EP2783364B1 - Method and apparatus for controlling an active noise cancellation system - Google Patents

Description

The invention relates to a method for treating the appearance of a malfunction in an Active Noise Control (ANC) system.

More specifically, the invention relates to a method for controlling an active noise reduction system, for example in a passenger compartment having one or more loudspeakers for producing one or more sound output signals that oppose noise and a or more microphones for capturing one or more feedback signals that measure the noise reduction achieved.

The invention also relates to a device and a computer program for implementing said method.

Active noise reduction is an old subject. Henri Coanda had thus described in 1930 a method of protection against noise in his patent FR722274 consisting in obtaining a zone of silence by interference of sound waves. The idea was good but not so obvious to realize. A little later in 1934, Paul Lueg was limited in his patent US2043416 in the simplified case of a pipe in which he placed a loudspeaker downstream of a sound source with a microphone placed between the source and the loudspeaker to pick up the sound to be removed before it reached the loudspeaker. speaker.

Despite numerous scientific developments since that time, particularly in the field of signal processing, the use of this invention, however old, struggles to become democratized, in other words to become accessible to a wide audience.

The disadvantage is that, in spite of a strong current control of theoretical noise reduction, the slightest defect or unforeseen event on the equipment or the environment of a device for reducing sound waves per generation appropriately out of phase, has consequences contrary to the desired effect, namely those of adding the energy of the phase-shifted sound waves to those of the source instead of cutting them off, with the effect of increasing rather than reduce the noise.

Among the many attempts since that time to try to overcome these inconveniences, we can cite, for example, the one described in the document EP1143411A2 which includes at least one sensor for measuring a system condition that communicates with a control unit. When a predetermined system condition is detected by the sensor, the noise suppression property of the control unit is disabled. The predetermined system condition is based on a motor noise level received by the sensor (an error microphone), a background noise level received by the sensor, or a relationship between the engine noise level and the level background noise. The system conditions may be factors potentially leading to unwanted noise generation by the noise attenuation system without system deactivation. For example, a motor noise level lower than the background noise would indicate a situation of possible generation of unwanted noise. In this situation as in other circumstances, the control unit disables the noise attenuation properties to avoid unwanted noise generation.

The document JP05027780 discloses in abbreviated form an active noise controller which calculates an evaluation function from inputs each allocated to a microphone when the filtering coefficient of an adaptive filter is updated and which calculates the gradient of the evaluation function compared to the filter coefficient. Then it is decided whether or not the evaluation function is higher than a threshold value. If the evaluation function is greater than the threshold value, a timer is started and the frequency of variation of the sign of the gradient is counted until the timer expires. When the variation frequency exceeds a determined value, the state divergence due to a model spatial transfer function and an effective spatial transfer function, requires switching off the power of a control signal to a speaker.

The document US2008 / 159553 discloses a method and an active noise reduction system in which a faulty system state is detected when an error signal given back by a sound sensor exceeds a second threshold after exceeding a first one.

Previous solutions are all based on the obvious concept that the noise may increase in case of malfunction, it should be disabled the system when the sound picked up, by a microphone or in some other way, exceeds a certain threshold. However the prior methods and systems pose a problem of inefficiency in case the malfunction comes from the sound sensor itself.

These more or less recent solutions, like other known solutions, are not sufficiently complete to bring complete satisfaction.

• une étape d'activation du système de réduction active de bruit ;
• une étape de vérification de retour qui établit un diagnostic de retour en analysant au moins un signal de retour et qui autorise une réexécution de l'étape d'activation à la suite d'un diagnostic de retour positif ;
• une étape de neutralisation qui est exécutable à la suite d'un diagnostic de retour négatif et qui désactive le système de réduction active de bruit.

Selon l'invention, l'étape de vérifications de retour comprend une sous-étape de détection basse qui calcule un critère de retour opérant et qui rend négatif le diagnostic de retour lorsqu'au moins un signal de retour ne satisfait pas une valeur minimale du critère de retour opérant. Selon l'invention, le critère de retour opérant correspond à un cumul de variations du signal de retour sur un intervalle de temps donné. Particulièrement, l'étape de vérification de retour comprend une sous-étape de détection haute qui rend négatif le diagnostic de retour lorsqu'au moins un signal de retour n'est pas inférieur à une valeur maximale en amplitude.To overcome the drawbacks of the prior art, the subject of the invention is a method for controlling an active noise reduction system, as defined in independent claim 1, the method comprising:

• an activation step of the active noise reduction system;
• a return verification step that establishes a return diagnosis by analyzing at least one return signal and that allows a replay of the activation step following a positive feedback diagnosis;
• a neutralization step that is executable following a negative feedback diagnosis and that deactivates the active noise reduction system.

According to the invention, the return check step comprises a low detection substep which calculates an operative return criterion and renders the return diagnosis negative when at least one return signal does not satisfy a minimum value of the return. Operational return criterion. According to the invention, the operating return criterion corresponds to a plurality of variations of the feedback signal over a given time interval. In particular, the return check step includes a high detection sub-step that negates the return diagnosis when at least one feedback signal is not less than a maximum amplitude value.

Preferably, the control method comprises an output verification step which establishes an output diagnostic by analyzing at least one output signal, which allows a re-execution of the step following a positive output diagnostic and which makes the neutralization step executable as a result of a negative output diagnostic so as to deactivate the active noise reduction system

Specifically, the output verification step includes a high detection substep that negates the output diagnostic when at least one output signal is not less than a maximum amplitude threshold.

Also particularly, the output verification step includes a substep of amplitude limitation of the output signal a maximum threshold.

Particularly advantageously, the method comprises a moderation step which allows a re-execution of the activation step following a diagnosis of negative output or feedback until a sufficient number of an output diagnostic or negative feedback occurrence, which triggers the disabling step when there is a sufficient number of output diagnostic or negative feedback occurrences.

More preferably, the control method comprises a state monitoring step of an environment of the active noise reduction system that allows activation of the active noise reduction system only when said environment is in a state compatible with said activation.

• des moyens de vérification de retour agencés pour établir un diagnostic de retour en analysant au moins un signal de retour ; et
• des moyens d'activation et de neutralisation du système de réduction de bruit actif pilotés pour activer, respectivement désactiver le système de réduction de bruit actif à la suite d'un diagnostic de retour positif, respectivement à la suite d'un diagnostic de retour négatif.

Selon l'invention, les moyens de vérification de retour sont agencés pour calculer un critère de retour opérant et pour rendre négatif le diagnostic de retour lorsqu'au moins un signal de retour ne satisfait pas une valeur minimale du critère de retour opérant.The subject of the invention is also a device for controlling an active noise reduction system, as described in independent claim 8, in particular in a passenger compartment, comprising one or more loudspeakers for producing one or more output signals. sound that oppose the noise and one or more microphones for capturing one or more feedback signals that quantify the noise reduction achieved. The control device comprises in particular:

• return verification means arranged to establish a return diagnosis by analyzing at least one return signal; and
• activation and deactivation means of the active noise reduction system controlled to activate or deactivate the active noise reduction system respectively after a positive feedback diagnosis, respectively following a negative feedback diagnosis .

According to the invention, the return verification means are arranged to calculate an operating return criterion and to make the return diagnosis negative when at least one return signal does not satisfy a minimum value of the operating return criterion.

Advantageously, the return verification means are arranged to make the return diagnosis negative when at least one feedback signal is not less than a maximum amplitude value.

The subject of the invention is also a computer program, comprising program code means for performing all or part of the steps of the method which is the subject of the invention, when the program is running on a computer, in particular on a computer. embedded calculator.

The invention particularly relates to a computer program product, comprising program code means, stored on a computer-readable medium, for implementing the method according to the invention, when the program product runs on a computer.

The subject of the invention is in particular a vehicle in which an active noise reduction system in a passenger compartment comprises one or more loudspeakers for producing one or more noise-canceling output signals and one or more pickup microphones. one or more feedback signals which quantify the noise reduction obtained, the vehicle comprising a control device according to the invention.

• la figure 1 est une vue schématique d'un système sur lequel l'invention est appliquée ;
• la figure 2 montre des étapes de procédé conforme à l'invention ;
• les figures 3 et 4 sont des détails d'étapes du procédé conforme à l'invention ;
• les figures 5 à 7 sont des courbes comportementales obtenues dans certaines étapes du procédé.

The invention will be better understood with the aid of exemplary embodiments of a device according to the invention with reference to the appended drawings, in which:

• the figure 1 is a schematic view of a system to which the invention is applied;
• the figure 2 shows process steps according to the invention;
• the figures 3 and 4 are details of steps of the process according to the invention;
• the Figures 5 to 7 are behavioral curves obtained in some steps of the process.

The figure 1 shows a motor vehicle referenced 12 which includes an active noise reduction system (ANC) which some of the elements shown below are shown outside the vehicle 12 simply for ease of explanation.

One or more microphones 11, generally three, each pick up an error signal u _mic at a predetermined delivery point of the vehicle 12. Each delivery point is predetermined during the design and testing phases of a prototype vehicle. in order to obtain optimal noise reduction at the ears of the driver and preferably of each of the occupants. Thus the microphones can be placed closer to the driver's head and each occupant or at geometrically correlated locations of the vehicle with noise amplitude nodes of the noise in the vicinity of the occupants' heads.

One or more boxes or speakers 13 whose number generally varies between four and five, receive control signals u _HP of an electronic device 14 shown in dashed lines.

The electronic device 14 comprises an electronic card 15 which houses an ANC algorithm for active noise reduction, an audio device 16, for example radio, which can also independently include multimedia and / or navigation functions and a mixer 17.

The algorithm hosted by the electronic card 15 generates a signal u _C for each speaker 13 to reduce or eliminate the noise in the cabin 20 of the vehicle 12. The noise that is to be suppressed is a frequency noise or at a frequency spectrum determined by a measurable or calculable RPM rotation rate of a vehicle member such as, for example, but not necessarily of a power train 21. Sounds coming from other sources such as, for example, the tread of the wheels 22 on the roadway or of a sound emission apparatus, could then also be reduced or eliminated provided they are transmitted at the same frequency or at one or more frequencies controlled spectrum.

The audio device 16 generates a signal u _R intended for one or more of the loudspeakers 13 to generate sound in the passenger compartment 20 of the vehicle 12, for example that of a radio transmission, the music of a multimedia support or audible messages for navigation, vehicle operating status or telecommunication.

The electronic card 15 and the audio device 16 may be contained in the same housing of the electronic device 14 or in separate boxes. The ANC algorithm can also be hosted in an on-board computer shared with the audio device 16 in the form of one or more programs executable by the on-board computer.

The mixer 17 generates u _HP signals which result u _C and u _R signals to be routed each one to that of the speakers 13 which are intended u _C and u _R signals respectively combined two by two.

The electronic card 15 is connected to a vehicle signal multiplexing bus 18, for example a CAN (Controller Area Network) bus, in order to read in real time various information on the state of the vehicle comprising in particular the engine speed. RPM (acronym for Revolutions Per Minute) expressed in revolutions per minute. This information can also be received wireline from point to point. The advantage of the multiplexing bus 18 is to make available to the ANC algorithm real-time information on many other states of the vehicle, such as the opening state of a door or window, for example. engine running condition. The advantage of the on-board computer for carrying out the functions of the electronic card 15 is to provide a great flexibility in the progressive operation of the states available on the bus 18.

The electronic card 15 or the on-board computer also receives a supply voltage Va of the electronic components from a battery 19 of the vehicle 12.

The ANC algorithm uses, in a manner known otherwise, the theoretical and practical knowledge of active noise reduction without the need to present all the details here.

It is simply recalled that currently there are essentially two types of ANC algorithms for active noise reduction, feedforward algorithms and feedback-based algorithms, usually referred to as feedback loops. reaction.

As for example exposed in French in the article of Emmanuel Friot "An Introduction to Active Acoustic Control" of October 6, 2005, in particular on pages 16 to 21 and 38 to 41 , or exposed in English in the article of SJ Elliot "A Review of Active Noise and Vibration Control in Road Vehicles" of December 2008, especially pages 12-14 , the predictive action consists mainly in controlling a loudspeaker sound on a noise reference, measured by a first microphone or estimated based on, for example, a motor speed. A second microphone is used to adapt in real time the transfer function of the servo so as to obtain a noise cancellation measured by the second microphone.

As for example stated in the international patent application WO201013661 , the retroactive action consists mainly of enslaving a loudspeaker sound on an error compared to a zero reference, as measured by a microphone. A favored noise frequency is used to adapt the transfer function of the servocontrol so as to obtain cancellation of the error at said favored frequency. The adaptation of the transfer function is modifiable so as to follow the changes in the preferred frequency that can change, for example depending on the rotational speed of the engine.

The invention can be used for both the predictive and retroactive action algorithms and for any other type of ANC algorithms for active noise reduction, notably by producing a sound well at a noise frequency that results from the engine rotation speed. .

Nevertheless, a retroactive action type algorithm is preferred. The inventors have noted that the predictive algorithm requires constantly adapting the transfer function to any variation measured by the second microphone. These adaptations require calculations that are perform in real time. The inventors have noted that, on the other hand, retroactive algorithms do not require the transfer function to be constantly adapted to any variation measured by the microphone which conventionally acts as a feedback function with a given transfer function in a closed control loop. The inventors have thus found it advantageous to adapt the transfer function to a favored frequency which corresponds, for example, to the fundamental frequency or to the second harmonic of the noise generated by the motor. It is then possible to pre-calculate adaptation parameters of the transfer function for a series of favored frequencies and then quickly select in operation the adaptation of the transfer function which corresponds to the frequency favored as a function of the speed of transmission. motor rotation observed in real time.

The transfer function involves one or more frequency response functions between the signal (s) _HP sent to the loudspeakers 13 and the _microphone signal (s) measured on the error microphones 11.

It is possible to evaluate a frequency response function at a value FRF (f) according to a frequency f by sending a signal u _HP (f) to or to one of the loudspeakers 13 in the absence of noise. and collecting the _microphone signal (f) from each microphone 13, using the formula: $$\mathrm{FRF}\left(\mathrm{f}\right)={\mathrm{u}}_{\mathrm{microphone}}\left(\mathrm{f}\right)/{\mathrm{u}}_{\mathrm{HP}}\left(\mathrm{f}\right)$$

The frequency response functions depend on the audio reproduction system comprising speakers and loudspeakers 13, the acoustic cavity formed by the passenger compartment 20 of the vehicle 12 and the error microphone or microphones 13 including the sensitivity.

It will be noted that the electronic device 14 represented in figure 1 , comprises a device 23 for controlling the active noise reduction system, in particular the electronic card 15.

The device 23 comprises on the one hand one or more output couplers for transmitting to the mixer 17 one or more sound output signals u _c to the speaker or speakers 13 to oppose the noise in the passenger compartment 20.

The device 23 further comprises one or more input couplers connected to the microphone or microphones 11 for receiving one or more feedback signals for transmission to the ANC algorithm, for example hosted on the card. electronics 15 to quantify the noise reduction obtained. The device 23 may also include an input coupler connected to the battery 19 to observe the voltage level and one or more input couplers connected to the bus 18 to read the engine speed RPM and different states of the vehicle 12 relative to example when opening the doors or windows, the vehicle load acceleration, deceleration, uphill or downhill.

Return verification means are arranged in the device 23 to establish a return diagnosis by analyzing at least one _mic return signal.

The return verification means may perform several analyzes of the return signal.

A first possible analysis consists in calculating a criterion C1 of operating return, in other words non-zero return specific to the use of the operations performed by the algorithm ANC. The existence of a return signal which does not satisfy a minimum value of the operating return criterion C1 then renders the diagnosis of negative return

A second possible analysis consists in comparing each u _mic feedback signal with a maximum amplitude value so that the return diagnosis is made negative as soon as a u _mic feedback signal is not lower than this maximum value.

Control verification means are arranged in the device 23 to establish an output diagnostic by analyzing all or part of the u _C signals output of the ANC algorithm, each intended for one of the speakers 13.

Here again, the control verification means can perform several analyzes of the output signal by means of tests.

A first test consists in verifying that the amplitude of the control signal u _c of each of the loudspeakers 13 does not exceed a threshold value. The threshold value is different for each of the loudspeakers because the control signals sent to each of the loudspeakers are different. On the other hand, the threshold value depends on the control frequency associated with one or more harmonics, in particular with the harmonic 2 of the engine speed. This threshold value is set and entered by the manufacturer at the time of manufacture of the vehicle. The control signal sent to the loudspeakers is a sinusoidal type signal or a composition of periodic signals in a predetermined frequency band. The test consists in verifying, at a given engine speed, that the maximum of this control signal never exceeds a threshold value given in the table. If the signal has a value that exceeds the threshold value, then in this case, the amplitude of the signal is replaced by this threshold value so as to limit the amplitude. This operation ensures that the amplitude of the signal emitted by the loudspeakers never exceeds a certain threshold.

The device 23 thus sends the mixer 17 a controlled signal u _e associated with each control signal uc so that the amplitude of the signal u _c is equal to the amplitude of the signal u _c as long as the amplitude of the signal u _c is less than the threshold value and which is equal to the threshold value when the amplitude of the signal u _c is greater than or equal to the threshold value.

Other tests may be considered to complete the failure detection system, for example a frequency test and a phase test between the signals. It is not absolutely necessary to implement these other tests because the system has shown satisfactory behavior in a large number of situations during tests carried out as part of the development of the invention.

où E[] est l'opérateur d'espérance mathématique.Regarding the detection of a failure on the frequency, the following test can be imagined and easily implemented. The control signal sent to the loudspeakers is a sinusoidal type signal whose frequency must be identical to that of the control relative to the harmonic 2 of the engine speed. It is then a question of verifying that the two signals have the same frequency. One way to achieve it is to calculate a coefficient of temporal inter correlation C _up between the control signal u (x _i , t) of the loudspeaker xi at time t and the sinusoidal signal p (xi, t + τ ) which has a frequency identical to the control frequency at time t + τ, represented by the following expression: $${\mathrm{VS}}_{\mathit{up}}\left({\mathrm{x}}_i,{\mathrm{x}}_j,\tau \right)=\frac{E\left[u\left({\mathrm{x}}_i,t\right)p*\left({\mathrm{x}}_j,t+\tau \right)\right]}{\sqrt{E\left[u\left({\mathrm{x}}_i,t\right)u*\left({\mathrm{x}}_i,t\right)\right]\sqrt{E\left[p\left({\mathrm{x}}_j,t+\tau \right)p*\left({\mathrm{x}}_j,t+\tau \right)\right]}}}.$$

where E [] is the mathematical expectation operator.

The detection of a failure on the phase between the signals is more delicate because it is essentially the ANC algorithm.

More specifically, the device 23 comprises means 24 for activating and neutralizing the active noise reduction system, comprising, for example, the electronic card 15. The means 24 are driven firstly to activate the active noise reduction system. following a positive return diagnosis. The means 24 are controlled on the other hand to deactivate the active noise reduction system following a negative feedback diagnosis.

The device 23 for controlling the active noise reduction system may be implemented by means of an electronic circuit of the FPGA (field of programmable gate array) type, ASIC (acronym for English Application -Specific Integrated Circuit for "application-specific integrated circuit") or other.

Advantageously, the device 23 is made using the resources of the on-board computer or a multimedia computer of the vehicle shared with the ANC algorithm, the radio and the mixer.

The memory of the computer used then contains a computer program, comprising program code means for performing all of the steps of the method set out below, when said program is running on a computer.

The program can thus be loaded on the computer at the factory in the form of a computer program product, comprising program code means, stored on a computer readable medium, for implementing the method set out below. , when the program product is running on a computer.

An example of a process according to the invention is now set out with reference to figure 2 .

• Niveau 1 : limitation de l'amplitude des signaux de commande envoyés aux haut-parleurs.
• Niveau 2 : utilisation d'informations provenant de l'environnement extérieur au système ANC.

First, a failure tree of the Active Noise Control System (ANC) is documented to determine the various possible causes of failure. On the basis of this analysis, a self-diagnosis procedure is established, preferably broken down into three levels of diagnosis:

• Level 1: limitation of the amplitude of the control signals sent to the loudspeakers.
• Level 2: Use of information from the environment outside the ANC system.

Level 3: A posteriori detection based on tests on the ANC signals of exit and entry, in particular of return.

The process starts in a step 100 when the active noise reduction system, powered up, receives a positive voltage Va of the battery 19.

Step 100 triggers a step 101 which consists in checking different states of the vehicle that allow or not to activate the algorithm ANC under the conditions for which it is intended.

The states can be binary as for example purely illustrative and non-exhaustive, door open or closed, glass closed or lowered, engine started or stopped.

It will be understood from the recalls given above on the predictive and counter-reaction algorithms that the effectiveness of the ANC algorithm is conditioned by a well-tuned agreement of FRF frequency response functions in the passenger compartment of the vehicle. These frequency response functions are disturbed by any modification of the cabin space, including the changes that result from an opening on the outside. It is therefore considered in step 101 that a correct state (OK abbreviated) of the opening of the vehicle corresponds to a closed position of the passenger compartment of the vehicle.

We have also seen above that the noise that is to be suppressed is a frequency or frequency spectrum noise determined by a measurable or calculable RPM rotation of a vehicle member, in particular of the power train 21 It will be understood that it is difficult to agree on a zero frequency in the absence of rotation of the motor. It is therefore considered in step 101 that a correct state (abbreviated OK) of the engine speed corresponds to an RPM value greater than a positive lower limit.

The states can also be quantified on a continuous or discrete scale when they relate to a temperature in the passenger compartment or to a vehicle occupancy rate.

To detect whether a state is correct or not, its value is read on the vehicle communication bus. A diagnostic variable Diag (E) is set when all the states E of the vehicle necessary for proper operation of the algorithm ANC are correct. The variable Diag (E) is set to zero as soon as a state E is not correct.

A step 103 is triggered if all states are detected correct in step 101 and a step 102 is turned on otherwise, in other words if at least one state is detected incorrectly.

Step 102 is to block any activation of the ANC algorithm, in other words not to enable or disable the ANC algorithm. Step 102 loops back to step 101 so that step 103 can be started as soon as all states are detected correctly in step 101.

Step 103 is to enable the activation of the ANC algorithm, in other words to activate or maintain the activation of the ANC algorithm.

An exit check step 110 and a return check step 130 are started from step 103.

Step 110 consists in establishing an output diagnostic by analyzing at least one output signal, in particular by verifying that the signals u _C, each intended for a loudspeaker 13, conform to pre-established criteria of amplitude, frequency and / or phase to suppress the noise in the passenger compartment 20 of the vehicle 12.

An example of step 110 according to the invention is described in more detail with reference to the figure 4 .

In step 110, a sub-step 111 is cyclically engaged as long as the ANC algorithm is activated, for example purely illustrative and nonlimiting after each activation of step 103. In the sub-step step 111, an index j is initialized to zero to designate the first loudspeaker 13 of a list containing a quantity Q _HP of loudspeakers 13.

For each execution cycle of substep 111, a substep 112 is repeated as many times as there are monitored speakers, in other words substep 112 is executed to verify the set. output signals of index j, j ranging from zero to Q _HP -1. A run cycle typically matches but not necessarily at a sampling period on the inputs or at a date of the fundamental frequency of the noise to be canceled.

Verification of an output signal in sub-step 112 as illustrated on the figure 4 , consists in ensuring that the amplitude | u _C (j) | the control signal of the loudspeaker 13 of index j, is less than a threshold value u predetermined _threshold .

The _threshold value is typically predetermined during tests on a prototype vehicle so as to cancel the noise in optimal conditions with a minimum margin above the noise actually observed. The sound power of the noise and therefore the _threshold value are generally a function of the load and the rotational speed of the engine, in other words the RPM regime. Different tests are then carried out for different RPM engine speeds during tests on the prototype vehicle. The adjusted _threshold values are then stored in an associative data structure indexed by the possible RPM engine speed values. The same possible RPM engine speed value can index several _threshold values _, each specially adjusted to one of the speakers 13 in relation to its range of octaves and its position in the vehicle. The data structure thus obtained is then duplicated on data carriers, for example readable by the on-board computer or any other computer of the vehicle so as to be usable on vehicles of the same type at the output of the production line.

The assurance on the amplitude of the noise canceling signal below the threshold value is intended in particular to prevent the cancellation signal from being greater than the noise to be canceled, with the opposite and disastrous effect of amplifying it. The amplitude test can be performed in real time in different ways.

A simple way is to compare the absolute value of the signal u _C (j) at each sampling period with the threshold value. In fact, any exceeding of the _threshold value by the signal u _C (j) indicates an amplitude greater than the value u _threshold . It is reasonable to consider that an amplitude greater than the threshold value causes a crossing of at least one sample of the signal u _C (j) when the sampling frequency is clearly greater than the Nyquist-Shannon frequency.

A more elaborate way is to raise the sampled signal squared and then filter it by a first-order filter with a time constant substantially greater than the period of the sampled signal. It will be recalled that the squaring of a first signal of sinusoidal nature generates a second signal comprising a DC component equal to the half-amplitude of the first signal and a sinusoidal component with a frequency double that of the first signal. The filtering of the double-frequency sinusoidal component with a sufficiently high time constant then leaves only the continuous component which it is sufficient to multiply by two to reproduce the amplitude of the first signal. It is also possible to take a second threshold value equal to half of the threshold value considered in the preceding paragraph and thus directly compare the output of the filter with the second threshold value without having to double the filtered signal. This second way, of course, with respect to the first way, has the advantage of not requiring a sampling frequency much higher than the Nyquist-Shannon frequency to guarantee the detection of at least one peak above the value threshold when the amplitude is greater. A sampling frequency at least equal to the Nyquist-Shannon frequency is then sufficient because it reproduces the entirety of the properties of the signal and consequently of its squaring. This second way also has another advantage which is that of filtering any inadvertent exceeding of the threshold value which could result for example from a parasite or a momentary accumulation of sound energy of several signals and not a real overrun amplitude.

Another more elaborate way is to find in the output signal, the amplitude of a component of the frequency signal ω ₀ / 2π corresponding to the expected frequency of the noise generated by the engine for a given RPM regime.

This third way of verifying the amplitude is particularly adapted to the signal u _HP coming from the mixer 17. In fact the signal comprises not only the frequency of the signal u _c theoretically equal to ω ₀ / 2π but also the frequencies of the signal u _R which scan at least the spectrum of audible frequencies by the human ear. The signal can also contain the frequency ω ₀ / 2π and this with an amplitude such that, added to that of the signal u _c , one obtains a total amplitude greater than the threshold value of the amplitude, with the risk of saturating the regulation of the ANC algorithm and consequently to cause non-linearities detrimental to the adaptive parameterization.

This third way of verifying the amplitude does not bring any particular advantage to the verification of the amplitude of the single signal u _c , the frequency of which is, unless the ANC algorithm itself is malfunctioning, equal to the frequency expected ω ₀ / 2π. In this case, the verification should not focus on the amplitude but more on the frequency itself, for which we will see a possible method below.

$$C=\frac{2}{T}{\displaystyle {\int }_{-T/2}^{T/2}{u}_{\mathit{HP}}\left(t\right).\sin \left({\omega }_{0}t\right)\mathit{dt}}$$

$$A=\sqrt{B^2+C^2}$$

The third way of verifying the amplitude is implemented by calculating an abscissa B and an ordinate C relating to an amplitude module A by means of the following formulas: $$B=\frac{2}{T}{\displaystyle {\int }_{-T/2}^{T/2}{u}_{\mathit{HP}}\left(t\right).\cos \left({\omega }_{0}t\right)\mathit{dt}}$$

$$\mathrm{VS}=\frac{2}{T}{\displaystyle {\int }_{-T/2}^{T/2}{u}_{\mathit{HP}}\left(t\right).\sin \left({\omega }_{0}t\right)\mathit{dt}}$$

$$\mathrm{AT}=\sqrt{{\mathrm{<figure-callout\; id="2"\; label="B"\; filenames="imgf0001.png"\; state="\{\{state\}\}">B</figure-callout>}}^2+{\mathrm{<figure-callout\; id="2"\; label="VS"\; filenames="imgf0001.png"\; state="\{\{state\}\}">VS</figure-callout>}}^2}$$

Whatever the manner of checking the amplitude chosen in the sub-step 112, a sub-step 113 is executed if the amplitude is not less than the amplitude threshold value and a sub-step 114 is executed if the amplitude is less than the threshold amplitude _{threshold value} .

In the sub-step 113, the amplitude of the signal is limited to the _threshold value u and a variable Diag (S) previously initialized to 1 for example in the sub-step 111, is set to zero.

In sub-step 114, the amplitude of the signal is maintained at its value and the variable Diag (S) retains its previous value.

Thus, it is necessary for the amplitudes of all the verified output signals to be lower than their respective threshold values for the Diag (S) variable to be maintained at 1 and all that is required is an output signal amplitude greater than its threshold value. to set the Diag (S) variable to zero.

The example of implementation illustrated by the figure 4 corresponds to a sequential execution of the method in which a substep 115 increments the index j following each execution of the substep 113 or the substep 114 to re-execute sub-step 112 as long as the index j is less than Q _HP . An end-of-cycle sub-step 117 is started as soon as a substep 116 detects that the index j reaches the number QHP of output signals to be checked.

Other implementations of the process than that illustrated by the figure 4 are possible. For example, in a multitasking or logic circuit implementation, a parallel execution of Q _HP checks each of an output signal, sets to 1 or 0 a distinct Diag (S) variable for each signal. A synthesis task or an AND gate then makes the product of all the Diag (S) variables to obtain a final value equal to 1 if all the checks are positive or a final value equal to 0 as soon as a check is negative.

Steps 112, 113 and 114 of the figure 4 illustrate a check on a maximum allowable amplitude of output signal.

Other output signal checks with or without correction are possible.

In particular, it can be verified whether or not the frequency of an output signal u ₂ (t) is close to the control frequency f = ω ₀ / 2π by means of an inter-correlation coefficient C _u1u2 (τ) of the following way.

An sinusoidal signal u ₁ (t) of frequency f = ω ₀ / 2π is arbitrarily generated.

$$E\left[u_1\left(t\right)u_1^{*}\left(t\right)\right]=\frac{1}{N}{\displaystyle \sum _{n=0}^{N-1}{u}_1\left(n\right)u_1\left(n\right)}$$

$$E\left[u_2\left(t\right)u_2^{*}\left(t\right)\right]=\frac{1}{N}{\displaystyle \sum _{n=0}^{N-1}{u}_2\left(n\right)u_2\left(n\right)}$$

Three mathematical expectations E [] are calculated using the following approximate formulas: $$E\left[u_1\left(\mathrm{<figure-callout\; id="2"\; label="t\; u"\; filenames="imgf0001.png"\; state="\{\{state\}\}">t\; </figure-callout>},\right)u_{}^{}{}_2^{*}\left(t+\tau \right)\right]=\frac{1}{\mathrm{NOT}}{\displaystyle \underset{\mathrm{not}=0}{\overset{\mathrm{NOT}-1-\left|\tau \right|}{\Sigma }}{\mathrm{<figure-callout\; id="1"\; label="u"\; filenames="imgf0001.png,imgf0002.png"\; state="\{\{state\}\}">u</figure-callout>}}_1\left(\mathrm{not}\right){\mathrm{<figure-callout\; id="2"\; label="u"\; filenames="imgf0001.png"\; state="\{\{state\}\}">u</figure-callout>}}_2\left(\mathrm{not}+\left|\tau \right|\right)}$$

$$E\left[u_1\left(\mathrm{<figure-callout\; id="1"\; label="t\; u"\; filenames="imgf0001.png,imgf0002.png"\; state="\{\{state\}\}">t\; </figure-callout>},\right)u_{}^{}{}_1^{*}\left(t\right)\right]=\frac{1}{\mathrm{NOT}}{\displaystyle \underset{\mathrm{not}=0}{\overset{\mathrm{NOT}-1}{\Sigma }}{\mathrm{<figure-callout\; id="1"\; label="u"\; filenames="imgf0001.png,imgf0002.png"\; state="\{\{state\}\}">u</figure-callout>}}_1\left(\mathrm{not}\right){\mathrm{<figure-callout\; id="1"\; label="u"\; filenames="imgf0001.png,imgf0002.png"\; state="\{\{state\}\}">u</figure-callout>}}_1\left(\mathrm{not}\right)}$$

$$E\left[u_2\left(\mathrm{<figure-callout\; id="2"\; label="t\; u"\; filenames="imgf0001.png"\; state="\{\{state\}\}">t\; </figure-callout>},\right)u_{}^{}{}_2^{*}\left(t\right)\right]=\frac{1}{\mathrm{NOT}}{\displaystyle \underset{\mathrm{not}=0}{\overset{\mathrm{NOT}-1}{\Sigma }}{\mathrm{<figure-callout\; id="2"\; label="u"\; filenames="imgf0001.png"\; state="\{\{state\}\}">u</figure-callout>}}_2\left(\mathrm{not}\right){\mathrm{<figure-callout\; id="2"\; label="u"\; filenames="imgf0001.png"\; state="\{\{state\}\}">u</figure-callout>}}_2\left(\mathrm{not}\right)}$$

The correlation coefficient C _u1u2 (τ) between the two signals u ₁ (t) and u ₂ (t) is then calculated using the following formula: $${\mathrm{VS}}_{u_1{\mathrm{<figure-callout\; id="2"\; label="u"\; filenames="imgf0001.png"\; state="\{\{state\}\}">u</figure-callout>}}_2}\left(\tau \right)=\frac{E\left[u_1\left(\mathrm{<figure-callout\; id="2"\; label="t\; u"\; filenames="imgf0001.png"\; state="\{\{state\}\}">t\; </figure-callout>},\right)u_{}^{}{}_2^{*}\left(t+\tau \right)\right]}{\sqrt{E\left[u_1\left(\mathrm{<figure-callout\; id="1"\; label="t\; u"\; filenames="imgf0001.png,imgf0002.png"\; state="\{\{state\}\}">t\; </figure-callout>},\right)u_{}^{}{}_1^{*}\left(t\right)\right]}\sqrt{E\left[u_2\left(\mathrm{<figure-callout\; id="2"\; label="t\; u"\; filenames="imgf0001.png"\; state="\{\{state\}\}">t\; </figure-callout>},\right)u_{}^{}{}_2^{*}\left(t\right)\right]}}$$

The correlation coefficient C _u1u2 (τ) thus obtained is compared with a threshold value coefficient, for example equal to 0.9.

If the inter-correlation coefficient C _u1u2 (t) is not greater than the threshold coefficient, the variable Diag (S) is set to zero to signify that the frequencies of the two signals u ₁ (t) and u ₂ (t) are not close enough to each other.

In particular, it can be verified whether the phase of an output signal u _C (t) varies over time. Knowing the period T equal to the inverse of the frequency f = ω ₀ / 2π of the signal u _C (t), the values of the signal u _C (t) are compared to two times separated by a period T.

For example, the difference u'c (t + T) is evaluated: $$\mathrm{u}{\text{'}}_{\mathrm{VS}}\left(\mathrm{t}+\mathrm{T}\right)={\mathrm{u}}_{\mathrm{VS}}\left(\mathrm{t}+\mathrm{T}\right)-{\mathrm{u}}_{\mathrm{VS}}\left(\mathrm{t}\right)$$

A non-zero difference then makes it possible to detect a phase variation.

For example, the difference u " _C (t + T): $${\mathrm{u\; "}}_{\mathrm{VS}}\left(\mathrm{t}+\mathrm{T}\right)={\mathrm{u}}_{\mathrm{VS}}\left(\mathrm{tT}\right)-2{\mathrm{u}}_{\mathrm{VS}}\left(\mathrm{t}\right)+{\mathrm{u}}_{\mathrm{VS}}\left(\mathrm{t}+\mathrm{T}\right)$$

A non-zero difference then makes it even better to detect a variation in phase variation.

Those skilled in the art will of course take the usual precautions in terms of filtering to avoid unwanted phase variation detections so as to position the variable Diag (S) to zero in the event of detection of known phase variation.

The variable Diag (S) is then evaluated in the substep 117 after having made all the checks provided on all the output signals to be checked. The positive escapement of sub-step 117 when the variable Diag (S) is at 1 corresponds to the positive escape of step 110 and the negative escape of substep 117 when the variable Diag (S) is at 0 corresponds to the negative exhaust of step 110.

The positive exhaust of step 110 leads to a continuation of the process without taking particular measurement so as to allow a re-execution of step 103 following a positive output diagnostic, for example as illustrated in FIG. figure 2 by looping back to step 101 when the variable Diag (S) is equal to 1.

The negative escape of step 110 triggers a step 120 of testing the occurrences of the variable Diag (S) equal to zero so as to make executable a step 104 of neutralization of the algorithm ANC when the occurrences of Negative output diagnostics are considerable. Step 104 then essentially consists in deactivating the active noise reduction system, preferably at least until a new start of step 100 by powering up after powering off, or even until further control is performed. in after sales service.

Step 120 essentially consists in detecting whether the non-escaping Diag (S) variable of step 110 reflects a failure that occurs over a length T _{DIAG = 0 that is} too long. The duration T _{DIAG = 0} is estimated to be too long if it exceeds a predetermined duration T _TIME during the prototype vehicle test phases and possibly adjustable to sensitize or desensitize the ANC deactivation in the presence of failures. We will see later in the description a possibility of determining a duration T _THRESHOLD common to the outputs and returns. When determining a duration T _THRESHOLD equal to a duration Ts (S) specific to the outputs, the following test is carried out on a duration Tdef (S) of zero diagnostic specific to the outputs: $$\mathrm{Tdef}\left(\mathrm{S}\right)={\mathrm{T}}_{\mathrm{DIAG}=0}>{\mathrm{T}}_{\mathrm{THRESHOLD}}=\mathrm{ts}\left(\mathrm{S}\right)$$

Step 120 can be implemented in different ways.

A first way is simply to increment a counter at each occurrence of a zero value of the variable Diag (S) during an observation period equal to T _THRESHOLD counted from the first occurrence of the variable Diag (S) to zero . If the observation time is reached or exceeded without the contents of the counter corresponding to a number of all zero occurrences of the variable Diag (S), the counter is reset. This first way, if it has the merit of being simple, is not entirely satisfactory because each reset of the counter causes erasure of past events in terms of failure detection.

Advantageously, a second way is to apply a first order filter with a time constant a on the variable DIAG = Diag (S) to obtain a filtered variable DF: $$\mathit{DF}=\frac{1-\mathrm{at}}{1-\mathrm{at}.z^{-1}}\mathit{DIAG}$$

The figure 5 presents a temporal evolution curve of the DIAG variable in the upper part and a temporal evolution curve of the DF variable in the lower part.

When at a time t ₀ , the variable DIAG initially at the value 1, passes to the value 0, the variable DF until then to the value 1, decreases with the time constant a until reaching a threshold ε of detection null at a time t ₂ provided that the variable DIAG remains at zero.

If at a time t ₁ later than the instant t ₀ and which precedes the instant t ₂ , the variable DIAG returns from the value 0 to the value 1, the variable DF then to a value less than 1, increases with the constant time until the variable DIAG returns to zero at a time t ₃ . When, at time t ₃ , the variable DIAG passes to the value 0, the variable DF then at a value greater than that reached at time t ₁ decreases with the time constant a until it reaches the threshold ε zero detection at a time t ₆ significantly greater than the instant t ₂ . It should be noted here that the raising of the variable DIAG to 1 during a period t ₃ -t ₁ , causes the threshold ε of zero detection to be crossed with a delay t ₆ - t _{3 that is} clearly greater than the duration t ₃ - t ₁ during which the variable DIAG is returned to 1.

Although the probability of such a phenomenon occurring is very small, one solution may be to lower the time constant a or to raise the threshold ε of zero detection.

The figure 6 presents a temporal evolution curve of the variable DF when the filter is applied only if the variable DIAG is at zero and the variable DF remains fixed if the variable DIAG is at 1.

This second way of filtering the zero crossings of the variable DIAG is well adapted to the example of implementation of the method illustrated by the figure 2 . The filter is applied in step 120 only in the event of escape from step 110 with a zero value of the variable DIAG equal to the variable Diag (S). As long as step 110 loops back to step 101 with a unit value of the variable Diag (S), the variable DF is not changed in step 120.

When at a time t ₁ after the instant t ₀ and which precedes the instant t ₂ , the variable DIAG returns from the value 0 to the value 1, the variable DF then at a value less than 1, retains this value until the variable DIAG returns to zero at a time t ₃ . When, at time t ₃ , the variable DIAG passes to the value 0, the variable DF then at a value equal to that reached at time t ₁ decreases with the time constant a until it reaches the threshold ε zero detection at a time t ₄ greater than the instant t ₂ but very close to the instant t ₃ . It should be noted here that the raising of the DIAG variable to 1 during the duration t ₃ - t ₁ causes the threshold ε of zero detection to be crossed with a delay t ₄ - t _{3 that is well} below the duration t ₃ - t ₁ during which the variable DIAG is returned to 1. It is thus avoided that the DIAG variable's up-to-1 occurrences inadvertently hide zero crossings whose occurrences indicate a system failure.

However, we observe on the figure 6 that if the variable DIAG remains at 1 for a duration t ₇ - t ₁ clearly greater than t ₁ - t ₀ , the variable DF persists in crossing the threshold ε of detection zero at an instant t ₈ greater than the instant t ₇ but nevertheless as close to time t ₇ as time t ₄ is at time t ₃ . We note here a memory effect of the zero crossings of the variable DIAG which, even of negligible durations before those of passages to 1 of this same variable DIAG, have the effect of making the variable DF fall below the threshold of detection nil by a short transition to zero DIAG variable after a time more or less long and completely unpredictable.

The figure 7 presents a temporal evolution curve of the variable DF when the filter is applied if the variable DIAG is at zero with a time constant a of value lower than if the variable DIAG is at 1.

This third way of filtering the zero crossings of the variable DIAG poses no particular difficulty of realization because the variable DIAG being a binary logical variable, it suffices to type the time constant a in the form of parameter instantiated at a first low value when the variable DIAG is at 0 and at a second high value when the variable DIAG is at 1. The application of the filter during the ascent of the variable can be carried out in a step not represented on the figure 2 but that is easily located between step 110 and step 101.

When at time t ₁ , the variable DIAG returns from the value 0 to the value 1, the variable DF then to a value less than 1, increases until the variable DIAG returns to zero at a time t ₃ . When at time t ₃ , the variable DIAG passes to the value 0, the variable DF then to a value greater than that reached at time t ₁ but less than that reached at the same time on the figure 5 because of the higher value time constant, decreases with the time constant a of low value to reach the threshold ε of detection zero at a time t ₅ greater than the instant t ₂ but less than the instant t ₆ of the figure 5 . It is noted here that the raising of the variable DIAG to 1 during the duration t ₃ - t ₁ , causes a crossing of the threshold ε of detection zero with a delay t ₅ - t ₁ much lower than the duration t ₆ - t ₁ of the figure 5 . Compared to the first way of filtering, it is thus easier to avoid that the DIAG variable's 1-up-ups inadvertently mask zero crossings, the occurrences of which show a failure of the system. Compared to the second way of filtering, it is also avoided that descents to 0 of the variable DIAG do not inadvertently hide a predominance of the passages to 1 whose occurrences testify to an acceptable functioning of the system because the time constant has, well that of high value at the ascent, leads to a duration t ₉ - t ₁ of reaching the threshold ε of null detection higher than the duration t ₈ -t ₁ when the duration t ₇ - t ₁ is definitely greater than the duration t ₁ - t ₀ .

A negative escape of step 120, as long as the negative diagnosis has not persisted long enough, loops back to step 101 at the rate of the signal samplings.

Step 130 consists in establishing a return diagnosis by analyzing at least one return signal, in particular by verifying that the u _mic signals each coming from a microphone 11, comply with pre-established criteria of amplitude, frequency and / or phase according to the noise suppression expected in the passenger compartment 20 of the vehicle 12.

An example of step 130 according to the invention is described in more detail with reference to the figure 3 .

In step 130, a substep 131 is cyclically engaged as long as the ANC algorithm is activated, for example purely illustrative and not limiting, following each activation of step 103. step 131, an index i is initialized to zero to designate the first microphone 11 of a list containing a _microphone Q quantity Q 11.

For each cycle of execution of the substep 131, a substep 132 is repeated as many times as there are controlled microphones, in other words the substep 132 is executed to check all the signals. output of index i, i ranging from zero to Q _micro -1. A run cycle typically matches but not necessarily at a sampling period on the inputs or at a date of the fundamental frequency of the noise to be canceled.

Verification of an output signal in sub-step 132 as illustrated on the figure 3 , consists in ensuring that the amplitude | u _mic (i) | of the signal picked up by the microphone 11 of index i, is less than a predetermined threshold value u _maxi .

The _maximum value u is typically predetermined during tests on a prototype vehicle in agreement with a sound level bearable by the human ear. The sound power of the noise and thus the _maximum value u are generally based on the rotation speed and engine load, in other words RPM regime. Different tests are then carried out for different RPM engine speeds during tests on the prototype vehicle. The adjusted _max u values are then stored in an associative data structure indexed by the possible RPM engine speed values. The same possible value of RPM engine speed can index several u _max values, each specially adjusted to one of the microphones 11 in relation to its sensitivity and position in the vehicle. The data structure thus obtained is then duplicated on data carriers, for example readable by the on-board computer or any other computer of the vehicle so as to be usable on vehicles of the same type at the output of the production line.

The assurance on the amplitude of the signal captured below the maximum value, is intended in particular to avoid a feedback effect with the opposite and disastrous effect of unpleasantly amplifying the noise. The amplitude test can be performed in real time in different ways.

A simple way is to compare the absolute value of the _micro signal (i) at each sampling period with the threshold value. Indeed, any exceeding of the _maximum value u by the signal u _micro (i) indicates an amplitude greater than the value u _micro (i).

It is possible to perform a finer analysis of the maximum value on the microphone signal. Indeed, the error microphone 11 measures a broadband noise, in other words a noise spectrum over a wide frequency range. The active reduction algorithm aims to remove only the noise component at the expected frequency of being canceled. This filtering operation is implicitly performed in the body of the algorithm. But it is possible to perform it also by a simple operation.

ou encore : $$u_{\mathit{micro}}\left(t\right)={\displaystyle \sum _n{B}_n\cos \left(\mathit{n\omega t}\right)+C_n\sin \left(\mathit{n\omega t}\right)}$$

$$\omega =2\pi /T$$

avec T : période du signal u_micro(t)It is recalled that, in general, the signal measured by the microphone can be decomposed into a Fourier series. It is written as: $$u_{\mathit{microphone}}\left(t\right)={\displaystyle \underset{\mathrm{not}}{\Sigma }{\mathrm{AT}}_{\mathrm{not}}\cos \left(\mathit{n\omega t}+\phi \right)}$$

or : $$u_{\mathit{microphone}}\left(t\right)={\displaystyle \underset{\mathrm{not}}{\Sigma }{B}_{\mathrm{not}}\cos \left(\mathit{n\omega t}\right)+{\mathrm{VS}}_{\mathrm{not}}\sin \left(\mathit{n\omega t}\right)}$$

$$\omega =2\pi /T$$

with T: signal period u _micro (t)

$$C_n=\frac{2}{T}{\displaystyle {\int }_{-T/2}^{T/2}{u}_{\mathit{micro}}\left(t\right).\sin \left(\mathit{\omega nt}\right)\mathit{dt}}$$

The coefficients of this series are given by the relations: $$B_{\mathrm{not}}=\frac{2}{T}{\displaystyle {\int }_{-T/2}^{T/2}{u}_{\mathit{microphone}}\left(t\right).\cos \left(\mathit{\omega nt}\right)\mathit{dt}}$$

$${\mathrm{VS}}_{\mathrm{not}}=\frac{2}{T}{\displaystyle {\int }_{-T/2}^{T/2}{u}_{\mathit{microphone}}\left(t\right).\sin \left(\mathit{\omega nt}\right)\mathit{dt}}$$

In the case where we want to extract the component of the signal at the control frequency f = ω ₀ / 2π , we consider only the component which is written in the form $$u_{\mathit{microphone}}\left(t\right)=\mathrm{AT}\sin \left({\omega }_{0}t+\phi \right)$$

avec B, C calculés grâce aux relations suivantes : $$B=\frac{2}{T}{\displaystyle {\int }_{-T/2}^{T/2}{u}_{\mathit{micro}}\left(t\right).\cos \left({\omega }_{0}t\right)\mathit{dt}}$$

$$C=\frac{2}{T}{\displaystyle {\int }_{-T/2}^{T/2}{u}_{\mathit{micro}}\left(t\right).\sin \left({\omega }_{0}t\right)\mathit{dt}}$$

Which is rewritten again in the following form $$u_{\mathit{microphone}}\left(t\right)=B\cos \left({\omega }_{0}t\right)+\mathrm{VS}\sin \left({\omega }_{0}t\right)$$

with B, C calculated using the following relationships: $$B=\frac{2}{T}{\displaystyle {\int }_{-T/2}^{T/2}{u}_{\mathit{microphone}}\left(t\right).\cos \left({\omega }_{0}t\right)\mathit{dt}}$$

$$\mathrm{VS}=\frac{2}{T}{\displaystyle {\int }_{-T/2}^{T/2}{u}_{\mathit{microphone}}\left(t\right).\sin \left({\omega }_{0}t\right)\mathit{dt}}$$

Cette amplitude varie en fonction du régime moteur A. De manière générale, on a A = A(RPM). The total amplitude A of the signal at the frequency f is then such that $\mathrm{AT}=\sqrt{{\mathrm{<figure-callout\; id="2"\; label="B"\; filenames="imgf0001.png"\; state="\{\{state\}\}">B</figure-callout>}}^2+{\mathrm{<figure-callout\; id="2"\; label="VS"\; filenames="imgf0001.png"\; state="\{\{state\}\}">VS</figure-callout>}}^2}.$

This amplitude varies according to the engine speed A. In general, we have A = A ( RPM ) .

In this case, the test on the simple instantaneous module of the signal mentioned in the preceding paragraph is replaced by a test which consists in checking, at a given RPM engine speed in real time, that the amplitude A (RPM) measured by the microphone is less than a threshold amplitude defined for this same engine speed: $$\mathrm{AT}\left(\mathit{RPM}\right)<{\mathrm{AT}}^{\mathit{threshold}}\left(\mathit{RPM}\right)$$

This second maximum amplitude test is more interesting than the first maximum amplitude test explained above because an anomaly, in other words a threshold overshoot, is detected only at the control frequency f, for a RPM regime. given. It should be borne in mind that the error microphone 11 measures at each moment a pressure value which is a mean value while the pressure fluctuation is the superposition of all the frequency contributions as expressed by the Fourier decomposition . But only the fluctuation of pressure at the control frequency interests us. Therefore, if the pressure level measured by the error microphone results from broadband excitation or mono-frequency excitation but at a frequency different from the control frequency, the first maximum amplitude test detects a error while the second maximum amplitude test does not detect it. But the purpose of active noise reduction is to remove only the component of the signal that is at the control frequency. The detection of a fault only makes sense at this frequency.

Whatever the manner of checking the maximum permitted amplitude chosen in sub-step 132, a sub-step 133 is executed if the amplitude is less than the amplitude threshold value and a sub-step 134 is executed if the amplitude is not less than the threshold value of amplitude u _max .

In the sub-step 133, it is verified that the microphone 11 of index i is operational, in other words that it actually captures a non-zero signal.

At each instant t of passage in step 133, a criterion C1 _mic (i) is calculated which measures a plurality of variations of the signal _mic (i, t) discretized by time intervals Δt on the N samplings preceding the instant current, in other words over a period of observation T = NΔt, by means of the formula: $$\mathrm{<figure-callout\; id="1"\; label="VS"\; filenames="imgf0001.png,imgf0002.png"\; state="\{\{state\}\}">VS</figure-callout>}{1}_{\mathit{mic}}\left(i\right)={\displaystyle \underset{k=0}{\overset{\mathrm{NOT}-1}{\Sigma }}\left|u_{\mathit{mic}}\left(i,t-k\mathrm{\Delta }t\right)-u_{\mathit{mic}}\left(i,t-\left(\mathrm{<figure-callout\; id="1"\; label="k\; +"\; filenames="imgf0001.png,imgf0002.png"\; state="\{\{state\}\}">k\; </figure-callout>}+1\right)\mathrm{\Delta }t\right)\right|}$$

We then check the criterion C1 _mic (i)> C1 _min . If no signal is measured by the microphone, the value of C1 _mic (i) is very low. The value of the lower bound C1 _mini is also determined during prototype system tests. The advantage of this criterion is that it does not depend on the average value of the signal and that it is quite simple to calculate.

In the example of implementation of the method illustrated by the figure 3 a sub-step 136 is executed if the criterion C1 _mic (i)> C1 _min is found and the sub-step 134 is executed in the opposite case.

In step 134, the variable Diag (R) is set to zero so that a negative response to one of the verification steps 132 or 133 is sufficient to set the variable Diag (R) to zero and the variable Diag (R) remains at 1 if and only if all the responses to verification steps 132 and 133 are positive.

The example of implementation illustrated by the figure 3 corresponds to a sequential execution of the method in which the substep 136 increments the index i to following each execution of the substep 133 or substep 134 to re-execute the substep 132 as long as the substep index i is less than Q _micro . An end-of-cycle sub-step 138 is triggered as soon as a sub-step 137 detects that the index i reaches the _micro number Q of return signals to be checked.

Other implementations of the process than that illustrated by the figure 3 are possible. In particular, the order of execution of steps 132 and 133 can be reversed or their execution can be done in parallel. For example still in a multitasking or logic circuit implementation, a parallel execution of Q _micro tasks each verification of a feedback signal, sets to 1 or 0 a distinct Diag (R) variable for each signal. A synthesis task or an AND gate then makes the product of all Diag (R) variables to obtain a final value equal to 1 if all the checks are positive or a final value equal to 0 as soon as a check is negative.

The variable Diag (R) is then evaluated in the substep 138 after having made all the checks provided on all the return signals to be checked. The positive escape of the substep 138 when the variable Diag (R) is at 1 corresponds to the positive escape of the step 130 and the negative escape of the substep 138 when the variable Diag (R ) is 0 corresponds to the negative exhaust of step 130.

The positive exhaust of step 130 leads to a continuation of the process without taking a particular measurement so as to allow a re-execution of step 103 following a positive feedback diagnosis, for example as illustrated in FIG. figure 2 by looping back to step 101 when the variable Diag (R) is equal to 1.

The negative exhaust of step 130 triggers a step 140 of testing the occurrences of the variable Diag (R) equal to zero so as to make executable the step 104 of neutralization of the algorithm ANC when the occurrences of diagnostic return negative are considerable.

Step 140 essentially consists in detecting whether the non-escaping Diag (R) variable of step 130 reflects a failure that occurs over a too long duration T _DIAG-0 . The duration T _DIAG-0 is considered too long if it exceeds a predetermined duration T _THRESHOLD during the prototype test phases of the vehicle. The duration T _THRESHOLD may be adjustable to sensitize or desensitize the ANC deactivation in the presence of failures. We will see later in the description a possibility of determining a duration T _THRESHOLD . common to outputs and returns. When determining a duration T _THRESHOLD equal to a duration Ts (R) specific to the outputs, the following test is carried out on a test time Tdef (R) null specific to the outputs: $$\mathrm{Tdef}\left(\mathrm{R}\right)={\mathrm{T}}_{\mathrm{DIAG}=0}>{\mathrm{T}}_{\mathrm{THRESHOLD}}=\mathrm{ts}\left(\mathrm{R}\right)$$

Step 140 can be implemented in different ways on the model of those of step 120.

A negative escape of step 140, as long as the negative diagnosis has not persisted long enough, loops back to step 101 at the rhythm of the signal samplings.

As we have just seen, a step 120 distinct from the step 140 makes it possible to determine a threshold duration Ts (S) that is customized for the occurrences of the negative output diagnostics and a threshold duration Ts (R) that is customized for the occurrences of the diagnostics. negative output of different values.

If the values of the threshold durations Ts (S) and Ts (R) are identical, steps 120 and 140 can be grouped in a single step in which the occurrences of exit and return diagnostics are nevertheless considered separately or are considered at the same time. title, in other words in the latter case, a Negative diagnosis is considered an occurrence regardless of whether it relates to an exit or a return.

The invention just described meets the objective of preventing, in use, that the ANC system causes inconvenience to the user when the system becomes defective, for example because a microphone or speaker is down. We have seen how the invention makes it possible to prevent the loudspeakers of the vehicle from emitting a loud sound when the system fails. The invention thus makes it possible to detect the appearance of the fault in a very short time and to find an adequate correction.

The detection is robust in that it does not fire unexpectedly.

This simple solution makes it possible to deal with all the failures identified in the fault tree. Since it is general enough not to depend on the particular origin of the failure, it has the potential to deal with other unidentified failures so far.

Claims (12)

1. Method for controlling an active noise cancelling system comprising one or more loudspeakers (13) for producing one or more sound output signals which oppose the noise and one or more microphones (11) for picking up one or more return signals which measure the noise reduction obtained, characterized in that it comprises:

   - a step (103) of activation of the active noise cancelling system;

   - a return verification step (130);

   - which establishes a return diagnosis by analyzing at least one return signal in a low detection substep (132) which calculates an operative return criterion (C1) and which renders the return diagnosis negative when corresponding to an aggregate of variations of the return signal over a given time interval, at least one return signal does not satisfy a minimum value of the operative return criterion (C1); and

   - which allows a re-execution of the step (103) following a positive return diagnosis;

   - a neutralization step (104) which can be executed following a negative return diagnosis and which deactivates the active noise cancelling system.
2. Controlling method according to Claim 1, characterized in that the return verification step (130) comprises a high detection substep (133) which renders the return diagnosis negative when at least one return signal is not lower than a maximum amplitude value.
3. Controlling method according to either of the preceding claims, characterized in that it comprises:

   - an output verification step (110) in which an output diagnosis is established by analyzing at least one output signal, which allows a re-execution of the step (103) following a positive output diagnosis and which renders the neutralization step (104) executable following a negative output diagnosis so as to then deactivate the active noise cancelling system.
4. Controlling method according to Claim 3, characterized in that the output verification step (110) comprises a high detection substep (112) which renders the output diagnosis negative when at least one output signal is not below a maximum amplitude threshold.
5. Controlling method according to either of Claims 3 and 4, characterized in that the output verification step (110) comprises a substep (113) of limiting the amplitude of the output signal to a maximum threshold.
6. Controlling method according to one of the preceding claims, characterized in that it comprises a moderation step (120, 140) which allows a re-execution of the step (103) following a negative output or return diagnosis as long as there is not a sufficient number of negative output or return diagnosis occurrences, notably as long as said diagnosis is not negative over a sufficient duration and which triggers the neutralization step (104) when there is a sufficient number of negative output or return diagnosis occurrences, notably when said diagnosis is negative over a sufficient duration.
7. Controlling method according to one of the preceding claims, characterized in that it comprises a step (101) of monitoring the state of an environment of the active noise cancelling system which allows the activation of the active noise cancelling system only when said environment is in a state compatible with said activation.
8. Device (23) for controlling an active noise cancelling system (15) comprising one or more loudspeakers (13) for producing one or more sound output signals which oppose the noise, one or more microphones (11) for picking up one or more return signals which quantify the noise reduction obtained, and means (24) for activating and neutralizing the active noise cancelling system (15) that are driven to activate, respectively deactivate, the active noise cancelling system following a positive return diagnosis, respectively following a negative return diagnosis, characterized in that it comprises:

   - return verification means arranged for calculating an operative return criterion (C1) corresponding to an aggregate of variations of the return signal over a given time interval, and for establishing a return diagnosis by analyzing at least one return signal (u_mic) so as to render the return diagnosis negative when at least one return signal does not satisfy a minimum value of the operative return criterion (C1).
9. Device (23) according to Claim 8, characterized in that said return verification means are arranged to render the return diagnosis negative when at least one return signal (u_mic) is not lower than a maximum amplitude value.
10. Computer program, comprising program code means for performing all the steps of any one of Claims 1 to 7, when said program runs on a computer.
11. Computer program product, comprising program code means, stored on a computer-readable medium, for implementing the method according to any one of Claims 1 to 7, when said program product runs on a computer.
12. Vehicle (12) in which an active noise cancelling system (15) in a vehicle interior (20) comprises one or more loudspeakers (13) for producing one or more sound output signals which oppose the noise and one or more microphones (11) for picking up one or more return signals which quantify the noise reduction obtained, characterized in that it comprises a controlling device (23) according to either of Claims 8 and 9 mounted in such a way as to control the active noise cancelling system.

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