JP3460587B2 - Abnormality detector that detects abnormality of the rotation angle detector - Google Patents

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a device for detecting an abnormality of a rotation angle detection device based on a modulation signal which is a modulation component included in an output signal from a resolver according to a rotation angle of a rotating machine.

[0002]

2. Description of the Related Art A resolver for detecting a rotation angle of a rotor of a rotating machine is known. The rotation angle detected by the resolver is
It is used for controlling the electric current of the rotating machine. When a sine wave sinωt signal is input as a reference signal to the primary winding of the resolver, the two secondary windings arranged with a phase difference of 90 ° output signals modulated according to the rotor rotation angle θ. sinωtsinθ and sinωtcosθ are obtained. For example, an R / D converter (resolver / digital converter) has a reference rotation angle φ controlled by a voltage controlled oscillator.
From the resolver output signal including the rotor rotation angle θ and the signals sinφ and cosφ according to the above, sin (θ−φ) is calculated, and the phase difference (θ−φ) is set to zero. PLL (Phase Locked Loop) control for increasing / decreasing the value is performed. Then, φ in the state where the PLL control is converged, that is, in the state of (θ−φ) = 0 is detected and output as the value of the rotor rotation angle θ.

Also, the R / D converter determines that the count value φ has become zero and outputs a Z-phase signal. Z
One pulse appears in the phase signal for each rotation of the rotating machine.

In order to detect an abnormality in the rotation angle detecting device for detecting the rotation angle θ by the above R / D converter, an abnormality detecting device for separately processing the output signal of the resolver is provided.

In this abnormality detecting device, in order to extract the information of θ contained in the output signal of the resolver, the reference signal component is removed and the modulation signal sin which is amplitude-modulated
Detection is performed to extract θ and cos θ. Between these two modulation signals, sin ² θ + cos ²
The relationship of θ = 1 holds. Conventionally, the sum of squares of sin θ and cos θ extracted by detection is calculated, and an abnormality such as disconnection of the harness of the resolver output signal is detected due to fluctuations such that the sum of squares falls below a predetermined threshold. It was

Here, (sin ² θ + cos ² θ) = 1 should be equally established, but in reality, not only when the rotation angle detection circuit is abnormal, but also when it is normal, it will be described below. For this reason, the above evaluation formula may not always be 1. The first cause is an error generated in the detection processing of the modulation signal. The modulation signals sin θ and cos θ are extracted by sequentially sampling the values of the output signal corresponding to the peak position (phase ωt = ± π / 2) of the reference signal sinωt. Here, regarding the determination of the peak position of the reference signal, the threshold value is set to a level whose absolute value is slightly smaller than the amplitude of the reference signal, and the point at which the reference signal exceeds the threshold value (when the peak on the negative side is captured, , The threshold value was set to a negative value, and the point at which the reference signal fell below the threshold value was used as the approximate peak position. Then, the sampling operation of the A / D converter (analog-digital converter) is started at that timing, the output signal is sampled and converted into a digital value, and this is set as the value at the peak position. Therefore, since the sampling positions of sin θ and cos θ are not exactly the peak positions of the reference signal, the evaluation formula (si
The value of (n ² θ + cos ² θ) is generally smaller than 1. That is, when the sampling position is ωt = (± π / 2−ε), the value of the reference signal sinωt at that point is ± cosε,
The sampling values of the output signals sinωtsinθ and sinωtcosθ are ± cosεsinθ and ± cosεcosθ, respectively, and the sum of squares is cos ² ε, which is generally smaller than 1.

The second possible cause is fluctuations in the amplitude of the reference signal. The amplitude of the reference signal may change due to a change in the circuit constant of the oscillator that generates the reference signal depending on the external temperature or a change in the power supply voltage. Note that this fluctuation is generally a long time cycle as compared with the rotation cycle of the rotating machine. At the timing of instructing to start the sampling operation of the A / D converter, the value of the reference signal is equal to the peak detection threshold value regardless of the fluctuation of its amplitude. However, the smaller the amplitude, the smaller the amount of change in the value of the reference signal in the time from the timing at which the threshold is exceeded to the timing at which actual sampling is performed. Therefore, the absolute values of the sampling values of the output signals sinωtsinθ and sinωtcosθ also become smaller as the amplitude of the reference signal becomes smaller.

As described above, the sum of squares is not always 1 even in the normal state, and may vary. Therefore, the threshold value for abnormality determination based on the sum of squares is set to a value that does not cause erroneous detection in consideration of this fact.

In the abnormality detection based on the sum of squares,
The large processing load required for the calculation of the evaluation formula (sin ² θ + cos ² θ) is due to, for example, the CPU (Central Process) used.
It may be a problem depending on the ability of (sing Unit). Therefore, the following method is used to approximately utilize the relationship of constant sum of squares and reduce the processing load on the CPU. In that method, instead of the sum of squares, each modulated signal is full-wave rectified to obtain each absolute value, and after adding them, a low-pass filtered signal is used. The smoothed signal (| sin θ | + | cos θ |) to which the absolute value is added falls below a predetermined threshold value, whereby the above abnormality is detected.

In this case, the evaluation formula (| sin θ | + | cos
θ |) does not take a constant value in principle, unlike the sum of squares. Therefore, the threshold value or the range of the evaluation value to be determined to be normal should be set more gently than the sum of squares.

[0011]

In the conventional abnormality detection method based on the sum of squares of modulated signals, the threshold value cannot be set sufficiently close to 1 as described above. In other words, this anomaly detection method cannot sufficiently narrow the normal range of the evaluation value defined by the threshold value, and fluctuations due to an abnormality of the rotation angle detection device are likely to fall within the normal range. However, there is a problem in that even if such an abnormality occurs, it cannot be detected, that is, the detection accuracy cannot be improved.

The problem of the conventional method based on the sum of squares described above similarly occurs in the abnormality detection method based on the signal obtained by smoothing (| sin θ | + | cos θ |). In particular, in this method, although the processing load can be reduced, the range of the evaluation value to be judged to be normal must be made gentler than the method using the sum of squares, and the detection accuracy is generally lower than the method using the sum of squares.

Further, when the rotating machine is stopped, there is a problem that a dead zone for abnormality detection may occur depending on the rotational position of the resolver. For example, cos of the output signal from the resolver
If the signal wiring related to θ is disconnected and stopped near θ where sin θ = 1, the rotating machine starts rotating and si
No abnormality is detected until nθ becomes small and the evaluation value deviates from the normal range.

It is an object of the present invention to solve the above problems and provide an abnormality detecting device capable of improving the accuracy of abnormality detection.

[0015]

SUMMARY OF THE INVENTION An anomaly detection apparatus according to the present invention eliminates asymmetry between fluctuations of the modulation signal above the reference level of the modulation signal and fluctuations of the modulation signal below the reference level. means for detecting, that having a means for determining the abnormality based on the asymmetry.

The modulation signal fluctuates according to the rotation angle, and its value has a characteristic of fluctuating up and down around a certain reference level with one rotation of the rotation angle to restore the initial value. According to the property of this modulation signal, the modulation signal swings up and down with the same amplitude from the reference level during one rotation of the rotation angle, and, for example, when the angular velocity of rotation is constant, the modulation signal is higher than the reference level. waveforms and under the above is symmetrical and ing.

[0017]

[0018]

The abnormality detecting device according to the present invention is provided with the above-mentioned modulation signal.
Asymmetry is detected and anomaly is judged by utilizing the nature of the issue.
For this purpose, means for obtaining the integrated value in the first half cycle and the integrated value in the second half cycle of the modulated signal, and means for obtaining the difference between the absolute values of the two integrated values in the first half cycle and the second half cycle And a means for determining an abnormality based on a comparison between the difference and an abnormality determination threshold value.

According to this aspect, the integrated value in the first half cycle and the integrated value in the second half cycle of the modulated signal are calculated. Then, the abnormality is determined when the difference between these absolute values is outside the range defined by the abnormality determination threshold. In the state where the rotating machine can be regarded as rotating at a constant angular velocity, the modulation signal is a sine wave or a cosine wave. For example, the first half period is the period during which those waveforms should take positive values, and the second half period is the period during which those waveforms should take negative values. For example, the first half cycle has a phase of 0 to π for sine waves and a phase of −π / 2 for cosine waves.
~ Π / 2, and the latter half of the cycle is a phase π ~ 2 for a sine wave.
The phase is π / 2 to 3π / 2 in π and the cosine wave. Due to the symmetry of the sine wave and the cosine wave, the difference between the absolute values of the integrated values should be basically 0. In this aspect, similarly to the above-described aspect, with respect to this difference, the abnormality determination threshold value is used to determine abnormality or normality. Thereby, for example, an anomaly such that the modulation signal is offset is detected.

An abnormality detecting apparatus according to the second aspect of the present invention comprises means for calculating a sum of squares of a sine-modulated signal and a cosine-modulated signal to generate a sum-of-squares signal, and low-pass filtering the sum-of-squares signal to obtain a reference signal. It is characterized by having means for generating and means for judging abnormality based on a difference between the sum of squares signal and the reference signal.

According to the invention, the sum of squares signal is not compared with a constant threshold value, but with a low-pass filtered, ie smoothed with a predetermined time constant, reference signal. For example, when the absolute value of the difference between the sum of squares signal and the reference signal exceeds a predetermined threshold, it is determined to be abnormal. According to this abnormality detection method, a high-frequency fluctuation component that occurs due to abnormality of the resolver, for example, generated in one rotation unit is detected. DC changes in the sum of squares that often occur due to reasons such as gradual fluctuations in the amplitude of the reference signal that are inappropriate to determine as abnormal,
Alternatively, the low frequency fluctuation component is difficult to detect. That is, when a constant threshold value is used as in the prior art, the threshold value needs to be set gently to avoid erroneous detection, which reduces the accuracy of abnormality detection, whereas the present invention squares the reference signal. By generating by summing the sum signal itself,
Even if the threshold for determining the difference between the sum of squares signal and the reference signal is made small, a normal low-frequency fluctuation component is less likely to be erroneously detected as an abnormality, and the accuracy of abnormality detection can be improved.

The abnormality detection device according to the present invention is a resolver
It corresponds to the sine function of the rotation angle of the rotating machine detected from the output signal.
Cosine according to the cosine function of the rotation angle and the sine modulation signal
Detect an abnormality of the rotation angle detection device based on the modulation signal
In the abnormality detection device, the sine modulation signal and the cosine
The sum of squares is calculated each time the key signal and
Means for generating a sum signal, and the square sum signal sequentially generated
Signal is low-pass filtered to sequentially generate reference signal
Means for sequentially generating the sum of squares signal and the base
Determination means for determining the abnormality based on the difference between the quasi-signal and
It is characterized by having.

According to the present invention, the anomaly detection device is sequentially activated.
Generated based on the difference between the sum of squares signal and the reference signal.
The abnormality of the turning angle detection device is determined .

One aspect of the abnormality detection device according to the present invention
According to the above, the determining means determines the ratio of the difference and the abnormality determining threshold value.
It is a means for judging the abnormality based on the comparison
And

According to the present invention, the abnormality detecting device is
The difference between the sum of squares signal and the reference signal,
Judgment of abnormality of rotation angle detection device based on comparison with constant threshold
To do .

[0027]

BEST MODE FOR CARRYING OUT THE INVENTION Embodiments of the present invention (hereinafter referred to as embodiments) will be described below with reference to the drawings. FIG. 1 shows a schematic configuration of a rotation angle detection device for a rotating machine according to this embodiment. Here, the abnormality detecting device according to the present invention is configured by using the CPU 10 in the rotation angle detecting device.

In the present rotation angle detecting device, the oscillator 12 outputs the reference signal sinωt, which is applied to the primary coil 16 of the resolver 14. FIG. 2 is a waveform diagram schematically showing the reference signal and the output signal from the resolver described below, and FIG. 2A shows the reference signal. Resolver 1
Two 2's arranged with a phase difference of 90 ° from each other
Each of the following coils 18 and 20 has a voltage sin ωtsin in which a reference signal is modulated by a rotation angle θ of a rotating machine such as an electric motor.
θ and sinωt cos θ are generated, and these are output as an output signal (resolver signal) from the resolver. The same figure (b)
Represents the resolver signal sin ωt sin θ and the amplitude modulation component sin θ, and FIG.
Represents ωt cos θ and a modulation signal cos θ that is its amplitude modulation component. The modulation signal shown in each figure shows the case where the rotation angle θ linearly increases with time, and in this case, the modulation signal has a sine wave or cosine wave shape with the horizontal axis as the time axis. In the processing of the resolver signal, basically only the phase becomes a problem, so the amplitude of the reference signal and the resolver signal will be described as 1.

Each resolver signal from the resolver 14 is sent to the detection circuit 22 and the R / D converter 24. R /
The processing described in the related art is performed in the D converter 24. That is, resolver signals sinωt sinθ, sinω
tcosθ is multiplied by cosφ and sinφ, respectively, and they are subtracted to generate sinωtsin (θ−φ). This is detected based on the reference signal sinωt, and the modulation component sin (θ−
φ) is taken out. The R / D converter 24 performs feedback control for increasing or decreasing the digital count value φ so that the phase (θ−φ) becomes 0, and when the feedback control is completed, the count value φ is set as a digital value representing the rotation angle θ, for example, a motor. Output to control device etc. Further, the rotation angle θ _RD and the Z-phase signal S _Z obtained by the R / D converter 24 are
Output to 0.

On the other hand, the detection circuit 22 uses the method such as sampling at the peak position of the reference signal as described in the prior art to resolver signals sinωtsinθ, sinω.
The modulated signals sin θ and cos θ are detected from t cos θ and taken out. The detected modulated signal is converted into a digital signal by the A / D converter 30 and passed to the CPU 10 when the detection circuit 22 performs analog processing.

The abnormality detection processing in the CPU 10 of this apparatus will be described below.

[First Abnormality Detection Method] FIG. 3 is a schematic diagram for explaining the first abnormality detection method. CPU10 is A
The digital values of the modulation signals sin θ and cos θ from the / D converter 30 are traced and, for example, the rotation angle θ _RD from the resolver 14 is traced.
One rotation of the rotating machine is detected based on the above, and the maximum value V _{SINP +} , V in one cycle of each modulation signal corresponding to the one rotation is detected.
_{COSP +} , minimum values V _SINP- , V _COSP- are detected. And
The absolute values of these maximum and minimum values are compared for each modulated signal. Specifically, the modulation signal sin θ is determined to be abnormal by the conditional expression K ≦ | (| V _{SINP +} | − | V _SINP- |) | ... (1). Here, K is an abnormality determination threshold value. The maximum value and the minimum value of the modulation signal sin θ when θ changes by 360 °, that is, one rotation is basically sin.
(Π / 2) and sin (−π / 2), and their signs are different from each other and their absolute values should be equal. Therefore, in the normal state, the right side of the above equation should basically be 0. However, as described in the prior art, even in a normal state,
Since there are factors such as a detection error of the modulation signal and a fluctuation of the amplitude of the reference signal, the right side is not always 0. The abnormality determination threshold value K is determined in consideration of the error factors in these normal states.

Based on the threshold value K determined in this way, the above conditional expression is determined and when the condition is not satisfied, that is, when the difference between the absolute values of the maximum value and the minimum value is less than the threshold value K. It is determined that there is no abnormality, and if the condition is satisfied, that is, if the difference between the absolute values of the maximum value and the minimum value is greater than or equal to the threshold value K, it is determined to be abnormal.

In the right side of the above equation, the absolute value of the minimum value is subtracted from the absolute value of the maximum value to obtain the absolute value. For example, the modulation signal is offset to the negative side and V _{SINP +} This is because the right side is kept positive when = 0.8 and V _SINP- = -1.2.

Although one abnormality determination threshold value K is used in the above equation, an appropriate upper limit threshold value K ₊ larger than 0 and an appropriate lower limit threshold value K ₋ smaller than 0 are set as the abnormality determination threshold value, and | V _{SINP + | - | V SINP- | ≦ K} -, K + ≦ | V SINP + | -
Abnormality can also be determined by the conditional expression | V _SINP- |.

According to this abnormality detecting method, for example, a failure mode of the resolver in which the modulation signal is offset can be detected with a small calculation load.

The above processing is performed by another modulation signal cos θ.
Can be similarly performed, and the abnormality can be determined by the following condition: K ≦ | (| V _{COSP +} | − | V _COSP- |) | (2).

By the way, the purpose of the first method is normal when the modulated signal basically fluctuates with the same amplitude above and below 0, and when the modulated signal shifts above or below a predetermined value or more. The point is that it is abnormal. Abnormality detection according to this point, instead of, for example, the following conditional expression K ′ / 2 ≦ that is determined to be abnormal when the midpoint of the full width of the modulation signal deviates from 0 by a predetermined value K ′ or more (V _{SINP +} + V _SINP- ) / 2 (3) or _{K'≤V SINP +} + V _{SINP -...} (3 ') can also be achieved.

[Second Abnormality Detection Method] FIG. 4 is a schematic diagram for explaining the second abnormality detection method. The CPU 10 detects the first half period and the second half period of the modulation signals sin θ and cos θ based on the rotation angle θ _RD from the resolver 14, for example. Here, the first half cycle is defined as a period in which the waveform of the modulated signal should have a positive value, and the second half cycle is defined as a period in which the waveform should have a negative value. For example, the first half cycle has a phase of 0 to π in the modulation signal sinθ and a phase of −π / in the modulation signal cosθ.
2 to π / 2, and the latter half period is the phase π to 2π in the modulation signal sinθ and the phase π / 2 to 3π / in the modulation signal cosθ.
Is 2.

The CPU 10 calculates the integral value in each of the first half period and the second half period of the modulation signal defined in this way. This integration is calculated, for example, by integrating the values of the modulation signal at a constant interval τ from the start timings t ₊ and t ₋ of the first half period and the second half period, respectively, in a state where the rotation angle linearly changes with time. It For example, the value of the modulation signal sin θ at time t is V with t as an argument.
_{Expressing SIN} (t), the integrated values I ₊ , I of the first half period and the second half period
_- is, each _{I + = V SIN (t +} ) + V SIN (t + + τ) + ... + V SIN (t + + nτ) ......... (4) I - = V SIN (t -) + V SIN (t _{- + τ) + ... + V} SIN (t - + nτ) ......... becomes (5).

In the abnormality detection method described here, the abnormality is judged when the difference between the absolute values of these integrated values I ₊ and I ₋ is outside the range defined by the abnormality judgment threshold value. That is,
When the following conditional expression is satisfied, it is determined to be abnormal.

[0042] _{K ≦ | (| I + |} - | I - |) | ......... (6) Here, K is the abnormality determination threshold value which is determined in accordance with the present method. By the way, if it is defined that ΔV _j = | V _SIN (t ₊ + jτ) | − | V _SIN (t ₋ + jτ) | ... (7), the equation (6) can be expressed in the following form. .

K ≦ | ΔV ₀ | + | ΔV ₁ | + ... + | ΔV _n | ... (6 ′) In FIG. 4, the curve 50 is the waveform of the first half cycle of the modulation signal sin θ, and the curve 52 is it. It is the waveform of the subsequent second half cycle. Further, the curve 54 is obtained by inverting the sign of the curve 52 and setting its leading edge (that is, the start timing of the latter half cycle) to the curve 50.
Is moved so as to be overlapped with the leading edge (that is, the start timing of the first half cycle) of, and is for the purpose of showing the image of the processing for obtaining the difference between the absolute values of the integrated values I ₊ and I ₋ .
The difference between the absolute values of the integrated values I ₊ and I ₋ corresponds to the area of the region 56 sandwiched between the curve 50 and the curve 54.

The above abnormality determination processing can be similarly performed for the other modulation signal cos θ.

When the rotating machine is not rotating at a constant angular velocity, for example, the output θ _RD from the R / D converter 24
With reference to, the calculation is performed by integrating the values of the modulation signal at a constant rotation angle interval λ from the rotation angles θ ₊ , θ ₋ corresponding to the start timings t ₊ , t ₋ of the first half period and the second half period, respectively. Specifically, for example, the modulation signal sin θ at the rotation angle θ
When the value of is expressed as V _SIN (θ) with θ as an argument, (4)
The following equations are used as the equations corresponding to the equations (5) and (7). The expressions (6) and (6 ′) can be used as they are in this case.

[0046] _{I + = V SIN (θ +} ) + V SIN (θ + + λ) + ... + V SIN (θ + + nλ) ......... (8) I - = V SIN (θ -) + V SIN (θ - _{+ λ) + ... + V SIN} (θ - + nλ) ......... (9) ΔV j = | V SIN (θ + + jλ) | - | V SIN (θ - + jλ) | ......... (10) this According to the abnormality detection method, for example, the failure mode of the resolver in which the modulation signal is offset is detected as in the first abnormality detection method. In addition, the present method can detect a failure such that the waveform of the modulated signal is broken by comparing the modulated signals not in one point but in area.

[Third Abnormality Detection Method] FIG. 5 is a schematic diagram for explaining the third abnormality detection method. The CPU 10 firstly outputs two modulation signals (a sine modulation signal sin θ and a cosine modulation signal cos θ) obtained from the detection circuit 22 (or the A / D converter 30).
The sum of squares of is calculated, for example, every time each digital data of the modulation signal is input, and the sum of squares signal 60 is generated. Also, C
The PU 10 performs a low-pass filtering operation on the sum of squares signal 60 to generate a reference signal 62 in which the sum of squares signal is smoothed with a predetermined time constant. Then, if the difference between the square sum signal 60 (V _SQ ) and the reference signal 62 (V _LPF ) is outside the range defined by the predetermined abnormality determination threshold value, it is determined to be abnormal. For example, assuming that the abnormality determination threshold value determined corresponding to this method is K, it is determined to be abnormal when the following conditional expression is satisfied.

K ≦ | V _SQ −V _LPF | (11) Although one abnormality determination threshold value K is used in the above equation, an appropriate upper limit threshold value K greater than 0 is used as the abnormality determination threshold value.
₊ A, 0 less suitable lower threshold K _{- defines, V SQ -V LPF ≦ K -} , it is also possible to determine an abnormality according to the conditional expression of _{K + ≦ V SQ -V LPF .........} (12).

Here, the abnormality determination threshold value K and the like are determined in consideration of the same factors as those described in the prior art, that is, factors such as an error generated in the modulation signal detection process and a fluctuation of the reference signal. However, in the conventional method, as described above, the threshold value defines a constant level that does not change with time. Therefore, for example, there are various cases regarding the temperature environment in which the rotation angle detection device can be used. Assuming that false detection does not occur, the threshold value will be set loosely, and an abnormal state is likely to be included in the range defined as normal by the threshold value, that is, the accuracy of abnormality detection deteriorates. There was a problem. On the other hand, the range determined to be normal by this method is a range of a predetermined width centered on the reference signal, and the reference signal gently follows the fluctuation of the sum of squares signal. Therefore, if the smoothing time constant for generating the reference signal is determined according to the fluctuation speed of the sum of squares in the normal state, the deviation between the sum of squares signal and the reference signal does not increase in the normal state, and Therefore, the abnormality determination threshold value K and the like can be set small. As a result, the possibility that an abnormal state is included in the range determined to be normal is reduced, and the accuracy of abnormality detection is improved.

Incidentally, the comparison between the conventional technique and the present method regarding the magnitude of the threshold value can be considered as follows from another viewpoint. That is, in the conventional method, the normal range must be increased according to the normal fluctuation range of the sum of squares in a sufficiently long time. On the other hand, in this method, since the normal range is followed by the sum of squares, the range is adjusted to a width within which the sum of squares can vary due to a normal factor within a short time such as a smoothing time constant. The setting is sufficient, and the range can be narrowed.

According to this method, it is possible to detect, for example, a high-frequency fluctuation component that occurs due to an abnormality in the resolver, for example, in one rotation unit, that is, on a time scale shorter than the smoothing time constant, while detecting the peak timing of the modulated signal. Misalignment,
A direct-current change in the sum of squares or a low-frequency fluctuation component that often occurs due to reasons such as moderate fluctuations in the amplitude of the reference signal according to natural fluctuations in the external environment that are not appropriate for judging abnormalities. False detection as an abnormality is suppressed.

By the way, in the case where the signal lines of the two modulation signals are broken, one of the modulation signal components becomes 0, and the sum of squares fluctuates greatly depending on the rotation angle. If the failure mode is just such a simple case,
There is no problem even if the threshold value is set gently as in the conventional case.
That is, such an abnormality is not included in the range that is erroneously determined to be normal. However, for example, when a coil in the resolver is short-circuited, specifically, for example, when the inlet portion and the middle portion of the secondary coil 18 or 20 are short-circuited, the corresponding modulation signal is not completely zero. Become. In this case, the sum of squares has a smaller fluctuation amplitude than that in the case of complete disconnection, but has a waveform that rapidly changes for each rotation. Even if the fluctuation range is small in such a case, the present method can accurately detect it as an abnormality because it is a harmonic component.

[Fourth Abnormality Detection Method] In the fourth abnormality detection method, the CPU 10 calculates the rotation angle θ _CAL separately from the R / D converter 24. That is, the CPU 10 obtains the modulation signals sin θ and cos θ obtained from the detection circuit 22, calculates tan θ from them, and obtains θ corresponding to the value of tan θ, thereby determining θ _CAL .

The CPU 10 uses the R / D converter 2
The θ _RD obtained from 4 and the above θ _CAL are compared, and an abnormality is determined when the difference is equal to or more than the abnormality determination threshold K defined in the present method, for example, as represented by the following equation.

K ≦ | θ _RD −θ _CAL | (13) With this method, for example, an abnormality of the R / D converter 24 can be detected.

[Fifth Abnormality Detection Method] In the fifth abnormality detection method, the CPU 10 monitors the Z-phase signal from the R / D converter 24. Then, θ in the R / D converter 24
When the pulse of the Z-phase signal emitted when the count value corresponding to is detected is 0, it is examined whether the rotation angle information obtained from the modulation signal at that timing indicates θ = 0. .

For example, as the rotation angle information, θ _CPU as described in the fourth method can be used. Also,
It is also possible to use the fact that sin θ = 0 and cos θ = 1 at θ = 0 as the rotation angle information without calculating the load tan ⁻¹ (sin θ / cos θ).

By this method, it is possible to detect an abnormality such as a shift of the Z-phase signal of the R / D converter or a shift of the count value.

[Brief description of drawings]

FIG. 1 is a schematic diagram showing a schematic configuration of a rotation angle detection device for a rotating machine that is an embodiment of the present invention.

FIG. 2 is a waveform diagram schematically showing a reference signal and an output signal from a resolver.

FIG. 3 is a schematic diagram illustrating a first abnormality detection method.

FIG. 4 is a schematic diagram illustrating a second abnormality detection method.

FIG. 5 is a schematic diagram illustrating a third abnormality detection method.

[Explanation of symbols]

10 CPU, 12 oscillator, 14 resolver, 16
Primary coil, 18, 20 Secondary coil, 22 Detection circuit, 24 R / D converter, 30 A / D converter.

─────────────────────────────────────────────────── ─── Continuation of the front page (56) Reference JP-A-7-19899 (JP, A) JP-A-8-145719 (JP, A) JP-A-7-198413 (JP, A) JP-A-6- 147922 (JP, A) JP-A-9-72758 (JP, A) JP-A-63-243703 (JP, A) JP-A-59-102103 (JP, A) Jitsukaihei 1-84018 (JP, U) Fukukaihei 4-5727 (JP, U) (58) Fields investigated (Int.Cl. ⁷ , DB name) G01D 5/00-5/62 G01B ⁷ /00-7/34

Claims (4)

(57) [Claims] 1. An abnormality detecting device for detecting an abnormality of a rotation angle detecting device based on a modulation signal according to a rotation angle of a rotating machine detected from an output signal of a resolver, wherein the abnormality detecting device detects an abnormality above a reference level of the modulation signal. A detection unit configured to detect an asymmetry between a variation of the modulation signal and a variation of the modulation signal below the reference level; a determination unit that determines the abnormality based on the asymmetry; The means acquires an integrated value in the first half cycle of the modulated signal and an integrated value in the second half cycle, and obtains a difference between absolute values of the integrated values in the acquired first half cycle and the second half cycle. An abnormality detecting apparatus, which is a means for detecting asymmetry, wherein the determining means is a means for determining the abnormality based on a comparison between the difference and an abnormality determination threshold value. 2. An abnormality of a rotation angle detection device based on a sine modulation signal according to a sine function of a rotation angle of a rotating machine detected from an output signal of a resolver and a cosine modulation signal according to a cosine function of the rotation angle. In the abnormality detection device for detecting, a means for calculating the sum of squares of the sine modulation signal and the cosine modulation signal, and means for generating a sum of squares signal, means for low-pass filtering the sum of squares signal, means for generating a reference signal And an abnormality determining unit that determines the abnormality based on a difference between the sum of squares signal and the reference signal. 3. An abnormality of a rotation angle detection device based on a sine modulation signal according to a sine function of a rotation angle of a rotating machine detected from an output signal of a resolver and a cosine modulation signal according to a cosine function of the rotation angle. An abnormality detection device for detecting the sum of squares every time the sine-modulated signal and the cosine-modulated signal are input, and means for generating sum-of-squares signals; An abnormality detection comprising: means for filtering and sequentially generating reference signals; and determination means for sequentially determining the abnormality based on a difference between the sum of squares signal and the reference signal. apparatus. 4. The abnormality detection device according to claim 2, wherein the determination unit is a unit that determines the abnormality based on a comparison between the difference and an abnormality determination threshold value. apparatus.