The calculation and compensation further improves the position determination between the elements.

Measuring points of individual characteristic curves are determined as application parameters. The offset and gain-compensated individual characteristic curves are approximated using measuring points and thereby linearized.

The application parameters have the following conditions, for example.
To determine the offsets of the sensor signals, a magnet must cover a minimum distance and move across the center of the sensor.

To determine the amplification of offset-corrected sensor signals, the magnet must move over both sensor elements.

To determine a linearity error, the magnet must move over the center of the sensor and at least one sensor element.

To determine measuring points of individual characteristic curves, the measuring points are determined at specific positions calculated by the sensor.

Until the conditions are met, no application parameters are initially determined. There are therefore application parameters that are determined immediately and others that are only recorded after a few movements of the magnet. This leads to an order in determining the application parameters. The measuring points can usually be determined first, since there are hardly any preconditions here. At least two movements are required for the first determination to offset the raw signals. At least one for the amplification of offset-corrected sensor signals. Even 20 movements are necessary to determine the linearity error. However, this only has a very small influence on the measuring points.

• Der Offset von Sensorsignalen hat keine Abhängigkeiten und basiert nur auf Rohdaten.

The application parameters are therefore dependent on one another:

• The offset of sensor signals has no dependencies and is only based on raw data.

The amplification of offset-corrected sensor signals depends on the offset of the sensor signals

The linearity error depends on the offset of the sensor signals and on the amplification of offset-corrected sensor signals.

The measuring points of the sensor signals depend on the offset of the sensor signals, on the amplification of offset-corrected sensor signals and on the linearity error.

For example, the filter parameter filter counter = five is selected for this hierarchy of dependencies. This should ensure that all application parameters are determined at least once before the filter effect is increased.

• Filterwert als Startwert des Filters = 0,
• Filterwert als Endwert des Filters = 0,9,
• Inkrementalwert des Filterwertes = 0,45,
• Filterzähler mit einer Anzahl zu bestimmender Werte innerhalb einer Filterstufe = 5.

For example, the following values are selected for the filter parameters:

• Filter value as start value of the filter = 0,
• filter value as final value of the filter = 0.9,
• incremental value of the filter value = 0.45,
• Filter counter with a number of values to be determined within a filter level = 5.

In a development of the invention, the filter result is calculated according to the following rule: $$\begin{array}{l}\text{filter result}\left(\text{n}\right)=\text{filter result}\left(\text{n}-1\right)*\text{filter value}+\text{reading}\left(\text{n}\right)*(1-\text{filter}-\\ \text{value})\text{where n}=\text{Incremental value of the filter}\left(5\right)\text{is}\text{.}\end{array}$$

The measured value is, for example, the currently recorded value of the application parameter.

• 1 einen Sensor an einem Pneumatikzylinder;
• 2 zwei Diagramme zur Filterauswertung;
• 3 zwei Diagramme zum Stand der Technik.

The invention is explained below also with regard to further advantages and features with reference to the attached drawing based on exemplary embodiments. The figures of the drawing show in:

• 1 a sensor on a pneumatic cylinder;
• 2 two diagrams for filter evaluation;
• 3 two prior art diagrams.

In the following figures, identical parts are provided with identical reference numbers.

1 shows a sensor 1 with at least one sensor element 2 for detecting sensor signals and at least one control and evaluation unit 3 for generating application parameters from the sensor signals, and an output unit 4 for outputting an object detection signal, the control and evaluation unit 3 having at least one filter 5 for Filtering of the application parameters and generation and output of filter results, the filter 5 being a filter with an infinite impulse response, the filter being an adaptive filter, and the control and evaluation unit 3 having the filter 5 and the object detection signal being designed as a function of the filter results of the filter ( 5) to form.

For example, the sensor 1 is an inductive or magnetic sensor 1 according to FIG 1 .

In pneumatic cylinders 9, a piston position is usually determined by means of an inductive or magnetic sensor 1 via a transmitter magnet 8 attached to the piston 7. The properties such as orientation, magnetization, remanence or geometry of the magnet can vary.

An inductive or magnetic sensor 1 is provided, for example, for the contactless magnetic detection of linear relative movement of the transmitter magnet 8 along a measuring section 10 . The sensor 1 has, for example, two identical sensor elements 2, with each sensor element 2 detecting at least one component of a magnetic field 11 of the transmitter magnet 8, with the sensor elements 2 being arranged at a distance along the measuring section 10, with the sensor elements each generating a monotonic position signal, each with a Generate a value of a value range for a respective position along the measuring section 10 of the sensor magnet 8, with the characteristic curves of the position signals each having point symmetry, for example. The distance between the sensor elements 2 is, for example, shorter than the measuring section 10. The spatial extent of the sensor elements 2 is also, for example, shorter than the measuring section 10.

A possible magnetic sensor 1 or position sensor is a magnetic position sensor that calculates the relative position of a transmitter magnet 8 to the sensor center via, for example, two sensor elements 2 each with two field components. For example, since the magnetic field is highly non-linear, various application parameters must be determined so that the position can be calculated correctly. In addition, various corrections must be made during the evaluation in the magnetic field so that the position determination has good accuracy.

• - mindestens ein Filterwert als Startwert des Filters,
• - mindestens ein Filterwert als Endwert des Filters,
• - mindestens ein Inkrementalwert des Filterwertes und
• - mindestens ein Filterzähler mit einer Anzahl zu bestimmender Werte innerhalb einer Filterstufe sind,

wobei die Anwendungsparameter zyklisch zu verschiedenen Zeitpunkten entsprechend der Anzahl zu bestimmender Werte erfasst werden, und mit dem Filterwert als Startwert des Filters 5 gefiltert werden, und ein aktualisiertes Filterergebnis berechnet wird, wobei die Anwendungsparameter zyklisch zu verschiedenen Zeitpunkten entsprechend der Anzahl zu bestimmender Werte erfasst werden und mit dem aktuellen Filterwert gefiltert werden, wobei die Anwendungsparameter zyklisch so lange zu verschiedenen Zeitpunkten entsprechend der Anzahl zu bestimmender Werte erfasst werden und so lange mit dem aktuellsten Filterwert gefiltert werden bis ein Endwert des Filters erreicht ist, wobei das finale gefilterte Filterergebnis in der Steuer- und Auswerteeinheit 3 zur Berechnung des Objektfeststellungssignals angewendet wird.For example, the filter 5 has at least four filter parameters, with the filter parameters

• - at least one filter value as the start value of the filter,
• - at least one filter value as the end value of the filter,
• - at least one incremental value of the filter value and
• - are at least one filter counter with a number of values to be determined within a filter stage,

where the application parameters are recorded cyclically at different points in time according to the number of values to be determined, and are filtered with the filter value as the start value of the filter 5, and an updated filter result is calculated, with the application parameters being recorded cyclically at different points in time according to the number of values to be determined and filtered with the current filter value, with the application parameters being recorded cyclically at different times according to the number of values to be determined and filtered with the most recent filter value until a final value of the filter is reached, with the final filtered filter result in the control - And evaluation unit 3 is used to calculate the object detection signal.

If the sensor 1 has not yet been taught in for the application (eg in the delivery state), then the lowest filter effect, namely the filter value, is selected as the start value of the filter. The control and evaluation unit 3 now determines the application-specific parameters or application parameters n times (n=number of values to be determined within the filter level of the filter counter) and filters them with the lowest filter level, i.e. the start value of filter 5. The filter parameter number of values to be determined within the filter stage of the filter counter' depends on the complexity of the dependencies. The more complex the dependencies or the more hierarchical levels there are, the higher this filter parameter must be selected so that a steady state results before the filter effect is increased. After the application parameters have been determined n times, the filter effect is increased by an incremental value of the filter value. The larger this filter parameter is, the faster high accuracy is achieved. At the same time, however, reaching the stationary state is delayed. In this filter stage the application-specific parameters or the application parameters are again determined n times until the filter effect is increased again by an incremental value of the filter value. This procedure is carried out until the maximum filter level, i.e. the filter value as the final value of the filter, is reached.

For example, the sensor 1 has a memory unit 6, the application parameters being stored in the memory unit 6 and the application parameters being read in by the control and evaluation unit 3 when the sensor 1 is switched on.

In order to prevent unnecessary re-teaching for the same application after a sensor restart, the control and evaluation unit 3 persistently stores the filter level and the application parameters in the storage unit 6 and starts after a restart with these parameters and in this filter level.

At the same time, however, to enable rapid re-teaching if a sensor 1 that has already been taught-in is to be used in a new application with different application parameters, the control and evaluation unit 3 determines the application parameters directly after the restart without a filter effect. If these application parameters deviate from the saved application parameters by more than an adjustable tolerance, all saved application parameters are discarded and the filter level is reset to the start value. The learning process starts again.

• - ein Offset von Sensorsignalen,
• - eine Verstärkung offsetkorrigierter Sensorsignale,
• - ein Linaritätsfehler,
• - und/oder Messpunkte der Sensorsignale.

For example, the application parameters are at least

• - an offset of sensor signals,
• - an amplification of offset-corrected sensor signals,
• - a linearity error,
• - and/or measuring points of the sensor signals.

The control and evaluation unit 3 determines the following application parameters. These application parameters are determined when the sensor magnet 8 passes over different characteristic points in the measuring area or the measuring section 10 . For some application parameters, certain conditions must first be met before they can be determined.

Offsets of sensor signals are determined as application parameters. Both individual signals of the two sensor elements must be as symmetrical and congruent as possible. Any offset must be corrected to establish point symmetry

An amplification of offset-corrected sensor signals is determined as an application parameter. It can happen that the negative area of the individual characteristic has a different gain than the positive area. This error must also be compensated for in order to establish point symmetry.

A linearity error (LinError) is determined as an application parameter.
A special algorithm, which has a (calculable) linearity error, is used to determine the position between the sensor elements 2 . The calculation and compensation further improves the position determination between the elements.

Measuring points of individual characteristic curves (MeasPoints) are determined as application parameters. The offset and gain-compensated individual characteristic curves are approximated using measuring points and thereby linearized.

The application parameters have the following conditions, for example.
In order to determine the offsets of the sensor signals, a transmitter magnet 8 has to cover a minimum distance and move over the sensor elements 2 .

In order to determine the amplification of offset-corrected sensor signals, the encoder magnet 8 must move over both sensor elements 2.

To determine a short-stroke linearity error, the encoder magnet 8 must move over the center of the sensor and at least one sensor element 2.

For the determination of measuring points of individual characteristic curves, the measuring points are determined at specific positions calculated by the sensor 2 .

Until the conditions are met, no application parameters are initially determined. There are therefore application parameters that are determined immediately and others that are only recorded after a few movements of the encoder magnet. This leads to an order in determining the application parameters. The measuring points can usually be determined first, since there are hardly any preconditions here. At least two movements of the transducer magnet along the entire measurement section 10 are required for the first determination for the offset of the raw signals. At least one for the amplification of offset-corrected sensor signals. Even 20 movements are necessary to determine the linearity error. However, this only has a very small influence on the measuring points.

• Der Offset von Sensorsignalen hat keine Abhängigkeiten und basiert nur auf Rohdaten.
• Die Verstärkung offsetkorrigierter Sensorsignale ist abhängig von Offset der Sensorsignale. Der Linearitätsfehler ist abhängig von Offset der Sensorsignale und von der Verstärkung offsetkorrigierter Sensorsignale. Die Messpunkte der Sensorsignale sind abhängig vom Offset der Sensorsignale, von der Verstärkung offsetkorrigierter Sensorsignale und vom Linearitätsfehler.

The application parameters are therefore dependent on one another:

• The offset of sensor signals has no dependencies and is only based on raw data.
• The amplification of offset-corrected sensor signals depends on the offset of the sensor signals. The linearity error depends on the offset of the sensor signals and on the amplification of offset-corrected sensor signals. The measuring points of the sensor signals depend on the offset of the sensor signals, on the amplification of offset-corrected sensor signals and on the linearity error.

For example, the filter parameter filter counter = five is selected for this hierarchy of dependencies. This should ensure that all application parameters are determined at least once before the filter effect is increased.

2 shows the application parameters for the adaptive filter (5).

• Filterwert als Startwert des Filters = 0,
• Filterwert als Endwert des Filters = 0,9,
• Inkrementalwert des Filterwertes = 0,45,
• Filterzähler mit einer Anzahl zu bestimmender Werte innerhalb einer Filterstufe = 5.

For example, the following values are selected for the filter parameters:

• Filter value as start value of the filter = 0,
• filter value as final value of the filter = 0.9,
• incremental value of the filter value = 0.45,
• Filter counter with a number of values to be determined within a filter level = 5.

With the adaptive filter effect, the position is determined very precisely after just two runs. With each increase in the filter effect (after run five and run ten), the precision of the position determination increases again. The measuring points are also much more precise and stable directly.

For example, the filter result is calculated according to the following rule: $$\begin{array}{l}\text{filter result}\left(\text{n}\right)=\text{filter result}\left(\text{n}-1\right)*\text{filter value}+\text{reading}\left(\text{n}\right)*(1-\text{filter}-\\ \text{value})\text{where n}=\text{Incremental value of the filter}\left(5\right)\text{is}\text{.}\end{array}$$

3 shows the settling of the application parameters for a constant filter value of, for example, 0.85 according to the prior art. With the constant filter effect, a slow settling of the measuring points can be observed, which means that the position is only stable after about 10 runs.

reference list

1

sensor

2

sensor element

3

Control and evaluation unit

4

output unit

5

filter

6

storage unit

7

Pistons

8th

encoder magnet

9

pneumatic cylinder

10

measuring section

11

magnetic field

Claims (10)

Sensor (1) with at least one sensor element (2) for detecting sensor signals and at least one control and evaluation unit (3) for generating application parameters from the sensor signals, and an output unit (4) for outputting at least one object detection signal, the control and evaluation unit (3) has at least one filter (5) for filtering the application parameters and generating and outputting filter results, characterized in that the filter (5) is a filter with an infinite impulse response, the filter (5) is an adaptive filter, and the control and evaluation unit (3) has the filter (5) and is designed to form the object detection signal as a function of the filter results of the filter (5). Sensor (1) after claim 1 , characterized in that the filter (5) has at least four filter parameters, the filter parameters having at least one filter value as the start value of the filter (5), at least one filter value as the end value of the filter (5), at least one incremental value of the filter value and at least one filter counter a number of values to be determined within a filter stage, the filter (5) being designed to record the application parameters cyclically at different points in time according to the number of values to be determined, and to filter with the filter value as the start value of the filter (5), and an updated To calculate the filter result, the application parameters of the filter (5) being recorded cyclically at different times according to the number of values to be determined, and being filtered with the current filter value, the application parameters of the filter (5) being cyclically recorded by the filter (5) at different times accordingly of the number of values to be determined req asst and filtered with the most current filter value until a final value of the filter (5) is reached, the control and evaluation unit (3) being designed to calculate the object detection signal evaluate. Sensor (1) according to at least one of the preceding claims, characterized in that the sensor (1) has a memory unit (6), wherein the application parameters are stored in the memory unit (6) and when the sensor (1) is switched on, the application parameters are read from the Control and evaluation unit (3) are read. Sensor (1) according to at least one of the preceding claims, characterized in that the sensor (1) is an inductive or magnetic sensor. Sensor (1) after claim 3 , characterized in that the application parameters are at least - an offset of sensor signals, - an amplification of offset-corrected sensor signals, - a linearity error, - and/or measuring points of the sensor signals. Sensor (1) according to at least one of the preceding claims, characterized in that the filter result is calculated according to the following rule: $$\begin{array}{l}\text{filter result}\left(\text{n}\right)=\text{filter result}\left(\text{n}-1\right)*\text{filter value}+\text{reading}\left(\text{n}\right)*(1-\text{filter}-\\ \text{value})\text{where n}=\text{Incremental value of the filter}\left(5\right)\text{is}\text{.}\end{array}$$

Method with a sensor (1) with at least one sensor element (2) for detecting sensor signals and at least one control and evaluation unit (3) for generating application parameters from the sensor signals, and an output unit (4) for outputting at least one object detection signal, the Control and evaluation unit (3) has at least one filter (5) for filtering the application parameters and generating and outputting filter results, characterized in that the filter (5) is a filter with an infinite impulse response, the filter (5) is an adaptive filter, and the control and evaluation unit (3) has the filter (5) and the object detection signal is formed depending on the filter results of the filter (5). procedure after claim 7 , characterized in that the filter (5) has at least four filter parameters, the filter parameters being at least one filter value as the start value of the filter (5), at least one filter value as the end value of the filter (5), at least one incremental value of the filter value and at least a number of determining values within a filter stage, with the application parameters being recorded cyclically at different points in time according to the number of values to be determined, and being filtered with the filter value as the start value of the filter (5), and an updated filter result being calculated, with the application parameters being cyclically recorded at different points in time are recorded according to the number of values to be determined and filtered with the current filter value, the application parameters being recorded cyclically at different times according to the number of values to be determined and filtered with the most recent filter value until a final value of the filter (5) is reached, the final filtered filter result being evaluated in the control and evaluation unit (3) for calculating the object detection signal. Method according to at least one of the preceding Claims 7 until 8th , characterized in that the sensor (1) has a memory unit (6), the application parameters being stored in the memory unit (6) and the application parameters being read in by the control and evaluation unit (3) when the sensor (1) is switched on. Method according to at least one of the preceding Claims 7 until 9 , characterized in that the filter result is calculated according to the following rule: $$\begin{array}{l}\text{filter result}\left(\text{n}\right)=\text{filter result}\left(\text{n}-1\right)*\text{filter value}+\text{reading}\left(\text{n}\right)*(1-\text{filter}-\\ \text{value})\text{where n}=\text{Incremental value of the filter}\left(5\right)\text{is}\text{.}\end{array}$$

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