WO2010044069A1

WO2010044069A1 - Method, device and system for identifying electronic products

Info

Publication number: WO2010044069A1
Application number: PCT/IB2009/054526
Authority: WO
Inventors: Xuecheng Qian; Yong Liu; Yugang Jia
Original assignee: Koninklijke Philips Electronics N.V.
Priority date: 2008-10-16
Filing date: 2009-10-15
Publication date: 2010-04-22

Abstract

The present invention provides a technical solution to identify an electronic product by means of the intrinsic physical character thereof, for the purpose of detecting fake products. The present invention provides a technical solution for obtaining the eigenvector of an operating electronic product by using a metal coil. The metal coil receives the electromagnetic wave emitted by the electronic product and converts it to an analog electrical signal, which analog electrical signal is then converted to a digital electrical signal, and then, the digital electrical signal is processed, in order to obtain a processed signal sequence as the eigenvector of said electronic product. On the basis of extracting the eigenvector, the present invention further provides a method, an identifying device and an identifying system for identifying an electronic product. A metal coil is used in the present invention, so that it is capable of detecting electromagnetic wave signals of a quite weak intensity, and the range of electronic products that can be identified using the characteristic information of the electromagnetic wave emitted by the electronic product is broadened effectively.

Description

METHOD, DEVICE AND SYSTEM FOR IDENTIFYING ELECTRONIC

PRODUCTS

Technical Field

The present invention relates to a method, device and system for identifying electronic products, especially to a method, device and system for identifying electronic products by means of the character of the electromagnetic wave emitted from the electronic products.

Background of the Invention

Nowadays, electronic products play an important role in people's lives, making their lives more convenient, and bringing the manufacturers considerable profits. At the same time, many fake and inferior electronic products appear on the market. Consumers and manufacturers both suffer great losses due to the fake and inferior copies of famous brands.

At present, there are many anti-counterfeiting techniques to solve the problem mentioned above, such as anti-fake labels, RF labels affixed to the products or the packaging thereof. There are many kinds of anti-fake labels, the most typical one of which is the Winsafe Coupon. Before selling the product, 'uncover the surface and dial 800******* or send a SMS message to 9588**** for verification' as the Winsafe Coupon on a product will be covered by a nontransparent layer. After purchasing the product, the consumer can wipe off this layer and dial a free number or send a SMS message to the manufacturer or a designated institution to verify whether it is a quality product. The anti-fake label has the drawback that it can be easily counterfeited. It is less easy to counterfeit a RF label, but the cost of attaching a RF label to every single product is too high.

Most electronic products, such as Compact Fluorescent Lamps (abbr. CFL), mobile phones, MP3 players, FM radio receivers, TV sets, computers and so on, will emit electromagnetic waves when in operation. Some electronic products, like mobile phones, have to emit electromagnetic waves for some purposes, while the electromagnetic waves emitted by other electronic products are 'by-products' which are useless to the operation of said products and considered as electromagnetic pollution. The spectrum of the electromagnetic wave emitted by the electronic product depends on the values taken by the electronic elements inside the product, the principle of the circuit, and even the layout of the circuit board. Electronic elements having the same nominal value actually take values which are not exactly the same, and the layouts of the circuit boards are different, so the spectrums of the electromagnetic waves emitted by different products will be different, even though they are of the same type. US patent application no. 7,420,474 discloses a method of identifying an electronic product by using a bipolar antenna to obtain characteristic information of its emitted electromagnetic wave. The method is imperfect as it is quite insensitive to weak electromagnetic waves emitted by electronic products and can barely detect them. For example, the method can hardly detect the electromagnetic waves emitted by a CFL, an electric shaver or an electric toothbrush. Summary of the Invention

To solve the aforesaid problem, there is proposed a technical solution for identifying electronic products by means of the physical characters thereof, for the purpose of detectingfake products. Said electronic products comprise the ones in a low-current area or in a high-current area, the electronic elements of which can be described using the electric or electromagnetic characters.

According to an embodiment of the invention, there is provided a method of obtaining the eigenvector of an operating electronic product, comprising the steps of: a. putting said operating electronic product into a metal coil which receives the electromagnetic wave emitted by said electronic product and converts said electromagnetic wave to an analog electrical signal; b. converting said analog electrical signal generated in said metal coil to a digital electrical signal; c. processing said digital electrical signal, in order to obtain a processed signal sequence as the eigenvector of said electronic product.

The eigenvector means the vector in relation with the spectrum of the electromagnetic wave emitted by an electronic product. Its embodying forms are not limited. Different eigenvectors can be obtained by processing the digital electrical signal in different ways.

According to another embodiment of the invention, there is provided an identifying method of identifying the authenticity of an electronic product, comprising the steps of: i. obtaining the eigenvector of an electronic product to be identified by using the aforesaid method of obtaining an eigenvector; ii. comparing the obtained eigenvector with at least one pre-stored eigenvector sample, and identifying said electronic product as a quality product if the obtained eigenvector matches one of the at least one pre-stored eigenvector sample.

According to another embodiment of the invention, there is provided a character obtaining means for obtaining the eigenvector of an operating electronic product, comprising: a metal coil, configured to receive the electromagnetic wave emitted by an operating electronic product accommodated therein and convert said electromagnetic wave to an analog electrical signal; an AD converter, configured to convert said analog electrical signal to a digital signal; a digital signal processor, configured to process said digital electrical signal so as to obtain a processed signal sequence as the eigenvector corresponding to said electronic product.

According to a further embodiment of the invention, there is provided an identifying device for identifying the authenticity of an electronic product, comprising: an aforesaid character obtaining means; and a comparator, configured to compare the eigenvector obtained by said character obtaining means with at least one pre-stored eigenvector sample, and identify said electronic product as a quality product if the obtained eigenvector matches one of the at least one pre-stored eigenvector samples.

According to another embodiment of the invention, there is provided an identifying system for identifying the authenticity of an electronic product, comprising: a local measurer and a remote server; wherein, the local measurer comprises an aforesaid character obtaining means configured to obtain the eigenvector of an operating electrical product and send said eigenvector to said remote server; said remote server is configured to compare the obtained eigenvector with at least one pre-stored eigenvector sample, and identify the authenticity of said electronic product according to whether the obtained eigenvector matches one of the at least one pre-stored eigenvector samples, and send a response message to said local measurer; said local measurer then receives said response message from said remote server and displays the authenticity of said electronic product according to said response message.

The present invention has adopted a metal coil, so that it is capable of detecting weak electromagnetic waves, and the range of electronic products that can be identified using the characteristic information of its emitted electromagnetic waves is effectively enlarged. By using the eigenvector obtaining algorithm and voltage applying strategy of the present invention, the character obtaining means can obtain a stable eigenvector, so that the identification rate can be improved.

Brief Description of the Drawings

Other objects, features and advantages of the present invention will appear in the following description of non-limiting exemplary embodiments, with reference to the appended drawings.

Fig.l illustrates a block diagram of the structure of a character obtaining means 100 according to an embodiment of the present invention;

Fig.2 illustrates the frequency spectrum amplitude of the electromagnetic wave emitted by a CFL operating in the normal state (AC 220V);

Fig.3 illustrates the frequency spectrum amplitudes of the electromagnetic waves emitted by four CFLs having the same nominal values and operating in the same state (AC 220V);

Fig.4 shows the flowchart of the method of obtaining the eigenvector of an operating electronic product by using the character obtaining means 100 shown in Fig.l, according to an embodiment of the invention;

Fig.5 illustrates the distribution of the frequency spectrum amplitudes of the electromagnetic wave emitted by a CFL at different operating voltages;

Fig.6 shows the flowchart of the algorithm of extracting the harmonic component from the frequency spectrum signal, according to an embodiment of the invention;

Fig.7 respectively illustrates the frequency spectrum amplitude of CFL Ll operating at 210V and 220V, and the frequency spectrum amplitudes of CFL Ll and L2 operating at 210V;

Fig.8(a) illustrates the frequency drift of a CFL under multiple measurements;

Fig.8(b) shows a schematic view of setting the rising edge and falling edge as a fixed value;

Fig.9 shows a flowchart of extracting the eigenvector from the signal in a frequency domain after DFT, by using a two-conversion method, according to an embodiment of the invention;

Fig.10 illustrates the step S903 in Fig.9 in detail;

Fig.l 1 illustrates a variation of the character obtaining means 100 shown in Fig.l ;

Fig.l2(a) illustrates the conventional voltage applying strategy, and Figs 12(b)-12(c) illustrate the two voltage applying strategies proposed in the present invention;

Fig.l3(a) illustrates the frequency spectrum curves obtained in four measurements, with respect to a CFL by means of the conventional voltage applying strategy shown in Fig.l2(a);

Fig.l3(b) illustrates the frequency spectrum curves obtained in four measurements, with respect to a CFL by means of the voltage applying strategy shown in Fig.l2(c);

Fig.14 illustrates an identifying system according to an embodiment of the present invention;

Fig.15 illustrates an identifying device according to an embodiment of the present invention;

In the drawings, same or similar reference signs denote same or similar step features and/or apparatus (module).

Detailed description of embodiments

Fig.l illustrates a block diagram of the structure of a character obtaining means 100 for obtaining the eigenvector of an operating electronic device, according to an embodiment of the present invention. The character obtaining means 100 comprises a metal coil 101, an AD convertor 102, a digital signal processor 103. Preferably, the character obtaining means 100 further comprises an analog filter 104. In addition, Fig.l further shows an electronic product to be identified 105 located in the metal coil 101. Without loss of generality, a CFL is taken as an example of the electronic product to be identified 105 in Fig.l, and said electronic product further comprises an AC power source 106 configured to supply power to the CFL. Of course, if the electronic product to be identified 105 has its own power source, e.g. an electric shaver, the power source 106 will be unnecessary.

In Fig.l, the metal coil functions as an antenna. It can capture wireless electromagnetic waves in a very wide frequency band range and very large power dynamic range in its neighboring space. A copper coil made according to the present invention is capable of measuring the electromagnetic signal having a frequency range from 10Hz to 50GHz, and a power range from 0 to 10OdBm. It is very easy to make such a metal coil. For example, a segment of metal wire can be wound around a cylinder, and the two ends of it are provided with an AD converter to form an electric loop.

The oscillation frequency of the electromagnetic wave emitted by a CFL operating in the normal state of operation typically ranges from 2OkHz to 30 kHz, or from 4OkHz to 50kHz. There always exists a harmonic signal of the oscillation frequency in the electromagnetic wave emitted by a CFL. Fig.2 illustrates the power spectrum amplitude of the electromagnetic wave emitted by a CFL operating in the normal state of operation(AC 220V). In Fig. 2, the abscissa stands for the frequency (Hz), and the ordinate stands for the power (dBm). The shape of the frequency spectrum of the electromagnetic wave emitted by each operating CFL is exclusive and it is an intrinsic physical feature of the CFL which can not be duplicated. The same applies for other kinds of electronic products, and can be referred to as the Physically Unclonable Feature (abbr. PUF). Since electronic products of the same type have similar but different PUFs, PUF can be considered as the DNA of electronic products.

The numerous elements on the circuit board are chosen according to their nominal values when CFLs are manufactured. As a matter of fact, each physical parameter of these elements never assumes exactly the nominal value, and will hover in an acceptable range around the nominal value. Hence, the frequency spectrum of the electromagnetic wave emitted by each CFL will be different due to the different parameters of the elements, even though they are of the same type. Furthermore, the layout of the major functioning components in a CFL will affect the frequency spectrum structure of the emitted electromagnetic wave.

Certainly, the aforesaid difference between CFLs will not have an impact on the user experience, but causes the frequency spectrum of the electromagnetic wave emitted by operating CFLs to be different. Therefore, the frequency spectrum characteristic can be used to identify each CFL.

Fig.3 illustrates power spectrums of the electromagnetic wave emitted by four CFLs having the same nominal values and being in the same state of operation (AC 220V). It should be noted that the distribution of power spectrums in Fig.3 is a result of the translation of the distribution of actual power spectrums (similar to the distribution of power spectrums shown in Fig.2). In Fig. 3, the patterns of the power spectrums are kept unchanged, and the meaning of the ordinate changes from absolute power value to relative power value denoted by dB. It can be seen in Fig.3 that the power spectrums of the four CFLs have different patterns.

Fig.4 shows the flowchart of the method of obtaining the eigenvector of an operating electronic product by using the character obtaining means 100 shown in Fig.l, according to an embodiment of the invention. Hereinafter, the flow shown in Fig.4 will be described in conjunction with the character obtaining means 100 shown in Fig.l.

Firstly, in step S401, the operating electronic product 105 is put in the metal coil 101. The metal coil 101 receives the electromagnetic wave emitted by the electronic product 105 and converts it to an analog electrical signal.

Then, in step S402, the analog electrical signal generated in the metal coil is converted to a digital electrical signal, and the function of this step is fulfilled by the AD convert or 102.

Finally, in step S403, the digital electrical signal obtained in step S402 is further processed so as to obtain a processed eigenvector as the eigenvector of said electronic product.

Preferably, between the steps S401 and S402, the method further comprises a filtering step (not shown in Fig.4) for filtering the analog electrical signal, so as to filter out the noise and undesired electromagnetic signals. The function of filtering can be performed by the analog filter 104 shown in Fig.l. Since the frequency spectrums of the electromagnetic wave emitted by electronic products of the same type distribute in substantially the same bandwidth, in practical use, the bandwidth of the analog filter can be set according to the type of electronic product to be identified 105.

Hereinafter, the process of obtaining the eigenvector by means of digital signal processor 103 in step S403 will be described in detail with the aid of examples.

The digital electrical signal (hereinafter referred to as 'digital signal' for short) converted by the AD convertor 102 is delivered directly to the digital processor 103 to be processed so as to obtain the eigenvector. In many cases, with a view to reducing the cost of the character obtaining means 100, the digital signal processor 103 can be composed of a very simple Micro Processor Unit and a memory. At present, the digital signal outputted by the AD convertor 102 cannot be processed in real time. The outputted digital signal will be stored in the memory and then processed by the microprocessor unit.

Preferably, the digital signal processor 103 can further comprise a digital filter, which is configured to perform digital filtering on the digital signal converted by the AD convertor 102, so as to reduce the sampling rate of the digital signal.

The amplitude of the electromagnetic wave emitted by an electronic product is not very stable in the time domain, but the frequency spectrum of its time-domain signal is comparatively stable. However, the noise and the inaccurate sampling time may also cause a small change of the frequency spectrum amplitude. Hence, for a better identifying effect, multiple samplings are performed during a certain time duration, and then the average value of the power spectrums of the time-domain signals obtained after each sampling will be calculated so as to obtain a stable frequency spectrum signal.

Even though a stable frequency spectrum signal can be obtained by multiple samplings during a certain time duration, the frequency spectrum emitted by an electronic product still changes, especially the oscillation frequency thereof drifts, due to the change of environment, temperature, voltage and the circuit status inside the electronic product, e.g. different initial status of a capacitance or an inductance with memory effect.

Fig.5 illustrates the distribution of the frequency spectrum of the electromagnetic wave emitted by a CFL at different operating voltages. In Fig. 5, the solid lines stand for the distribution of the power spectrums of the electromagnetic wave emitted at 210V operating voltage, while the dotted lines stand for the power spectrums of the electromagnetic wave emitted at 240V operating voltage. The abscissa stands for frequency, and the ordinate stands for the relative power.

It can be seen in Fig.5 that the frequency of the electromagnetic wave emitted by the CFL drifts due to the different operating voltages. If the power spectrum signal after DFT is compared directly without compensating the drift of frequency, the measurement results of a CFL at different voltages will be regarded as the measurement results of different CFLs, so that it is impossible to identify a CFL.

In order to control the drift of frequency, the present invention provides two methods of extracting the eigenvector on the basis of the power spectrum signal: one method relates to extracting the amplitude of the harmonic component of the power spectrum signal as the eigenvector; the other relates to the two-conversion method. These two methods will be described infra.

The first method is explained in detail hereinbelow.

Fig.6 shows the flowchart of the algorithm of extracting the harmonic component from the spectrum signal.

The power spectrum signal sequence of the time-domain signal after DFT is defined as s(n), n=l,...,N, wherein, the time-domain signal is in correspondence with the electromagnetic wave emitted by the electronic product. The power spectrum signal sequence can be the power spectrum signal after a sampling conversion, or the average power spectrum signal after multiple sampling conversions.

Firstly, in step S601, k=l, n=0.

Then, in step S602, n=n+l.

After that, in step S 603, it is determined whether n>N. If n>N, the method continues to the final step S 607 to accomplish the extraction of the amplitude of the harmonic component of the signal sequence s(n); if n < N, the step S604 is performed.

In step S604, it is determined for each s(n) whether it is the peak of a segment of a continuous signal, i.e. whether this s(n) is the biggest among the points from the N 1^st point prior to this point to the N2^nd one behind this point. It can also be expressed as an equation: s(n)=max(s(min(l,n-Nl):max(N,n+N2)))?. Of course, the special circumstances that n-Nl<l and n+N2>N should be taken into consideration.

If s(n) is not equal to max(s(min(l,n-Nl):max(N,n+N2))), then the method goes to step S602.

If s(n)=max(s(min(l,n-Nl):max(N,n+N2))), step S605 is performed.

In step S605, f_k=s (min (l,n-Kl):max(N,N+K2)), and f_k is stored as the k^th characteristic signal sequence.

Then, in step S606, k=k+l.

After step S606 is performed, the method goes back to step S602. The flow is performed circularly until n=N, and the obtained k characteristic signal sequences are stored as the eigenvectors of the electronic product.

The values taken by Nl, N2, Kl and K2 vary with the product type. In practical use, the values can be determined according to multiple measurement experiments.

In the identifying process, the eigenvectors obtained by means of the flow shown in Fig.6 can be identified by using the Piecewise Minimized MSE (abbr. PWMMSE) method described hereinbelow, in order to control the drift of frequency.

For example, in two measurements, the obtained eigenvectors are respectively fi,...,fk and gi, ...gk. The PWMMSE of the two sets of eigenvectors are calculated with a fixed displacement.

For each f_k and g_t, k=l,...K, the MSE e^ between them is calculated: e_k = mill ||Λ (max(U - D - ^min(^ N - l)) - _gk (max(l,l - /) + / : min(_V, N - /) + /)||

I -L, ,L

The PWMMSE d of the two sets of eigenvectors are:

K K

^{J =} Σ^ ⁼ ∑min||Λ(^maχ(¹ _' ¹-/) : min(N,N -/)) - ^(max(l,l-/) + / : min(N,N -/) + / k=\ k=\ I -L, ,L

Here, r is defined as a preset system threshold. If d>r, then it is taken that the aforesaid two measurements are performed on different CFLs; if d<r, then it is taken that the aforesaid two measurements are performed on the same CFL.

Hereinbelow, the advantages of the aforesaid PWMMSE method will be explained by means of an example. For this purpose, an example with 3 CFLs denoted by respectively Ll, L2 and L3 is used. Fig.7 illustrates respectively the frequency spectrum distribution of CFL Ll at 210V and 220V, and the frequency spectrum distribution of CFL Ll, L2 at 210V. The ordinate in Fig.7 stands for relative power. The eigenvectors of the four measurements are obtained according to the flow shown in Fig.6.

If a normal MSE method instead of the aforesaid PWMMSE method is adopted, the MSE between the eigenvectors of L2 and L3 will be 2181187, and the MSE between the eigenvectors of Ll at two different voltages, i.e. 210V and 220V, will be 3265690. If the preset system threshold r is set as r<2181187, then the two measurements with respect to Ll will be regarded as measurements with respect to different CFLs, while L2 and L3 will be regarded as the same CFL.

If the aforesaid PWMMSE method is adopted, then the PWMMSE between the eigenvectors of L2 and L3 will be 431804, and the PWMMSE between the eigenvectors of Ll at two different voltages, i.e. 210V and 220V, will be 367901. If the preset system threshold r is set as 36709 l<r<431804, then the two measurements with respect to Ll will be regarded as measurements with respect to the same CFL, while L2 and L3 will be regarded as different CFLs, so as to realize an accurate identification.

In the previous paragraphs, the first method of extracting the eigenvector, i.e. extracting the amplitude of the harmonic component from the power spectrum signal as the eigenvector and using the PWMMSE method in the identifying process, is described in detail. The second method of extracting the eigenvector, namely the two-conversion method, will be explained in detail.

Fig.5 illustrates the distribution of the frequency spectrum of the electromagnetic wave emitted by a CFL at different operating voltages. Sometimes, at the same operating voltage, the frequency of the electromagnetic wave emitted by the same electronic product will drift due to different temperatures, humidity and so on. Fig.8 (a) clearly illustrates the frequency drift of the power spectrum of a CFL in multiple measurements under the same measurement conditions. Likewise, the ordinates in Fig. 8 (a) and Fig.8 (b) stand for relative power.

To control the drift of frequency, it is necessary to extract the characters which are irrelevant to the drift of frequency. It is well known that, if the signals obtained after performing IDFT on the frequency-domain signals obtained by two measurements have the same amplitude and different phase, the two measurements can be considered as being performed on the same electronic product. Therefore, the problem of frequency drift can be controlled by means of this character. With respect to the IDFT signal of the whole frequency spectrum signal, in general, it is emphasized to extract the main lobe component 82 (also referred to as the global feature), while the side lobe component 81 (also referred to as the local feature) is often ignored, as shown in Fig.8 (a). In the two-conversion method of the present invention, a sliding zero-padding window is adopted to perform an IDFT process on the power spectrum signal, and both the main lobe component and the side lobe component are extracted. From a simulation it is found that the rising edge signal and falling edge signal of the power spectrum signal caused by the frequency spectrum estimation method in measuring instruments are very hard to be aligned during an IDFT process, which leads to the loss of information. One solution in this regard is to truncate the original frequency spectrum chart, and set the rising edge and the falling edge as a fixed value respectively. The fixed values can be somewhat before the rising edge starts/somewhat after the falling edge ends, as shown in Fig.8 (b).

Fig.9 shows a flowchart of extracting the eigenvector from the power spectrum signal after DFT by using a two-conversion method, according to an embodiment of the invention. The flow shown in Fig.9 will be described hereinbelow.

Firstly, in step S901, the rising edge and falling edge of the power spectrum signal are searched. There are many ways of searching the rising edge and falling edge of the power spectrum signal; see the method of extracting a harmonic component shown in Fig.6.

Then, in step S 902, the N points prior to the peak (namely the rising edge) are set as same fixed values, and the M points after the verge are also set as same fixed values, so as to obtain a frequency-domain signal sequence after the edge process. The values taken by N and M vary with the type of product and the sampling frequency. In practical use, they can be determined according to times of measurement experiment. For example, the rising edge and the falling edge can be set as any value between the peak of the power spectrum signal sequence and the minimum of the power spectrum signal sequence. The fixed values taken by the rising edge and falling edge can be the same or not.

After that, in step S903, a zero-padding sliding window is adopted to perform IDFT on the processed frequency-domain signal sequence, and the transformed signal sequence is taken as the eigenvector.

Fig.10 illustrates the step S903 in Fig.9 in detail. Here, a power spectrum signal sequence a(l), a(2), ...,a(800) is taken as an example, wherein, the step size is 10, and the length is 16. This power spectrum signal sequence is grouped, and each group of signals will be padded with zeros, and then experience IDFT. As shown in Fig.10, after zero padding, the group sequence a(l l ), ..., a(26) becomes: 0,0,a(l l),...,a(26),0,0; after performing IDFT on this sequence, a sequence b(l), b(2),...,b(20) will be obtained. f2 is defined as[ b(2) b(3) ... b(l l)]'. For each group of signals, a part of the signals, fl,f2, ...,f80, in the sequence after IDFT are obtained, and compose an eigenvector matrix MF=[fl ;f2;... ;f80].

During the identifying process, it can be determined whether the eigenvectors in two measurements belong to the same electronic product by determining whether the MSE of the eigenvector matrix of the two measurements is below the preset system threshold.

In the previous paragraphs, the second method of extracting the eigenvector, i.e. the two-conversion method, is described in detail.

For some electronic products like CFL, due to the memory effect of the elements therein, the frequency spectrum of the electromagnetic wave emitted by the electronic product depends on its historical parameters, such as temperature, residual charges of its internal circuits. Under the conventional voltage applying strategy, the operating voltage of the electronic product changes suddenly from 0 to target operating voltage V_T- After a heating-up period T3 of 120s as shown in Fig.l2(a), the measurement of the frequency spectrum of the electromagnetic wave emitted by the electronic product begins. In Fig.l2(a), for example, the measurement takes T4 (50s).

To control the memory effect, on the basis of the character obtaining means 100 as shown in Fig.l, there is further provided a character obtaining means 100' which is configured to control the manner of applying the operating voltage to an electronic product. Unlike the character obtaining means 100 shown in Fig.l, the character obtaining means 100' shown in Fig.l 1 further comprises a voltage controller 107.

Before measuring the frequency spectrum of the electromagnetic wave emitted by the electronic product, the voltage controller 107 will switch on the power source of the electronic product, and after Tl (e.g. 10 seconds), the power source will be switched off. After T2 (e.g. 2 seconds), the power source of the electronic product will be switched on again. In this way, the impact caused by the memory effect can be eliminated, and the measurement with respect to the frequency spectrum of the electromagnetic wave emitted by the electronic product can be started.

Frequently, the frequency spectrum of the electromagnetic wave emitted by the electronic product still comprises some uncertain components brought about by the sudden change of the voltage from OV to the target operating voltage V_T (e.g. 220V). Therefore, it is suggested in the present invention that the voltage should rise gradually at a rather low speed from 0 to the operating voltage, as the rising speed of the voltage should be controlled. For example, for an AC power supply at 50Hz, the voltage rises from OV to the target operating voltage continuously and gradually within 1 second rather than the conventional 0.01 second. Alternatively, the voltage can rise to the target voltage in one or more seconds in a discrete way with multiple phases (0, 0.2VT, 0.4V_T, 0.6V_T, 0.8V_T, V_x).

Fig.l2(a) illustrates the conventional voltage applying strategy, and Figs 12(b)-12(c) respectively illustrate the two voltage applying strategies proposed in the present invention. In Fig.l2(b), the voltage rises continuously to the target operating voltage, and in Fig.l2(c), the voltage rises to the target operating voltage in a discrete way.

It should be noted that the values taken by Tl, T2, T3 and T4 in Figs. 12 are just examples. The values may vary with the type of product. In practical usage, the values can be determined according to multiple measurement experiments.

Fig.l3(a) shows the power spectrum curves obtained in four measurements with respect to a CFL according to the conventional voltage applying strategy shown in Fig.l2(a). Fig.l3(b) shows the power spectrum curves obtained in four measurements with respect to a CFL according to the voltage applying strategy shown in Fig.l2(c). The four measurements are carried out under the same conditions, that is to say the same voltage, the same temperature, and the same humidity. It can be seen in Fig.13 (a) and Fig.13 (b) that, with the conventional voltage applying strategy shown in Fig.12 (a), there are big drifts in the frequency and amplitude of the power spectrums obtained in four measurements, while with the voltage applying strategy shown in Fig.12 (b), the drifts in the frequency and amplitude of the power spectrums obtained in four measurements decrease substantially.

Since there are always tens of thousands of electronic products of the same type, to differentiate better between them, different operating voltages are applied to each electronic product. At each of these operating voltages, the eigenvector corresponding to this voltage is obtained. Then, the combination of the eigenvectors obtained at different operating voltages is regarded as the eigenvector of the electronic product.

For example, for a CFL, we can obtain its eigenvectors at four voltages: 180V, 200V, 220V and 240V, and use the combination of the four eigenvectors as the eigenvector of the CFL. The voltage controller 107 shown in Fig.11 can be used to change the voltage.

The method of extracting eigenvectors and the comparison of eigenvectors of an electronic product are described above. It should be noted that the aforementioned embodiments of the method of extracting an eigenvector can be implemented individually or in combination. For example, in a character obtaining means, there can be comprised an analog filter and a voltage controller. In addition, a CFL is taken as an example to explain the method of extracting an eigenvector and the comparison of eigenvectors, and people skilled in the art will understand that the aforementioned method of extracting an eigenvector and the comparison of eigenvectors are also applicable to electronic products of other types, such as electric shavers, electric toothbrushes, etc.

The process of identifying the authenticity of an electronic product by means of the aforementioned extracted eigenvector will be described hereinbelow.

According to an embodiment of the present invention, the eigenvector of each electronic product is obtained by character obtaining means 100 or 100' and stored in the database as an eigenvector sample, before the electronic product enters the market. After an electronic product enters the market, the end users or dealers can use the character obtaining means 100 or 100' to obtain the eigenvector of the electronic product, and compare the obtained eigenvector with at least one pre-stored eigenvector sample. If the obtained eigenvector matches one of the at least one eigenvector samples, the electronic product is identified as a quality product.

Concretely, according to different positions of the database storing the eigenvector samples, said identifying process has two modes: the remote mode and the local mode. Below, the two modes will be described in detail.

The remote mode

The remote mode means that the database storing the eigenvector samples is located in the remote server 141 of the manufacturer of the electronic product ('remote' from the point of view of the identifier). As shown in Fig. 14, there is a local measurer 142 located at the end user's or dealer's location. The local measurer 142 comprises a character obtaining means 100 or 100' and is connected with the remote server 141 to compose an identifying system, as shown in Fig.14. The remote server 141 comprises a database 1411 storing the eigenvector samples and a processing center 1412. The local measurer 142 obtains the eigenvector of an operating electronic product and sends the eigenvector to the remote server 141. The remote server 141 compares the received eigenvector with at least one pre-stored eigenvector sample; if the obtained eigenvector matches one of the at least one pre-stored eigenvector samples, the electronic product is identified as a quality product, and then a response message will be sent to the local measurer 142.

The local measurer 142 receives the response message from the remote server 141, and displays the authenticity of the electronic product according to the response message.

In the remote server 141, if the obtained eigenvector can not match any pre-stored eigenvector sample, a response message indicating 'no match' will be sent to the local measurer 142. Alternatively, the remote server 141 does not send such a message. The remote server 141 and the local measurer 142 agree that if no response message is received within a predefined period of time, the electronic product to be identified shall be identified as a counterfeit.

It should be noted that the term 'match' mentioned here means the PWMMSE or MSE between the obtained eigenvector and an eigenvector sample is below a predefined system threshold.

If there are eigenvector samples of different types of electronic products stored in the database, the identification result can be rapidly obtained, when sending the eigenvector of the electronic product to the remote server 141, if the local measurer 142 also sends the product classifying information to the remote server 141, so that the remote server 141 can search for the matched eigenvector sample in the eigenvector samples of this type of products.

The local mode

The local mode means that the database storing the eigenvector samples is located in the identifying device 151 at the end user's or dealer's location. Fig.15 illustrates an identifying device 151 according to an embodiment of the present invention. The identifying device 151 comprises a character obtaining means 100 or 100', a database 1411 for storing the eigenvector samples, and a comparator 1511. The identifying device 151 can accomplish the identification of the authenticity of an electronic product without communicating with the remote server 141.

The operating method of the identifying device 151 is described below:

Firstly, the character obtaining means 100 or 100' in the identifying device 151 obtains the eigenvector of the operating electronic product.

Then, the comparator 1511 compares the obtained eigenvector with at least one pre-stored eigenvector sample. If the result shows that the obtained eigenvector matches one of the at least one pre-stored eigenvector samples, the electronic product is identified as a quality product.

Once an electronic product is identified as a quality product, the pre-stored information in relation to the electronic product can be provided to the identifier, e.g. the dealer or end user.

The two identifying modes are explained in the paragraphs above. The two modes both have their advantages and disadvantages. In practical use, the choice can be made according to the requirements. The advantages of the remote mode consist in that the local measurer 142 is simple and low-cost, because the eigenvector samples are all in a central remote server 141; the disadvantages thereof are that the local measurer 142 has to communicate with the remote server 141 frequently, and the identifying process may take too long if there is a communication delay. The advantages of the local mode are that there is no need for the communication between the identifying device 151 and the remote server 141, and the speed of identifying is high; the disadvantages consist in that it is costly, and each identifying device 151 needs to maintain a database of eigenvector samples. Although the embodiments of the present invention have been described above, it should be understood by those skilled in the art that the present invention is not limited to the aforementioned specific embodiments; various modifications can be made without departing from the scope and spirit of the attached claims.

Claims

What is claimed is:

1. A method of obtaining the eigenvector of an operating electronic product, comprising the steps of: a. putting said operating electronic product into a metal coil which receives the electromagnetic waves emitted by said electronic product and converts said electromagnetic waves to an analog electrical signal; b. converting said analog electrical signal generated in said metal coil to a digital electrical signal; c. processing said digital electrical signal in order to obtain a processed signal sequence as the eigenvector of said electronic product.

2. A method as claimed in claim 1, which, after said step a, further comprises the steps of:

- performing analog filtering on said analog electrical signal so as to obtain a filtered analog electrical signal; wherein said step b further comprises the step of:

- converting said filtered analog electrical signal to a digital electrical signal.

3. A method as claimed in claim 1, wherein, the step of processing said digital electrical signal in said step c further comprises the steps of: c21. performing DFT on said digital electrical signal so as to obtain a power spectrum signal sequence; c22. extracting the amplitude of the harmonic component of said power spectrum signal sequence as the eigenvector of said electronic product.

4. A method as claimed in claim 1, wherein the step of processing said digital electrical signal in said step c further comprises the steps of: c31. performing DFT on said digital electrical signal so as to obtain a power spectrum signal sequence; c32. determining the rising edge and the falling edge of said power spectrum signal sequence, and respectively setting the amplitudes of multiple points in the rising edge and the falling edge as same values so as to obtain a signal sequence after the edge process; c33. performing IDFT on said signal sequence after the edge process by using a zero-padding sliding window, and taking the signal sequence after IDFT as the eigenvector of said electronic product.

5. A method as claimed in claim 1, which, before said step a, further comprises the step of:

- controlling the manner of applying the operating voltage to said electronic product, by means of switching on the power supply of said electronic product, switching off said power supply, and switching said power supply on again, wherein the voltage rises gradually from zero to the operating voltage.

6. A method as claimed in claim 1, further comprising the steps of:

- applying different voltages to said electronic product, and executing said steps a, b and c at each of said voltages so as to obtain the eigenvector corresponding to the voltage;

- taking the combination of eigenvectors obtained at said different voltages as the eigenvector of said electronic product.

7. A method of identifying the authenticity of an electronic product, comprising the steps of: i. obtaining the eigenvector of an electronic product to be identified by using a method as claimed in any of claims 1 to 6; ii. comparing the obtained eigenvector with at least one pre-stored eigenvector sample, and identifying said electronic product as a quality product if the obtained eigenvector matches one of the at least one pre-stored eigenvector samples.

8. A character obtaining means for obtaining the eigenvector of a operating electronic product, comprising: a metal coil, configured to receive the electromagnetic wave emitted by a operating electronic product accommodated therein and convert said electromagnetic wave to an analog electrical signal; an AD converter, configured to convert said analog electrical signal to a digital signal; a digital signal processor, configured to process said digital electrical signal so as to obtain a processed signal sequence as the eigenvector corresponding to said electronic product.

9. A character obtaining means as claimed in claim 8, further comprising: an analog filter, configured to perform analog filtering on said analog electrical signal obtained by said metal coil so as to obtain a filtered analog electrical signal and then provide said filtered analog electrical signal to said AD convertor.

10. A character obtaining means as claimed in claim 8, further comprising: a voltage controller, configured to control the manner of applying the operating voltage to said electronic product, so that the voltage rises gradually from zero to the operating voltage.

11. An identifying device for identifying the authenticity of an electronic product, comprising: a character obtaining means as claimed in any of claims 8 to 10; and a comparator, configured to compare the eigenvector obtained by said character obtaining means with at least one pre-stored eigenvector sample, and identify said electronic product as a quality product if the obtained eigenvector matches one of the at least one pre-stored eigenvector samples.

12. An identifying system for identifying the authenticity of an electronic product, comprising: a local measurer and a remote server; wherein said local measurer comprises a character obtaining means as claimed in any of claims 8 to 10, configured to obtain the eigenvector of an operating electrical product and send said eigenvector to said remote server; and said remote server is configured to compare the obtained eigenvector with at least one pre-stored eigenvector sample, and identify the authenticity of said electronic product according to whether the obtained eigenvector matches one of the at least one pre-stored eigenvector samples, and send a response message to said local measurer; said local measurer then receives said response message from said remote server and displays the authenticity of said electronic product according to said response message.