Conversion Factors Between Common Detectors in EMI ... - IEEE Xplore

IEEE TRANSACTIONS ON ELECTROMAGNETIC COMPATIBILITY, VOL. 55, NO. 4, AUGUST 2013

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Conversion Factors Between Common Detectors in EMI Measurement for Impulse and Gaussian Noises Huadong Li and Kye Yak See, Senior Member, IEEE

Abstract—Based on the operating principle of a typical electromagnetic interference test receiver and the circuits of various commonly used detectors, a simulation model is developed. With the model, the response of each detector to broadband emission can be simulated and analyzed. The conversion factors between different types of detectors for the same type of broadband emission are determined and verified with those reported in well establish standards. The systematic analysis provides both insight and rationale behind how these conversion factors are derived. Index Terms—Average detection, peak detection, quasi-peak detection, root-mean-square (RMS) average detection.

I. INTRODUCTION PECTRUM analyzers and electromagnetic interference (EMI) test receivers are the two common types of equipment usually used for both radiated and conducted emission measurements for electromagnetic compatibility compliance. In general, EMI disturbances can be categorized into three types, namely narrowband continuous, broadband continuous, and broadband discontinuous disturbances [1]. In general, narrowband continuous disturbance constitutes any kind of frequency spectrum that falls within intermediate frequency (IF) bandwidth of the measuring receiver; for example, a modulated carrier that fits within the IF bandwidth or repetitive pulses whose separation between individual spectral lines is greater than the IF bandwidth. Broadband continuous disturbance is produced by repetitive pulses where the pulse repetition frequency (PRF) is smaller than the IF bandwidth of the receiver so that during the measurement more than one spectral line falls within the bandwidth. Broadband discontinuous disturbance is generated unintentionally by mechanical or electronic switching with a click rate ≤30 clicks/min. To differentiate these disturbances, different types of detectors are necessary during EMI measurement. There are four commonly used detectors and their functions will be briefly described. Average detection is generally used for the measurement of narrowband disturbance; quasi-peak detection is usually used for broadband disturbance for the assessment of audio annoyance to a radio listener but also useful for narrowband disturbance; root-mean-square (RMS) average detection,

S

Manuscript received January 14, 2011; revised June 18, 2011, November 8, 2011, March 3, 2012, and July 1, 2012; accepted September 3, 2012. Date of publication January 9, 2013; date of current version July 22, 2013. H. Li is with Caterpillar, Inc., Peoria, IL 61614 USA (e-mail: li_huadong@ hotmail.com). K. Y. See is with the Department of Electrical and Electronics Engineering, Nanyang Technological University, Singapore 639798 (e-mail: ekysee@ ntu.edu.sg). Digital Object Identifier 10.1109/TEMC.2012.2227752

a combination of the RMS detection and average detection, is usually used for the weighted measurement of broadband disturbance for the assessment of the effect of impulsive disturbance to digital radio communication services but also useful for narrowband disturbance; and peak detection may be used for either broadband or narrowband disturbance measurement. These detectors are implemented with different circuits and therefore exhibit varying responses. For example, quasi-peak detection requires longer time to complete the emission measurement than peak and average detections. In view of this, some standards give optional peak detection limits for broadband noise besides the quasi-peak detection limits. CISPR 12 specifies both peak and quasi-peak limits, and for repetitive pulses with a 20-Hz PRF, the difference between the two limits for broadband noise is as large as 20 dB [2]. CISPR 25 specifies either peak or quasi-peak detection for broadband noise measurement and the difference between the two limits is 13 dB [3]. To cater for different electronic products, EMI emission measurement covers a very wide frequency range. CISPR 16-1-1 subdivides the emission measurement frequency range into five bands: band A (9–150 kHz); band B (0.15–30 MHz); band C (30–300 MHz), band D (300 MHz–1 GHz), and band E (1–18 GHz) [4]. The 6-dB IF bandwidths (B6 ) in bands A, B, C, and D are 200 Hz, 9 kHz, 120 kHz, and 120 kHz, respectively. For band E, the 1-MHz impulse bandwidth is specified. For measurement of broadband noise, conversion factors between peak and quasipeak detectors are also given. For repetitive pulses of 25-Hz PRF in band A and 100-Hz PRF in bands B, C, and D, the conversion factors between peak and quasi-peak detectors for bands A, B, C, and D are 6.1, 6.6, 12, and 12 dB, respectively. As we can see, the conversion factors given in the three aforementioned standards vary, which may be due to variation in the broadband noise measurement conditions. Therefore, to understand how these conversion factors are derived and the rationale behind these varying conversion factors in emission measurement, an in-depth analysis is necessary. Besides the conversion factors due to different detectors, different measurement bandwidths are sometimes specified in different standards or even in the same standard for the same type of disturbance measurement. ISO 13766 allows different bandwidths for broadband noise measurement with peak detection and provides the conversion factors between measured readings obtained with different bandwidths [5]. These conversion factors depend on the spectral distribution of the measured signal and it may work well for peak detector but not necessarily for quasi-peak and average detectors. Most literature focused on the response of quasi-peak detector for various noises [6]–[10]. The conversion factor between peak and quasi-peak detections for broadband noise has been

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Fig. 1.

IEEE TRANSACTIONS ON ELECTROMAGNETIC COMPATIBILITY, VOL. 55, NO. 4, AUGUST 2013

Fig. 2.

Predetector block diagram of a test receiver.

found to be dependent on the PRF of the pulses [11]. However, the analysis is based on an input signal of pure rectangular pulses, which may not be necessarily true. Example data on the quasi-peak detection responses to different impulse rates and the respective conversion factors of different types of detections at different impulse rates are given in CISPR 16-1-1 [4]. In view of the variations of the detectors and the IF bandwidths in emission measurement, this paper studies the output responses of commonly used detectors of a typical EMI test receiver with broadband impulse or Gaussian noise as input signal. Based on a circuit model approach, the output response of each detector is simulated and the conversion factor between commonly used detectors is derived. The impacts of PRF and bandwidth on the conversion factors are also analyzed. II. SIGNALS BEFORE DETECTORS Fig. 1 shows the block diagram of a typical EMI test receiver without the detector. A signal ei (t) is fed at its input, it is amplified by a radio frequency (RF) amplifier, then mixes with a local oscillator (LO) for frequency conversion to an IF. The IF signal is amplified further by an IF amplifier and finally goes through an IF filter with a predefined 6-dB bandwidth. The transfer functions of the RF amplifier, the IF amplifier, and the IF filter are denoted as G1 (f ), G2 (f ), and G3 (f ), respectively. The transfer function of the mixer can be described as a frequency conversion process, fLO = ft − fIF ; where fLO , fIF , and ft are the LO frequency, IF frequency, and the receiver-tuned frequency, respectively. The output signal can be expressed by eo (f ) = ei (f ∗ )G(f ) ∗

(1) ∗

where f = f − fIF + ft and G(f ) = G1 (f )G2 (f )G3 (f ). According to [4], the overall transfer function G(f ) can be represented by two critically coupled-tuned transformers arranged in cascade as shown in Fig. 2. For each stage circuit, the R . When the attenuation or neper frequency is define as α = 2L input ei (t) is an impulse, it is thought to be a pulse with infinite amplitude and zero duration. Its Fourier transform is a constant equal to its strength σ, which is defined as integration of the impulse amplitude with respect to the time within the pulse period. In reality, a narrow pulse has a frequency spectrum with amplitude and phase constant√ over the pass band of the measurement receiver. When α  1/ LC, the unit impulse response of the network is given by [12] eo (t) =

1 −α t e ωo (sin(ωo t) − ωo t cos(ωo t)), 2

where ωo =

√1 LC

.

for t ≥ 0 (2)

Cascaded series-resonant circuits.

Its transfer function is expressed as follows: G(ω) =

(ωo2

ωo4 + (jω + α)2 )2

(3)

where ω = 2πf and f is the input signal frequency. The 6-dB bandwidth B6 in Hz is determined to be α (4) B6 = . π Assuming that the overall gain of a test receiver is Gc and including it into (2) and (3), we have eo (t) =

1 Gc e−α t ωo (sin(ωo t) − ωo t cos(ωo t)) 2

(5)

G(ω) =

ωo4 Gc . (ωo2 + (jω + α)2 )2

(6)

The expressions of (5) and (6) vary from those in [4]. The first difference is the coefficients. Since we are investigating the conversion factors between different detectors, this difference may not have any impact in our final results. The second difference is that the attenuation constant α is present in (5) and (6) while in [4] it is replaced by ωo . This difference will affect both the IF signal and the detector output, as we will observe later. Another important difference is that (2) and (5) are the IF signal expression while its correspondence in [4] is considered to be the IF signal envelope. With these differences mentioned, the analyses and conclusions presented in [6], which are based on [4], need to be revisited. For a general consideration, G(f ) can be assumed to be the transfer function of a narrow band network and [11] shows that G(f ) has the following property: |G(fo + Δf )| ej φ(f o +Δ f ) = |G(fo − Δf )| e−j φ(f o −Δ f ) (7) where fo and Δf are the center frequency and deviation from the center frequency. From there, the IF output can be expressed as a modulated IF signal with an envelop A(t) eo (t) = A(t) cos(2πfo t + φo ).

(8)

If the input is an impulse, the output of the IF filter is expressed as



eo (t) = 2 |Ei (fi )|

∞

|G(f )| cos(2πf t + φ(f ) + φi (fi ))df

0

(9) where φ(f ) and φi (fi ) are the angles of the network transfer function and the input signal; Ei (fi ) is the Fourier transformer of ei (t). The previous equation can be expressed in the form of (8) with φo = φi (fi ) and

(10)

LI AND SEE: CONVERSION FACTORS BETWEEN COMMON DETECTORS IN EMI MEASUREMENT FOR IMPULSE AND GAUSSIAN NOISES

Fig. 3.

Peak detector circuit.



∞

A(t) = 4|Ei (fi )|

Fig. 4.

Average detector circuit.

Fig. 5.

Quasi-peak detector circuit.

659

|G(fo + f  )| cos[2πf  t

0

+ φ(fo + f  )]df  .

(11)

III. DETECTOR When the IF signal eo (t) is fed into a detector, the detector essentially responds to its envelope. In Fig. 3, the IF output signal eo (t) and the output impedance of the IF filter Ro is connected to a diode D. The value of capacitor C is chosen such that the voltage across it will charge up almost instantly and follow the instantaneous IF signal, and the value of R is chosen to achieve a long discharge time constant. Therefore, Vp = |A(t)|m ax . Fig. 4 shows the average detector circuit, where the values of R and C are chosen to let the voltage across capacitor C follow the input envelope. The critically damped second-order low-pass filter is a meter simulating network. It only allows very low frequency components in A(t) to pass through and its output is a time average of A(t), which is given by Vav = |A(t)| for an impulsive disturbance with high PRF and steady narrow band disturbance. For intermittent disturbance and impulsive disturbance with low PRF [4], the peak value of the low-pass filter output is considered as the average detection value. Fig. 5 shows a conventional quasi-peak detector circuit. Td = Rd C, the discharging time constant, is very large so that the output voltage usually does not follow the envelope of eo (t) except for low frequency pulses with low duty cycles. The charging time constant Tc is defined as the time required for the output voltage Vqp to reach 63% of its final value when eo (t), which is a stepped IF sine wave, is applied. It has direct relationship with Ro C. The following filter’s time constants have been determined so that the detector provides not only the correct responses to intermittent, unsteady, and drifting narrow band disturbances but also weighting of the impulsive disturbance with low PRF, e.g., below 10 Hz [4]. In modern spectrum analyzers and EMI test receivers, an envelope detector is added before the quasi-peak weighting circuit. The charging time constant Tc1 is defined as the time required for Vqp to reach 63% of its final value when the envelope detected IF signal is applied [6]. In the following sections, the conventional quasi-peak detector circuit model is used since the introduction of modern quasi-peak detectors is also based on it [6]. IV. CONVERSION FACTORS BETWEEN DETECTORS For ease of analysis, Gc is assumed to be unity and (5) can be expressed in the format of (8): eo (t) = A(t) sin(ωo t + φ(t))

(12)

where 1 −at  e ωo 1 + ωo2 t2 and 2 1 cos(φ(t)) =  . 1 + ωo2 t2 A(t) =

The maximum value of A(t) is obtained at  ωo + ωo2 − 4α2 . t1 = 2αωo If α  ωo , we have t1 = given by

1 α

(13) (14)

(15)

and the peak detector output is

ωo2 . (16) α For a general case, the peak detector value can be obtained as [4], [13] Am ax ≈ 0.184

Ap = 2 |Ei (fi )| Go Bim p (17)  ∞ A where Bim p = 2|E i (fpi )|G o ≈ G1o 0 |G(f )|df . For some circuits, it is also known as the effective impulse bandwidth of the predetector circuit and Go is the gain of the whole circuits at the center frequency before the detector. If the input repetitive pulses has a PRF of fim p , there is no serious overlap in the output pulses and A(t) does not oscillate, the average detector value for a signal from an assembly of two critically coupled tuned transformers can be obtained as  ∞ 1 −α t  e ωo 1 + ωo2 t2 dt. Vave = fim p (18) 2 0 If we only consider the contribution made when ωo t 1, it becomes fim p ωo2 . (19) 2α2 From (16) and (19), the ratio between peak and average detector values is given by Vave ≈

Rp−ave ≈

0.368α . fim p

(20)

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TABLE I FUNDAMENTAL CHARACTERISTICS OF QUASI-PEAK DETECTORS

Fig. 7. Quasi-peak detector output with a single impulse input for bands C and D (α = 1 00 000 rad/s).

Fig. 6.

IF filter output with a single impulse input (α = 1 00 000 rad/s).

The ratio is inversely proportional to the impulse repetition frequency. According to (4), it is obvious that this ratio increases with the measurement bandwidth of the test receiver. For a general case [4], [13], the average detector value is given as Vave = 2 |Ei (fi )| Go fim p .

(21)

Fig. 5 shows that the discharging current goes through Rd and the charging current goes through Ro . Since the IF signal frequency is very high in terms of capacitor C, we can assume that Vqp does not change in one cycle of IF signal and have the following equation to determine the response of Vqp (t) to eo (t): Vqp dVqp + = dt Rd  ⎧ 1 2 Vqp −1 ⎪ 2 ⎨ A (t) − Vqp − Vqp cos , πRo A(t) ⎪ ⎩ 0,

C

A(t) > Vqp A(t) ≤ Vqp . (22)

Table I lists the time constants in different frequency bands and the values of Ro C calculated from (22). Once an impulse is applied to a test receiver, the IF filter output is a modulated IF pulse as described by (2). After the quasipeak detector, it becomes a low-frequency-pulsed signal which is determined by the envelope of the IF filter output. Figs. 6 and 7 give the MATLAB simulated results of the IF filter output and a quasi-peak detector output, respectively, before the critically damped second-order low-pass filter when the test receiver input is excited by a single impulse. Fig. 6 is obtained directly from (2) and Fig. 7 is based on a pure numerical integration. In the simulations, the IF frequency is set to be 21.4 MHz as it is used in DSI-600 series test receivers. The time step is set to be onethirtieth of the IF signal period. The other parameters are Ro = 250 Ω, Rd = 550 kΩ, C = 1 μF, and α = 1 00 000 rad/s, and

Fig. 8. Ratio of a peak detector value to a quasi-peak detector value (α = 1 00 000 rad/s).

the corresponding B6 ≈ 31.8 kHz. These values are normalized to the maximum of the IF filter output. If the test receiver input is repetitive pulses with a large PRF, the quasi-peak detector output Vqp can be assumed to be a constant. The total net charge in the capacitor C caused by the discharging and charging currents shall be zero during every pulse cycle. Vqp is determined by the following equation [8]:  Rd ∞ Vqp = (eo − Vqp )ρ(eo )deo (23) Ro V q p where ρ(eo ) is the probability density for eo . Simulations are also conducted in MATLAB to study the relationship between the peak and quasi-peak detector outputs in C and D bands. In the simulations, the peak detector values are obtained from (16). The quasi-peak detector values are obtained by trying 100 values evenly distributed between 0 and the peak detection value. The value which gives the closest charge value to the discharge value in an impulse interval is taken as the quasi-peak detector value. The conversion factor is found to be related to the attenuation factor and the PRF. Fig. 8 shows the ratio of the peak detector value to the quasi-peak detector value. It is found that the ratio decreases with the PRF. Fig. 9 shows that the ratio of peak to quasi-peak detector values increases with the attenuation factor α. From (12), it is clear that α determines the profile of the IF signal envelop. When α increases, the IF signal envelop becomes narrower and the total charging time for the quasi-peak detector for one pulse cycle is reduced. Therefore, the peak to quasi-peak detector values increases. On the other hand, it can be seen from (4) that α determines the bandwidth of the IF filter. When its value increases, the filter bandwidth

LI AND SEE: CONVERSION FACTORS BETWEEN COMMON DETECTORS IN EMI MEASUREMENT FOR IMPULSE AND GAUSSIAN NOISES

Fig. 9. Conversion factor of peak to quasi-peak detector value (fim p = 100 Hz).

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Fig. 11. Conversion factors of peak detector value to quasi-peak detector value for C and D bands (B 6 = 120 kHz).

simulated relationship between the ratio of Vqp1 to Vqp and the impulse frequency from 0.1 to 20 Hz. If we use the maximum value of Vqp1 as the output of the indicating instrument, the ratio of Vqp1 to Vqp can be much larger at frequencies below 1 Hz. V. VALIDATION AND ANALYSIS Fig. 10.

Ratio of indicating instrument output to input.

decreases. The corresponding bandwidth range in Fig. 9 is from 100 to 140 kHz. If different bandwidths are used for emission measurement, the conversion factors between peak and quasipeak detectors are different. Further simulations are conducted with different IF signal frequencies in the range of 20–30 MHz, and it is found that the conversion factor is almost independent of the IF frequency. A general relationship between peak and quasi-peak detector values are given as a curve in [13]. The quasi-peak detector output is applied to a meter simulating network, which is modeled as a critically damped secondorder low-pass filter. Its response can be described by [6] Tm2

d2 Vqp1 dVqp1 + Vqp1 = Vqp + 2Tm 2 dt dt

(24)

where Tm is the time constant of the indicating instrument, whose value is 160 ms for bands A and B, and 100 ms for bands C and D [4]. To study the relationship between Vqp and Vqp1 , Vqp is given − t a signal of e t d , where td is the discharge time constant of the quasi-peak detector. This signal has the same PRF as the receiver’s input impulses. It is easy to determine that the signal f

−

1

(1 − e f i mp t d )in an impulse interhas an average value of ti mp d val. It can be considered as the value of Vqp . The stable value of Vqp1 after some impulse periods is considered to be the quasipeak detection display value. The simulations are conducted in MATLAB with the direct use of an ordinary differential equation function. The results show that the stable Vqp1 is nearly constant when PRF is above 20 Hz and the ratio of Vqp1 to Vqp is almost unity. When PRF is less than 20 Hz, Vqp1 varies with cycles and its average value is used instead. Fig. 10 shows the

With α = 1 20 000π rad/s, the simulation corresponds to the CISPR bandwidth B6 = 120 kHz. Fig. 11 gives the simulated peak to quasi-peak conversion factor with increasing PRF for bands C and D. It also indicates the relative quasi-peak detector outputs with fixed input impulse area and different PRFs. The result for PRF = 1 Hz is obtained by trying 1000 evenly distributed values between 0 and the peak value while the other values are obtained by trying 100 values. The curve agrees well with the values from CISPR16-1-1 [4]. The discrepancy at low PRF may be due to the different data handling methods since the signals are oscillatory in nature. If the maximum output of the indicating instrument is chosen as the quasi-peak detection reading at low PRF, the obtained curve agrees quite well with the curve from [4]. For example, our simulated peak to quasi-peak detection conversion factor at 1 Hz fim p will reduce about 3 dB. When fim p = 21 Hz, the simulated conversion factor between the peak and quasi-peak values is about 21.9 dB. The results agree very well with the published results in [6], where the corresponding value is 21 dB if a rectangular pulse train with pulse duration of 10.6 μs and repetition frequency of 21 Hz is fed into the detectors. When fim p = 100 Hz, [4, corrigendum 2] shows the conversion factor between the peak and quasi-peak values is 12 dB, also agrees well with our simulated value of 12.6 dB. With the same input impulse area in bands C and D, [4, Table II] shows that the quasi-peak detector output at 100-Hz PRF is about 8 dB lower than at 1000-Hz PRF and about 9 dB higher than at 20-Hz PRF. Again, these values agree very well with the simulated results. Therefore, the model developed for the simulated works correctly. When a narrowband signal with unit amplitude is fed into a test receiver that is tuned to the signal frequency, the amplitude of the IF signal can be approximately expressed from (6) as Aif =

ωo2 Gc . 4α2

(25)

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It can be defined as the total gain of the test receiver between the RF input and the IF filter output, which is equal to Go . This value can be obtained through equipment design and calibration. The displayed measurement value of the test receiver is the value of the detection output signal compensated/divided by the total gain. With this in mind and from (16), one can conclude that the displayed peak detection value of a broadband noise is proportional to α and therefore is proportional to the measurement bandwidth from (4). Similarly, from (19), it indicates that the displayed average detection value of a broadband noise is independent of the measurement bandwidth. The relationship between the displayed quasi-peak detection value of a broadband noise and the measurement bandwidth is shown in Fig. 9, where the quasi-peak detection value increases with the measurement bandwidth but the increase is slower than a linear relationship. According to the definition of Bim p as given in (17), we get Bim p = 0.368α from the presented model. This relationship is obtained from (16) and (23) with Gc ignored. From (4), it becomes Bim p = 1.16B6 .

(26)

It is different from the relationship given in [4] where the coefficient is 1.05. In [4], emission measurements above 1 GHz are recommended to be conducted with the suggested Bim p . This relationship is important since test receivers are normally set with varying measurement bandwidths. Once a Gaussian noise passes through a narrow band system, the output is still a Gaussian noise. The instantaneous amplitude of its envelop obeys Rayleigh law and is determined by the RMS voltage of the output noise E [13] as A − A 22 e 2 E dA (27) E2 where dPA is the probability that the instantaneous value of the envelope lies between A and A+dA. E can be determined as   (28) E = Δfrn Go 2P (fi ) dPA =

where P (fi ) is the input noise power spectrum at the input frequency, Go is the center frequency gain of the linear network, and the effective random noise bandwidth is defined as ∞ |G(f )|2 df (29) Δfrn = 0 G2o where G(f ) is the frequency characteristic of the linear network. When the noise is input into an average or quasi-peak detector, the output voltage is proportional to E. Assuming that Δfrn is approximately equal to the bandwidth of the test receiver, the average or quasi-peak detection output voltage will be approximately proportional to the square root of the resolution bandwidth. According to [13], the quasi-peak value is approximately twice the average value for Bands C and D. A peak detection measurement is no longer meaningful since its value can exceed any value as long as the measurement time is long enough. For verification purposes, measurement of Gaussian noise is carried out. With the input port terminated by a 50-Ω load, a powered preamplifier LN1000 A from Amplifier Research is

used as a white noise source. Its output is inputted into a test receiver ESCI 7 from Rohde & Schwarz. The noise is measured at 100 MHz and 2 s is set for each measurement time. When the resolution bandwidth is 120 kHz, the quasi-peak and average detection results are 24.04 and 17.25 dB·μV, respectively. When the resolution bandwidth is 9 kHz, the results are 11.27 and 5.87 dB·μV. They agree well with the analyses. VI. CONCLUSION Based on the operating principle of a typical EMI test receiver and various common detector circuits, a system simulation model has been developed. The model allows IF signal, peak-detector, quasi-peak detector, and average detector output signals be simulated with pulsed waveform of varying PRF. The model has been validated by comparing the simulated conversion factors with those given in [4]. With the simulation model, the conversion factor between any two types of detectors for broadband noise measurements can be determined with ease. The model also allows comprehensive analysis of the effects of PRF of the pulsed waveform and IF bandwidth of the receiver on the conversion factors between common detectors. In addition, the relationship between the impulse bandwidth and the IF bandwidth of a test receiver is derived. For Gaussian noise, the quasi-peak or average detector value is found to be approximately proportional to the square root of the IF bandwidth. REFERENCES [1] Specification for radio disturbance and immunity measuring apparatus and methods—Part 2-3: Methods of measurement of disturbances and immunity—Radiated disturbance measurements, CISPR 16-2-3, ed. 3.0, 2010. [2] Vehicles, motorboats and spark-ignited engine-driven devices-Radio disturbance characteristics-Limits and methods of measurement, CISPR 12, 4th ed., 1997. [3] Vehicles, boats and internal combustion engines—radio disturbance characteristics- Limits and methods of measurement for the protection of on-board receivers, CISPR 25, ed. 3.0, 2008. [4] Specification for radio disturbance and immunity measuring apparatus and methods—Part 1-1: Radio disturbance and immunity measuring apparatus—Measuring apparatus, CISPR 16-1-1, ed. 3.0, 2010. [5] Earth-moving machinery- Electromagnetic compatibility, ISO 13766, 2nd ed., 2006. [6] A. Sugiura, T. Oguchi, and H. Nagatomo, “Responses of radio interference measuring apparatus employing an envelop quasi-peak detector,” Electron. Commun. Jpn., vol. 69, no. 7, pp. 73–82, 1986. [7] D. Ristau and D. Hansen, “Modulation impact on quasi-peak detector response,” in Proc. IEEE Int. Symp. Electromagn. Compat., 1997, pp. 90– 95. [8] F. Haber, “Response of quasi-peak detector to periodic impulses with random amplitudes,” IEEE Trans. Electromagn. Compat., vol. EMC-9, no. 1, pp. 1–6, Mar. 1967. [9] F. Krug and P. Russer, “Quasi-peak detector model for a time-domain measurement system,” IEEE Trans. Electromagn. Compat., vol. 47, no. 2, pp. 320–326, May 2005. [10] K.-O. Muller, “Speeding up quasi peak weighting EMI tests,” in Proc. IEEE Int. Symp. Electromagn. Compat., 1991, pp. 169–172. [11] H. Rakouth, R. Hozeska, and C. Cammin, “Detectors correlation factor of broadband measurements used in automotive EMC,” in Proc. IEEE Int. Symp. Electromagn. Compat., 2006, pp. 259–262. [12] S. Samuel, “Impulse excitation of a cascade of series tuned circuits,” in Proc. IRE., vol. 32, no. 12, pp. 758–760, Dec. 1944. [13] D. B. Geselowitz, “Response of ideal radio meter to continuous sine wave, recurrent impulses, and random noise,” IRE Trans. Radio Freq. Interference, vol. 3, pp. 2–11, May 1961.

LI AND SEE: CONVERSION FACTORS BETWEEN COMMON DETECTORS IN EMI MEASUREMENT FOR IMPULSE AND GAUSSIAN NOISES

Huadong Li was born in China. He received the B.S. degree in microwave engineering from East China Normal University, Shanghai, China, in 1989, the M.E. degree in electromagnetic Compatibility (EMC) from Nanyang Technological University, Singapore, in 1999, and the Ph.D. degree in electrical engineering from the University of Dayton, Dayton, OH, in May 2008. From 1989 to 1996, he was an Electronic Engineer with Shanghai Space Bureau, China. From 1999 to 2001, he was an EMC Engineer with Thomson Multimedia, Singapore. From 2001 to 2003, he was an EMC Engineer with Met Laboratories, Inc., Union City, CA. He then joined Pioneer Automotive Technologies, Inc., Springboro, OH, as a Senior EMC Engineer. He is currently working as an EMC Specialist with Caterpillar, Inc., Peoria, IL. His current research interests include signal integrity, EMC testing, simulation, and design.

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Kye Yak See (SM’02) received the B.Eng. degree from the National University of Singapore, Singapore, in 1986, and the Ph.D. degree from Imperial College, London, U.K., in 1997. Between 1986 and 1991, he was with Singapore Technologies Electronics as the Head of Electromagnetic Compatibility Centre. From 1991 to 1994, he was a Lead Electromagnetic Compatibility (EMC) Design Engineer in ASTEC Custom Power, Singapore. He is currently an Associate Professor in the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. He also holds concurrent appointments as the Head of the Circuits and Systems Division and the Director of the Electromagnetic Effects Research Laboratory. His research current interests include electromagnetic interference filter design for power electronics, signal integrity, and EMC measurement techniques. Dr. See is the Founding Chair of the IEEE Singapore EMC Chapter and a Technical Assessor of Singapore Accreditation Council. He was also the Organizing Committee Chairs for the 2006 EMC Zurich Symposium and 2008 Asia Pacific EMC Conference in Singapore. Since January 2012, he has been the Technical Editor of the IEEE ELECTROMAGNETIC COMPATIBILITY MAGAZINE.