Odor data analysis device, odor data analysis method and odor data analysis program

Abstract

To provide an odor data analysis device, analysis method and analysis program capable of discriminating odor more accurately.SOLUTION: An odor data analysis device has an odor sensor and an analysis unit. The odor sensor is configured to convert an adsorption amount of odorant into a predetermined physical quantity and outputs odor data, which is time-series data. The analysis unit analyzes the odor data, in which: (1) the analysis unit sets the odor data as reference data when the odorant is not substantially detected; (2) the odor sensor outputs the odor data during a detection period; (3) the analysis unit calculates an integral value by integrating a difference between the odor data and the reference data over the detection period; (4) the analysis unit calculates a derivative value by differentiating the odor data over time during the detection period; and (5) the analysis unit calculates a representative value R=(S*Kmin) / Kmax or R=(S*Kmax) / Kmin, where S is an integral value, Kmin is a minimum value of the derivative, and Kmax is a maximum value.SELECTED DRAWING: Figure 5

Description

[Technical Field]

[0001] The present invention relates to an odor data analysis device, an odor data analysis method, and an odor data analysis program. [Background technology]

[0002] Detecting odorants contained in gases has been performed to measure odor intensity and identify the type of odor. For example, Patent Document 1 discloses a configuration for detecting odorants by detecting a change in weight when an odorant is adsorbed onto a sensor element including a substance adsorption film. According to the configuration disclosed in Patent Document 1, the odor sensor outputs a frequency, and the amount of odorant adsorbed onto the substance adsorption film is output as a change in frequency. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] International Publication No. 2017 / 085939 Summary of the Invention [Problem to be solved by the invention]

[0004] However, even when different odor substances are used, there are cases where the change in frequency output from the odor sensor does not differ significantly. In such cases, even if an attempt is made to analyze the amount of adsorption of an odor substance using the change in frequency output from the odor sensor as is, it may be difficult to correctly distinguish between different odors.

[0005] In some cases, the odors of multiple different gases can be distinguished by simultaneously measuring multiple odor substances using multiple odor sensors. In this case, even if the multiple different gases each contain multiple different odor substances at different concentrations, it may be difficult to distinguish between the different gases because there is not much difference in the amount of frequency change output by the multiple odor sensors.

[0006] This tendency is not limited to odor sensors that output frequency, but may also occur in odor sensors that output other physical quantities. Therefore, there has been a need to propose an analytical method that can distinguish odors with even greater accuracy using the physical quantities output by odor sensors.

[0007] The present invention has been made in consideration of the above circumstances, and an exemplary object of the present invention is to provide an odor data analysis device, an odor data analysis method, and an odor data analysis program that can achieve more accurate odor discrimination. [Means for solving the problem]

[0008] In order to solve the above problems, an odor data analysis device according to an exemplary aspect of the present invention has the following configuration.

[0009] An odor data analysis device having an odor sensor and an analysis unit, The odor sensor has an adsorption film that adsorbs an odor substance, detects the odor substance by the odor substance being adsorbed by the adsorption film, and converts the amount of the odor substance adsorbed into a predetermined physical quantity to output odor data that is time-series data. the analysis unit analyzes the odor data output from the odor sensor, (1) The analysis unit sets the odor data output by the odor sensor in a state where the odor substance is not substantially detected as reference data, (2) the odor sensor detects the odor substance during a detection period from a detection start time to a detection end time, and outputs the odor data; (3) The analysis unit calculates an integral value obtained by integrating the difference between the odor data corresponding to the detection period and the reference data over the detection period; (4) The analysis unit calculates a differential value obtained by time-differentiating the odor data during the detection period; (5) When the integral value in (3) is S, the minimum value of the differential value in (4) is Kmin, and the maximum value of the differential value in (4) is Kmax, The odor data analysis device, wherein the analysis unit calculates a representative value R=(S·Kmin) / Kmax or a representative value R=(S·Kmax) / Kmin.

[0010] An odor data analysis device according to another exemplary aspect of the present invention has the following configuration.

[0011] An odor data analysis device having an odor sensor and an analysis unit, The odor sensor has an adsorption film that adsorbs an odor substance, detects the odor substance by the odor substance being adsorbed by the adsorption film, and converts the amount of the odor substance adsorbed into a predetermined physical quantity to output odor data that is time-series data. the analysis unit analyzes the odor data output from the odor sensor, (1) The analysis unit sets the odor data output by the odor sensor in a state where the odor substance is not substantially detected as reference data, (2) the odor sensor detects the odor substance during a detection period from a detection start time to a detection end time, and outputs the odor data; (3) The analysis unit calculates an integral value obtained by integrating the difference between the odor data corresponding to the detection period and the reference data over the detection period; (6) The analysis unit calculates a value of a half width during the detection period, (7) When the integral value in (3) is S and the half width value in (6) is HW, The odor data analysis device, wherein the analysis unit calculates a representative value R=S·HW.

[0012] An odor data analysis device according to yet another exemplary aspect of the present invention has the following configuration.

[0013] An odor data analysis device having an odor sensor and an analysis unit, The odor sensor has an adsorption film that adsorbs an odor substance, detects the odor substance by the odor substance being adsorbed by the adsorption film, and converts the amount of the odor substance adsorbed into a predetermined physical quantity to output odor data that is time-series data. the analysis unit analyzes the odor data output from the odor sensor, (1) The analysis unit sets the odor data output by the odor sensor in a state where the odor substance is not substantially detected as reference data, (2) the odor sensor detects the odor substance during a detection period from a detection start time to a detection end time, and outputs the odor data; (8) The analysis unit calculates a difference value between a detected peak value of the odor data corresponding to the detection period and the reference data, (4) The analysis unit calculates a differential value obtained by time-differentiating the odor data during the detection period; (9) When the difference value in (8) is D, the minimum value of the differential value in (4) is Kmin, and the maximum value of the differential value in (4) is Kmax, The odor data analysis device, wherein the analysis unit calculates a representative value R=(D·Kmin) / Kmax or a representative value R=(D·Kmax) / Kmin.

[0014] An odor data analysis device according to yet another exemplary aspect of the present invention has the following configuration.

[0015] An odor data analysis device having an odor sensor and an analysis unit, The odor sensor has an adsorption film that adsorbs an odor substance, detects the odor substance by the odor substance being adsorbed by the adsorption film, and converts the amount of the odor substance adsorbed into a predetermined physical quantity to output odor data that is time-series data. the analysis unit analyzes the odor data output from the odor sensor, (1) The analysis unit sets the odor data output by the odor sensor in a state where the odor substance is not substantially detected as reference data, (2) the odor sensor detects the odor substance during a detection period from a detection start time to a detection end time, and outputs the odor data; (8) The analysis unit calculates a difference value between a detected peak value of the odor data corresponding to the detection period and the reference data, (6) The analysis unit calculates a value of a half width during the detection period, (10) When the difference value in (8) is D and the half width value in (6) is HW, The odor data analysis device, wherein the analysis unit calculates a representative value R=D·HW.

[0016] A method for analyzing odor data according to a further exemplary aspect of the present invention has the following configuration.

[0017] An odor data analysis method for analyzing odor data, which is time-series data output from an odor sensor, by an analysis unit, comprising: The odor sensor has an adsorption film that adsorbs an odor substance, detects the odor substance by the odor substance being adsorbed by the adsorption film, and converts the amount of the odor substance adsorbed into a predetermined physical quantity to output odor data that is time-series data. the analysis unit analyzes the odor data output from the odor sensor, (1) the analysis unit sets the odor data output by the odor sensor in a state where the odor substance is not substantially detected as reference data; (2) the odor sensor detects the odor substance during a detection period from a detection start time to a detection end time, and outputs the odor data; (3) a step in which the analysis unit calculates an integral value obtained by integrating a difference between the odor data corresponding to the detection period and the reference data over the detection period; (4) the analysis unit calculates a differential value obtained by time-differentiating the odor data during the detection period; (5) When the integral value in (3) is S, the minimum value of the differential value in (4) is Kmin, and the maximum value of the differential value in (4) is Kmax, The odor data analysis method includes a step in which the analysis unit calculates a representative value R=(S·Kmin) / Kmax or a representative value R=(S·Kmax) / Kmin.

[0018] A method for analyzing odor data according to a further exemplary aspect of the present invention has the following configuration.

[0019] An odor data analysis method for analyzing odor data, which is time-series data output from an odor sensor, by an analysis unit, comprising: The odor sensor has an adsorption film that adsorbs an odor substance, detects the odor substance by the odor substance being adsorbed by the adsorption film, and converts the amount of the odor substance adsorbed into a predetermined physical quantity to output odor data that is time-series data. the analysis unit analyzes the odor data output from the odor sensor, (1) the analysis unit sets the odor data output by the odor sensor in a state where the odor substance is not substantially detected as reference data; (2) the odor sensor detects the odor substance during a detection period from a detection start time to a detection end time, and outputs the odor data; (3) a step in which the analysis unit calculates an integral value obtained by integrating a difference between the odor data corresponding to the detection period and the reference data over the detection period; (6) the analysis unit calculates a value of the half width during the detection period; (7) When the integral value in (3) is S and the half width value in (7) is HW, The odor data analysis method includes a step in which the analysis unit calculates a representative value R=S·HW.

[0020] A method for analyzing odor data according to a further exemplary aspect of the present invention has the following configuration.

[0021] An odor data analysis method for analyzing odor data, which is time-series data output from an odor sensor, by an analysis unit, comprising: The odor sensor has an adsorption film that adsorbs an odor substance, detects the odor substance by the odor substance being adsorbed by the adsorption film, and converts the amount of the odor substance adsorbed into a predetermined physical quantity to output odor data that is time-series data. the analysis unit analyzes the odor data output from the odor sensor, (1) the analysis unit sets the odor data output by the odor sensor in a state where the odor substance is not substantially detected as reference data; (2) the odor sensor detects the odor substance during a detection period from a detection start time to a detection end time, and outputs the odor data; (8) a step in which the analysis unit calculates a difference value between a detected peak value of the odor data corresponding to the detection period and the reference data; (4) the analysis unit calculates a differential value obtained by time-differentiating the odor data during the detection period; (9) When the difference value in (8) is D, the minimum value of the differential value in (4) is Kmin, and the maximum value of the differential value in (4) is Kmax, The odor data analysis method includes a step in which the analysis unit calculates a representative value R=(D·Kmin) / Kmax or a representative value R=(D·Kmax) / Kmin.

[0022] A method for analyzing odor data according to a further exemplary aspect of the present invention has the following configuration.

[0023] An odor data analysis method for analyzing odor data, which is time-series data output from an odor sensor, by an analysis unit, comprising: The odor sensor has an adsorption film that adsorbs an odor substance, detects the odor substance by the odor substance being adsorbed by the adsorption film, and converts the amount of the odor substance adsorbed into a predetermined physical quantity to output odor data that is time-series data. the analysis unit analyzes the odor data output from the odor sensor, (1) the analysis unit sets the odor data output by the odor sensor in a state where the odor substance is not substantially detected as reference data; (2) the odor sensor detects the odor substance during a detection period from a detection start time to a detection end time, and outputs the odor data; (8) a step in which the analysis unit calculates a difference value between a detected peak value of the odor data corresponding to the detection period and the reference data; (6) the analysis unit calculates a value of the half width during the detection period; (10) When the difference value in (8) is D and the half width value in (6) is HW, The odor data analysis method includes a step in which the analysis unit calculates a representative value R=D·HW.

[0024] An odor data analysis program according to yet another exemplary aspect of the present invention has the following configuration.

[0025] An odor data analysis program for analyzing odor data, which is time-series data output from an odor sensor, The odor sensor has an adsorption film that adsorbs an odor substance, detects the odor substance by the odor substance being adsorbed by the adsorption film, and converts the amount of the odor substance adsorbed into a predetermined physical quantity to output odor data that is time-series data. The odor data analysis program is installed on a computer. (1) setting the odor data output by the odor sensor in a state where the odor substance is not substantially detected as reference data; (2) causing the odor sensor to detect the odor substance during a detection period from a detection start time to a detection end time and outputting the odor data; (3) calculating an integral value obtained by integrating the difference between the odor data corresponding to the detection period and the reference data over the detection period; (4) calculating a differential value obtained by time-differentiating the odor data during the detection period; (5) When the integral value in (3) is S, the minimum value of the differential value in (4) is Kmin, and the maximum value of the differential value in (4) is Kmax, and calculating a representative value R=(S·Kmin) / Kmax or a representative value R=(S·Kmax) / Kmin.

[0026] An odor data analysis program according to yet another exemplary aspect of the present invention has the following configuration.

[0027] An odor data analysis program for analyzing odor data, which is time-series data output from an odor sensor, by an analysis unit, The odor sensor has an adsorption film that adsorbs an odor substance, detects the odor substance by the odor substance being adsorbed by the adsorption film, and converts the amount of the odor substance adsorbed into a predetermined physical quantity to output odor data that is time-series data. The odor data analysis program is installed on a computer. (1) setting the odor data output by the odor sensor in a state where the odor substance is not substantially detected as reference data; (2) causing the odor sensor to detect the odor substance during a detection period from a detection start time to a detection end time and outputting the odor data; (3) calculating an integral value obtained by integrating the difference between the odor data corresponding to the detection period and the reference data over the detection period; (6) calculating a half-width value during the detection period; (7) When the integral value in (3) is S and the half width value in (7) is HW, and a step of calculating a representative value R=S·HW.

[0028] An odor data analysis program according to yet another exemplary aspect of the present invention has the following configuration.

[0029] An odor data analysis program for analyzing odor data, which is time-series data output from an odor sensor, by an analysis unit, The odor sensor has an adsorption film that adsorbs an odor substance, detects the odor substance by the odor substance being adsorbed by the adsorption film, and converts the amount of the odor substance adsorbed into a predetermined physical quantity to output odor data that is time-series data. The odor data analysis program is installed on a computer. (1) setting the odor data output by the odor sensor in a state where the odor substance is not substantially detected as reference data; (2) causing the odor sensor to detect the odor substance during a detection period from a detection start time to a detection end time and outputting the odor data; (8) calculating a difference value between the detected peak value of the odor data corresponding to the detection period and the reference data; (4) calculating a differential value obtained by time-differentiating the odor data during the detection period; (9) When the difference value in (8) is D, the minimum value of the differential value in (4) is Kmin, and the maximum value of the differential value in (4) is Kmax, and calculating a representative value R=(D·Kmin) / Kmax or a representative value R=(D·Kmax) / Kmin.

[0030] An odor data analysis program according to yet another exemplary aspect of the present invention has the following configuration.

[0031] An odor data analysis program for analyzing odor data, which is time-series data output from an odor sensor, by an analysis unit, The odor sensor has an adsorption film that adsorbs an odor substance, detects the odor substance by the odor substance being adsorbed by the adsorption film, and converts the amount of the odor substance adsorbed into a predetermined physical quantity to output odor data that is time-series data. The odor data analysis program is installed on a computer. (1) setting the odor data output by the odor sensor in a state where the odor substance is not substantially detected as reference data; (2) detecting the odor substance during a detection period from a detection start time to a detection end time, and outputting the odor data; (8) calculating a difference value between the detected peak value of the odor data corresponding to the detection period and the reference data; (6) calculating a half-width value during the detection period; (10) When the difference value in (8) is D and the half width value in (6) is HW, and a step of calculating the representative value R=D·HW.

[0032] Further objects and other features of the present invention will become apparent from the following description of preferred embodiments with reference to the accompanying drawings. [Effects of the Invention]

[0033] According to the present invention, it is possible to realize odor discrimination with higher accuracy. [Brief explanation of the drawings]

[0034] [Figure 1] 1 is a schematic diagram showing a schematic configuration of an odor data analysis device according to a first embodiment. [Figure 2] FIG. 2 is a schematic diagram showing the general configuration of the odor sensor shown in FIG. [Figure 3] FIG. 2 is a diagram showing the state in which a plurality of different types of adsorption films are formed on the odor sensor shown in FIG. [Figure 4]2 is a graph showing an output waveform of odor data output from the odor sensor shown in FIG. 1. [Figure 5] 1 is a flowchart illustrating an odor data analysis method according to Type A in the first embodiment. [Figure 6] 1 is a flowchart illustrating an odor data analysis method according to Type B in the first embodiment. [Figure 7] 1 is a flowchart illustrating an odor data analysis method according to Type C in the first embodiment. [Figure 8] 1 is a flowchart illustrating an odor data analysis method according to Type D in the first embodiment. [Figure 9] 1 shows a schematic configuration of an odor sensor unit according to a second embodiment. [Figure 10A] FIG. 1 is a diagram showing the evaluation results of Example 1. [Figure 10B] FIG. 1 is a diagram showing the evaluation results of Example 1. [Figure 11A] FIG. 10 is a diagram showing the evaluation results of Example 2. [Figure 11B] FIG. 10 is a diagram showing the evaluation results of Example 2. [Figure 12A] FIG. 10 is a diagram showing the evaluation results of Example 3. [Figure 12B] FIG. 10 is a diagram showing the evaluation results of Example 3. [Figure 13] FIG. 10 is a diagram showing the evaluation results of Example 4. [Figure 14] FIG. 10 is a diagram showing the evaluation results of Example 5. DETAILED DESCRIPTION OF THE INVENTION

[0035] [Embodiment 1] The odor data analysis device S1 according to embodiment 1 will be described below with reference to the drawings. Fig. 1 is a schematic diagram showing the general configuration of the odor data analysis device S1 according to embodiment 1. The odor data analysis device S1 is generally configured to include an odor sensor 10 and an analysis unit 20.

[0036] <Odor Sensor 10> FIG. 2 is a schematic diagram showing the overall configuration of an odor sensor 10. The odor sensor 10 is a sensor for detecting odor substances. The odor sensor 10 has a base 2 and an adsorption film 4. The adsorption film 4 is formed on the surface of the base 2. The base 2 has the function of converting the amount of odor substance adsorbed on the adsorption film 4 into a predetermined physical quantity and outputting time-series data of the physical quantity. Examples of physical quantities include frequency, charge amount (potential), and current value. In this application, the time-series data of the physical quantity output from the odor sensor 10 is referred to as odor data F1.

[0037] For example, a quartz crystal sensor (QCM) can be used as the base 2, and in the first embodiment, a QCM will be described as an example. In this case, the physical quantity is frequency. Furthermore, for example, a CMOS sensor can be used as the base 2. In this case, the physical quantity is charge (potential). Other sensors that can be used as the base 2 include surface acoustic wave sensors, field effect transistors (FETs), charge coupled device sensors, MOS field effect transistors, metal oxide semiconductor sensors, organic conductive polymer sensors, and electrochemical sensors.

[0038] The adsorption film 4 has the function of adsorbing odorous substances contained in the gas surrounding the adsorption film 4. Odorous substances are substances that cause odors. Gas containing odorous substances emits an odor specific to that odorous substance. Examples of odorous substances include acetic acid and ammonia. Components contained in various herbal plants such as eucalyptus, citrus fruits such as lychee, and various spices can also be odorous substances. A gas may contain multiple odorous substances. By containing multiple odorous substances, the multiple odors may be blended, resulting in a gas with a different odor from each odorous substance.

[0039] As shown in Figure 2, the adsorption film 4 is constructed by adding an additive (dopant) 6 to a conductive polymer film 5 as a film material. The function of the adsorption film 4 to adsorb odorous substances is realized by the additive 6 adsorbing specific odorous substances. Depending on the type of additive 6, the adsorption film 4 can adsorb different odorous substances.

[0040] As shown in Figure 3, multiple different types of adsorption films 4a-4c may be formed on the base 2. The different adsorption films 4a-4c correspond to different additives 6a-6c, respectively. The different additives 6a-6c selectively adsorb different odor substances.

[0041] The number of adsorption films 4 formed on the surface of the base 2 is arbitrary, and may be one type as shown in Figure 2, or three types as shown in Figure 3, or more. For example, if the base 2 is a quartz crystal sensor, one type of adsorption film 4 can be formed on the surface of one base 2, and three bases 2 can be arranged in a row. For example, if the base 2 is a CMOS sensor, multiple types of adsorption films 4 can be formed on the surface of one base 2.

[0042] If the base 2 is a CMOS sensor, the numerous detection elements on the sensor (e.g., 3N sensor elements) may be divided into multiple regions (e.g., 3 regions), and one type of adsorption film may correspond to a group of N detection elements in each region. Specific examples of the base 2 and adsorption film 4 that make up the odor sensor 1 will be described later.

[0043] <Analysis section 20> The analysis unit 20 is for analyzing the odor data F1 output from the odor sensor 10. As shown in FIG. 1, the analysis unit 20 is primarily configured with a central processing unit (CPU) 20a, and may also have a storage device (memory) 20b. The memory 20b may, of course, be provided externally, separate from the analysis unit 20. The analysis unit 20 also has a data input / output port 20c. The input / output port 20c has the function of receiving the odor data F1 from the odor sensor 10 and the function of transmitting a representative value R as calculated data resulting from the calculation processing performed by the CPU 20a to a control unit (not shown).

[0044] The memory 20b stores an analysis program (odor data analysis program) P. This analysis program P causes the analysis unit 20 as a computer, i.e., the CPU 20a as the main component of the analysis unit 20, to execute the calculation process described below, thereby realizing the analysis of odor data.

[0045] <Odor data F1> FIG. 4 is a graph showing the output waveform of odor data F1 output from the odor sensor 10. In this embodiment 1, a QCM sensor is used as the base 2 of the odor sensor 10. Therefore, the physical quantity output from the odor sensor 10 is frequency. In FIG. 4, the vertical axis is frequency f, and the horizontal axis is time t. The frequency f on the vertical axis is set as the reference frequency (reference data) f0, which is the frequency f when the odor sensor 10 is in a state where it has not substantially adsorbed any odorous substance, i.e., is in a state where it is not substantially detecting any odorous substance. In FIG. 4, the reference frequency f0 = 0 Hz. The time t on the horizontal axis indicates the elapsed time when a specific reference time is set to 0.

[0046] 4 shows how odor data F1 output from one odor sensor 10 changes over time. This odor sensor 10 has one type of adsorption film 4 formed on one base 2. Therefore, the one type of adsorption film 4 has the property of adsorbing a specific odor substance.

[0047] An odor sensor 10 using a different adsorption film 4 that easily adsorbs different odor substances will exhibit a different output waveform. By arranging multiple odor sensors 10 using multiple adsorption films that easily adsorb multiple different odor substances, each odor sensor 10 will react to the multiple odor substances contained in the gas, making it possible to identify the odor of the gas.

[0048] In the first embodiment, when an odorant is adsorbed onto the adsorption film 4, the value of the frequency f output from the odor sensor 10 decreases from a value near 0. Therefore, in FIG. 4, when an odorant is adsorbed onto the adsorption film 4 of the odor sensor 10, the graph of odor data F1 drops downward. Whether the odor data F1 changes to a positive or negative value when an odorant is adsorbed onto the adsorption film 4 of the odor sensor 10 is a design decision. Depending on the properties of the adsorption film 4 and the output format of the odor sensor 10, the odor data F1 may increase as the odorant is adsorbed. In this case, the magnitude relationship of the odor data F1 in the first embodiment may be reversed. FIG. 4 shows the start time (detection start time) ts, the end time (detection end time) te, the peak time tp, and the peak frequency (detection peak value) fp.

[0049] The start time ts is the time when the adsorption film 4 begins to adsorb an odorant. The start time ts may also be the time when the value of the frequency f of the odor data F1 begins to change. That is, the start time ts may be the time when the absolute value of the frequency f exceeds a certain value, or the start time ts may be the time when the absolute value of the slope of the graph of the odor data F1 exceeds a certain value. The start time ts may also be the time when the odor sensor 10 begins to detect an odor. That is, the start time ts may be a time preset on the device side according to design considerations, and may be, for example, the time when the power to the odor sensor 10 is turned on, the time when a shutter (not shown) of a gas flow path is opened to start introducing gas into the odor sensor 10, or the time when a gas introduction pump (not shown) starts operating to start introducing gas into the odor sensor 10.

[0050] The end time te is the time when the odor substance adsorbed on the adsorption film 4 falls off and the amount of adsorption is substantially gone. The end time te may be the time when the value of the frequency f of the odor data F1 stops changing. That is, the end time te may be the time when the absolute value of the frequency f becomes less than a certain value, or the time when the absolute value of the slope of the graph of the odor data F1 becomes less than a certain value. The end time te may also be the time when odor detection by the odor sensor 10 ends. That is, it may be a time preset on the device side according to design considerations, such as the time when the power supply to the odor sensor 10 is turned off, the time when a shutter (not shown) of the gas flow path is closed to terminate the introduction of gas into the odor sensor 10, or the time when a pump (not shown) for introducing gas is stopped to terminate the introduction of gas into the odor sensor 10. The time from the start time ts to the end time te is the gas detection period TW.

[0051] The peak time tp is the time when the amount of odor substance adsorbed to the adsorption film 4 is maximum or locally maximum. That is, in embodiment 1, it is the time when the value of frequency f is minimum or locally minimum. The peak time tp may be the time when the value of frequency f between the start time ts and the end time te is minimum. Furthermore, the peak time tp may be the time when the value of frequency f changes from a decreasing trend to an increasing trend between the start time ts and the end time te, that is, the time when the time differential value of frequency f is approximately 0 (the slope of odor data F1 is approximately 0). The peak frequency fp is the frequency value of odor data F1 at the peak time tp. The difference between the peak frequency fp and the reference frequency f0 is defined as the differential frequency fd.

[0052] Figure 4 also shows the time width HW. The time width HW is the full width at half maximum (FWHM) between the start time ts and the end time te of the odor data F1. The time width HW is the time interval between two intersections W1 and W2 of the odor data F1 and the intermediate frequency fm, which is exactly midway between the reference frequency f0 and the peak frequency fp, i.e., fm = (f0 + fp) / 2.

[0053] 4 also shows the minimum slope (minimum value of the differential value) Kmin and the maximum slope (maximum value of the differential value) Kmax. The minimum slope Kmin is the value when the slope of the odor data F1 is minimum between the start time ts and the peak time tp, i.e., the minimum value of the time differential value of the odor data F1. The maximum slope Kmax is the value when the slope of the odor data F1 is maximum between the peak time tp and the end time te, i.e., the maximum value of the time differential value of the odor data F1.

[0054] As mentioned above, different types of adsorption films 4 are more likely to adsorb different odor substances. Therefore, when detecting odor substances contained in a gas, if multiple odor sensors 10 with different adsorption films 4 are used, each odor sensor 10 will output odor data F1 with a different output waveform. The gas to be detected may contain multiple types of odor substances. In order to identify these odor substances, multiple odor sensors 10 with multiple different adsorption films 4 are used in the gas detection. The multiple odor data F1 output from each odor sensor 10 can be used to determine the amount of multiple odor substances that are each easily adsorbed by each adsorption film 4 contained in the gas.

[0055] The odor data F1 output from the odor sensor 10 is used to identify the type and content of odor substances in the gas. Even if the differential frequency fd of the odor data F1 is used as a representative value of the odor data F1, it is difficult to achieve high accuracy in identifying the corresponding odor substance. The area value S is the integral value of the odor data F1 from the start time ts to the end time te (the value obtained by integrating the difference between the odor data F1 and the reference frequency f0 over the detection period TW). Even if the area value S is used as a representative value of the odor data F1, it is difficult to accurately identify the type and content of odor substances in the gas.

[0056] Therefore, by performing the following calculation process on the odor data F1 using the analysis unit 20, the accuracy of identifying odor substances and detecting their content in the gas is improved.

[0057] <Analysis Program P> The odor data analysis method executed by the analysis program P will be described below with reference to the flowcharts of Figs. 5 to 8. In embodiment 1, the odor data analysis method is executed based on the functions of the analysis program P. The analysis program P causes the analysis unit 20 to cause the odor sensor 10 to detect odors, and the CPU 20a executes arithmetic processing to analyze the odor data. Figs. 5 to 8 are flowcharts of the odor data analysis method when analyzing odor data F1 using different parameters. The odor data analysis method is realized by the CPU 20a, which is the main part of the analysis unit 20, performing arithmetic processing based on the functions of the analysis program P.

[0058] <Type A> FIG. 5 is a flowchart illustrating an odor data analysis method according to Type A. First, the odor sensor 10 is turned on (S.101). The odor sensor 10 begins detection without introducing gas to be detected into the periphery of the adsorption film 4 of the odor sensor 10, and outputs odor data F1 (S.102). In this state, the odor sensor 10 does not detect odorous substances in the gas. For example, a shutter may be provided in the supply flow path that supplies gas to the odor sensor 10, and closing the shutter can achieve a "state in which gas is not introduced into the odor sensor 10." The analysis unit 20 sets the odor data F1 output by the odor sensor 10 in a state in which odorous substances are not substantially detected as the reference frequency f0 (S.103).

[0059] Next, with gas introduced around the adsorption film 4 of the odor sensor 10, the odor sensor 10 detects odor substances during a detection period TW from a start time ts to an end time te, and outputs odor data F1 (S.104). For example, the "state in which gas has been introduced into the odor sensor 10" can be achieved by opening a shutter provided in the gas supply flow path. The method for setting the start time ts and the end time te has already been described.

[0060] The analysis unit 20 calculates an integral value by integrating the difference between the odor data F1 corresponding to the detection period TW and the reference frequency f0 over the detection period TW (S.105). The analysis unit 20 calculates a differential value by time-differentiating the odor data F1 during the detection period TW (S.106). The analysis unit 20 sets the integrated value calculated in (S.105) as the area value S (S.107), and sets the minimum value of the differential values calculated in (S.106) as the minimum slope Kmin (S.108), and sets the maximum value as the maximum slope Kmax (S.109). The analysis unit 20 calculates a representative value R=(S·Kmin) / Kmax (S.110).

[0061] In the above, the representative value R=(S·Kmin) / Kmax is calculated in (S.110), but the representative value R=(S·Kmax) / Kmin may also be calculated. In the first embodiment, for convenience, the representative value calculated by (S·Kmin) / Kmax is denoted as Ra1, and the representative value calculated by (S·Kmax) / Kmin is denoted as Ra2. Ratio=Kmin / Kmax RR(Reciprocal Ratio)=1 / Ratio=Kmax / Kmin given that, Representative value Ra1=S·Ratio Typical value Ra2=S·RR It is possible to express it as follows.

[0062] <Type B> 6 is a flowchart illustrating an odor data analysis method according to Type B. First, the odor sensor 10 is turned on (S.201). Next, the odor sensor 10 begins detection without introducing gas into the odor sensor 10, and outputs odor data F1 (S.202). The analysis unit 20 sets the odor data F1 output by the odor sensor 10 as the reference frequency f0 (S.203). Next, with gas introduced into the odor sensor 10, the odor sensor 10 detects odor substances during the detection period TW, and outputs the detected odor data F1 (S.204). Note that steps (S.201) to (S.204) are similar to steps (S.101) to (S.104), and therefore detailed description thereof will be omitted.

[0063] The analysis unit 20 calculates an integral value by integrating the difference between the odor data F1 corresponding to the detection period TW and the reference frequency f0 over the detection period TW (S.205). The analysis unit 20 calculates the value of the full width at half maximum FWHM during the detection period TW (S.206). The analysis unit 20 sets the integral value calculated in (S.205) as the area value S (S.207), and sets the value of the full width at half maximum FWHM calculated in (S.206) as the time width HW (S.208). The analysis unit 20 calculates a representative value R=S·HW (S.209). Note that in the first embodiment, the representative value calculated using S·HW is denoted as Rb for convenience.

[0064] <Type C> 7 is a flowchart illustrating an odor data analysis method according to Type C. First, the odor sensor 10 is turned on (S.301). Next, the odor sensor 10 begins detection without introducing gas into the odor sensor 10, and outputs odor data F1 (S.302). The analysis unit 20 sets the odor data F1 output by the odor sensor 10 as the reference frequency f0 (S.303). Next, with gas introduced into the odor sensor 10, the odor sensor 10 detects odor substances during the detection period TW, and outputs the detected odor data F1 (S.304). Note that steps (S.301) to (S.304) are similar to steps (S.101) to (S.104), and therefore detailed description thereof will be omitted.

[0065] The analysis unit 20 calculates the difference between the peak frequency fp of the odor data F1 corresponding to the detection period TW and the reference frequency f0 (S.305). The analysis unit 20 calculates a differential value by time-differentiating the odor data F1 during the detection period TW (S.306). The analysis unit 20 sets the difference value calculated in (S.305) as the difference value D (S.307), and sets the minimum value of the differential values calculated in (S.306) as the minimum slope Kmin (S.308), and sets the maximum value as the maximum slope Kmax (S.309). The analysis unit 20 calculates the representative value R=(D·Kmin) / Kmax (S.310).

[0066] In the above, the representative value R = (D·Kmin) / Kmax = D·Ratio is calculated in (S.310), but the representative value R = (D·Kmax) / Kmin = D·RR may also be calculated. In the first embodiment, for convenience, the representative value calculated by (D·Kmin) / Kmax is denoted as Rc1, and the representative value calculated by (D·Kmax) / Kmin is denoted as Rc2.

[0067] <Type D> 8 is a flowchart illustrating an odor data analysis method according to Type D. First, the odor sensor 10 is turned on (S.401). Next, the odor sensor 10 begins detection without introducing gas into the odor sensor 10, and outputs odor data F1 (S.402). The analysis unit 20 sets the odor data F1 output by the odor sensor 10 as the reference frequency f0 (S.403). Next, with gas introduced into the odor sensor 10, the odor sensor 10 detects odor substances during the detection period TW, and outputs the detected odor data F1 (S.404). Note that steps (S.401) to (S.404) are similar to steps (S.101) to (S.104), and therefore detailed description thereof will be omitted.

[0068] The analysis unit 20 calculates the difference between the peak frequency fp of the odor data F1 corresponding to the detection period TW and the reference frequency f0 (S.405). The analysis unit 20 calculates the value of the full width at half maximum FWHM during the detection period TW (S.406). The analysis unit 20 sets the difference value calculated in (S.405) as the difference value D (S.407), and sets the value of the full width at half maximum FWHM calculated in (S.406) as the time width HW (S.408). The analysis unit 20 calculates the representative value R=D·HW (S.409). Note that in the first embodiment, the representative value calculated using D·HW is denoted as Rd for convenience.

[0069] In any of the above types A to D, the analysis unit 20 calculates a representative value R that represents the odor data F1 by performing arithmetic processing on the odor data F1 during the detection period TW. The representative value R is transmitted from the analysis unit 20 to the control unit. The control unit then performs various processes using the representative value R. The representative value R extracts characteristics of the odor data F1. The representative value R varies greatly depending on the type of odor substance in the gas adsorbed by the adsorption film 4. When analyzing or identifying odor substances based on the odor data F1, using the representative value R enables more accurate analysis, identification, and odor discrimination.

[0070] [Embodiment 2] The odor sensor according to the second embodiment will be described below.

[0071] <Configuration of odor sensor> In odor sensors, an adsorption film that adsorbs specific odor substances is formed on the surface of the base. The adsorption film is formed by adding an additive to a film material such as a conductive polymer film.

[0072] A quartz crystal microbalance (QCM) sensor can also be used as the base. Other sensors that can be used include CMOS sensors, surface acoustic wave sensors, field effect transistors (FETs), charge-coupled device sensors, MOS field effect transistors, metal oxide semiconductor sensors, organic conductive polymer sensors, and electrochemical sensors. Depending on the base, the physical quantities that make up the odor data F1 can include frequency, electric potential, mass, and wavelengths of light or sound.

[0073] Examples of the film material that can be used to form the adsorption film include conductive polymers such as polyaniline, polypyrrole, and polythiophene, and inorganic materials such as gold, silver, platinum, chromium, titanium, aluminum, nickel, nickel-based alloys, silicon, carbon, and carbon nanotubes.

[0074] Examples of additives that can be used include inorganic salts, organic salts, organic acids and their salts, and polymeric acids and their salts. The constituent anions of each salt include, for example, inorganic anions such as halide ions (e.g., chloride ion, bromide ion, iodide ion), chlorine oxide ion, sulfate ion, nitrate ion, borate ion, tetrachloroferrate (III) ion, tetrafluoroborate ion, hexafluorophosphate ion, and hexafluoroantimonate ion. Examples of organic acids include aromatic sulfonic acids (e.g., alkyl sulfonic acid, alkyl phosphoric acid, alkyl phosphinic acid, alkyl phosphonic acid, alkyl dithiophosphoric acid, thiocyanic acid, alkyl sulfuric acid, benzenesulfonic acid), and carboxylic acids. Examples of polymeric acids include polymeric acids (e.g., polyacrylic acid, polystyrene sulfonic acid).

[0075] Other organic anions can also be used as additives. Examples of organic anions include bis(perfluoroalkylsulfonyl)imide anions, dicyanamide anions, and tricyanomethanide anions. Examples of constituent cations include inorganic cations such as metal ions of sodium and potassium. Examples of organic cations include ammonium, alkylammonium, alkylphosphonium, alkylimidazolium, alkylpyridinium, and alkylsulfonium.

[0076] Other than the above, various neutral organic molecules can be used as additives, such as liquid crystal molecules having a biphenyl skeleton, and cyclic molecules having molecular recognition functions, such as crown ethers and calixarenes.

[0077] <Odor sensor array> The odor sensor can be used by arranging multiple adsorption membranes on the surface of one or multiple bases. In this case, for example, multiple adsorption membranes with unique adsorption properties for different odor substances can be arranged in a row. Also, multiple adsorption membranes can be aligned in a plane, with multiple membranes arranged vertically and horizontally.

[0078] By using information about the order in which the adsorption films have been arranged and which have which adsorption properties as an encryption key or passcode, security can be enhanced in various situations. This odor sensor or the entire system including it can be used as a security system that utilizes odors.

[0079] <Odor database confidentiality processing> 9 is a schematic diagram of an odor sensor unit 210 according to a second embodiment. The odor sensor unit 210 has five odor sensors 210a-210e. The odor sensors 210a-210e use, for example, a quartz crystal microbalance (QCM) sensor as the base 202. In the second embodiment, the five odor sensors 210a-210e are arranged in a row. Adsorption films 204a-204e are formed on the surfaces of the five bases 202, respectively, and the adsorption films 204a-204e correspond to the odor sensors 210a-210e, respectively. The adsorption films 204a-204e are formed by adding additives 206a-206e to a conductive polymer film 205, respectively. Due to the differences in the properties of the additives 206a-206e, the adsorption films 204a-204e exhibit adsorption properties that allow them to adsorb different odor substances.

[0080] Assume that this odor sensor unit 210 detects the odors of three types of gases Ga, Gb, and Gc, for example, and stores them in database DB1. The detection results when the gases Ga, Gb, and Gc are detected by odor sensors 210a to 210e are, for example, as follows. The values in parentheses are the output values of odor sensors 210a to 210e, respectively. Gas Ga: (0,5,10,5,0) Gas Gb: (2, 4, 6, 8, 10) Gas Gc: (10,8,6,4,2) If these output values were stored as is in the odor database DB, then if the information in the odor database DB were to be stolen, the detection results of the odor sensors 210a-210e for the gases Ga-Gc would easily be revealed to the pirate. However, for example, the arrangement order of the output values of the five odor sensors 210a-210e could be changed, and the output values from the odor sensors 210a-210e stored in the changed arrangement order in the odor database DB. If the information on this changed order is then managed separately from the odor database DB as an encryption key, then even if the information in the database DB is stolen, the pirate will not be able to easily ascertain the detection results of the odor sensors 210a-210e for the gases Ga-Gc.

[0081] For example, if the output values of the five odor sensors 210a to 210e are arranged in the order (1, 3, 5, 2, 4), the detection results of the gases Ga to Gc stored in the odor database DB will be as follows: Gas Ga: (0,10,0,5,5) Gas Gb: (2,6,10,4,8) Gas Gc: (10,6,2,8,4) Without the encryption key, the detection results of gases Ga to Gc by the odor sensors 210a to 210e cannot be reproduced in the correct order of the sensors. Here, by using the encryption key (1, 3, 5, 2, 4), the detection results of gases Ga to Gc in the odor database DB can be decrypted in the correct order of the odor sensors 210a to 210e. This measure improves the security of the odor data stored in the odor database DB.

[0082] Furthermore, for example, the order of the sensors in an odor sensor unit for detecting odor data to be stored in the odor database DB can be changed from the order of the sensors in an odor sensor unit sold to users, and the change can be used as an encryption key. Furthermore, when producing multiple odor sensor units, changing the sensor arrangement in each unit or for each batch and managing the change as an encryption key can further contribute to improving the confidentiality of odor data.

[0083] <Access control using scent> By using the odor sensor unit 210 shown in FIG. 9, it is possible to realize, for example, room entry / exit management using odors. Locking and unlocking of rooms is performed using gases with specific odors. Here, the odor used for room entry / exit is referred to as an "odor key." The odor key may be, for example, a specific perfume or an individual's body odor. By linking the odor sensor unit 210 to an entry / exit control system that controls the locking and unlocking of room doors, it is possible to unlock the door using the odor key.

[0084] Here, for example, a configuration can be made in which the door cannot be unlocked with just the smell key, but can only be unlocked by inputting the sensor array information in the smell sensor unit 210 as a password. For example, the detection result that can unlock the door is (2, 4, 6, 8, 10), and this information is stored in a database or the like in the access control system or in the cloud. If the detection result of the smell key by the smell sensor unit 210 is (2, 6, 10, 4, 8), the door cannot be unlocked. However, when the sensor array information (1, 3, 5, 2, 4) in the smell sensor unit 210 is input, the detection result of (2, 6, 10, 4, 8) is converted to (2, 4, 6, 8, 10). The converted detection result is compared with the detection result stored in the database or the like, and if they match, the door can be unlocked.

[0085] <Industrial Applicability> Furthermore, by using the odor sensor described in the above embodiment and the method for analyzing odor data detected by the odor sensor, it is possible to quickly and accurately identify the odor substance contained in a gas containing multiple different odor substances. The load on the processing device can also be reduced. Even when distinguishing the odor of a specific gas from that of other gases, rapid and accurate discrimination is possible. Furthermore, when identifying odor substances contained in a detected gas by comparing the detected odor data with odor data stored in a database, etc., rapid and accurate matching is possible.

[0086] [Example 1] FIG. 10AB shows the evaluation results of Example 1. In Example 1, five odor sensors Q1 to Q5 were used to detect the odors of multiple gases and output odor data F1. Gas G1 was acetic acid, gas G2 was air, and gas G3 was ammonia. Each of the odor sensors Q1 to Q5 shared the same base 2, but the adsorption film 4 contained different additives 6, and therefore each had unique adsorption characteristics for different odor substances. The odors of gases G1 to G3 were detected by odor sensors Q1 to Q5 according to the procedures (S.101) to (S.104) of Type A in Embodiment 1.

[0087] 10A shows, in a pentagonal chart and bar graph, the differential frequency fd, which is the difference between the reference frequency f0 and the peak frequency fp in the odor data F1 of gases G1 to G3, for each of odor sensors Q1 to Q5. FIG. 10B shows, in a pentagonal chart and bar graph, the results of calculating the ratio (= Kmin / Kmax), RR (= Kmax / Kmin), minimum slope Kmin, maximum slope Kmax, and full width at half maximum FWHM (= time width HW) for each of odor sensors Q1 to Q5 based on the odor data F1 of gases G1 to G3.

[0088] Figure 10AB shows that the differences in the detection results for each of gases G1 to G3 are more clearly seen when expressed using the calculation results, particularly the Ratio, RR, and FWHM, as in Figure 10B, rather than using the differential frequency fd as in Figure 10A. In other words, the differences in odors due to the odor substances contained in each gas are more clearly seen when expressed using the Ratio, RR, and FWHM. It can be seen that using these calculated values enables more accurate odor discrimination.

[0089] [Example 2] FIG. 11AB shows the evaluation results of Example 2. In Example 2, five odor sensors Q6 to Q10 were used to detect the odors of multiple gases and output odor data F1. The multiple gases were acetic acid G1, air G2, and ammonia G3. The odor sensors Q6 to Q10 each share the same base 2, but the adsorption films 4 contain different additives 6, and therefore each has unique adsorption characteristics for different odor substances. The odors of gases G1 to G3 were detected by the odor sensors Q6 to Q10 based on the procedures (S.101) to (S.104) of Type A in Embodiment 1. Note that the odor sensors Q6 to Q10 used in Example 2 have different adsorption films 4 than the odor sensors Q1 to Q5 used in Example 1.

[0090] FIG. 11A shows, in a pentagonal chart, the results of calculating the area value S, Ratio (=Kmin / Kmax), RR, and full width at half maximum FWHM based on the odor data F1 of gases G1 to G3. FIG. 11B shows, in a pentagonal chart, the results (representative values) of analyzing the odor data F1 of gases G1 to G3 based on the analysis method of the present invention for each of odor sensors Q6 to Q10. FIG. 11B shows analysis results A to C. Analysis result A is a plot of the area value S vs. the Ratio (representative value Ra1) (Type A). Analysis result B is a plot of the area value S vs. the RR (representative value Ra2) (Type A). Analysis result C is a plot of the area value S vs. the full width at half maximum FWHM (representative value Rb) (Type B).

[0091] Figure 11AB shows that the differences in the detection results for each of gases G1 to G3 are more clearly seen when expressed using the representative values of analysis results A to C than when expressed using the area value S. In other words, the differences in odors due to the odor substances contained in each gas are more clearly seen when expressed using the representative values Ra1, Ra2, and Rb. It can be seen that using the representative values Ra1, Ra2, and Rb enables more accurate odor discrimination.

[0092] [Example 3] FIG. 12AB shows the evaluation results of Example 3. In Example 3, 35 odor sensors 10 were used to detect the odors of five types of spices A to D and output odor data F1. Spices A to D are black peppers, with spices A and C from a first region of origin, spice B from a second region of origin, and spice D a mixture of spices from the first and second regions of origin. Each of the 32 odor sensors 10 shares the same base 2, but the adsorption films 4 contain different additives 6, and therefore each has unique adsorption properties for different odor substances. Detection of the odors of spices A to D using the odor sensors 10 was performed based on the procedures (S.101) to (S.104) of Type A in Embodiment 1.

[0093] 12A shows the results of calculating the area value S for each of the 35 odor sensors 10 based on the odor data F1 for each of the spices A to D in the form of a circular (more precisely, a 35-sided) chart. FIG. 12B shows the area value S·full width at half maximum FWHM (representative value Rb) as the result (representative value) of analyzing the odor data F1 for each of the spices A to D based on the analysis method of the present invention in the form of a circular (more precisely, a 35-sided) chart for each of the 35 odor sensors 10. The numbers around the periphery of the chart in FIG. 12AB are the serial numbers of the 35 odor sensors 10.

[0094] Figure 12AB shows that the differences in the detection results for each of the spices A to D are more apparent when expressed using the representative value Rb = S · FWHM than when expressed using the area value S. In other words, the differences in odors due to the odor substances contained in each of the spices A to D are more apparent when expressed using the representative value Rb. This shows that using the representative value Rb enables more accurate odor discrimination.

[0095] [Example 4] 13 is a diagram showing the evaluation results of Example 4. In Example 4, a similar evaluation was performed using the same spices A to D as in Example 3, but the number of odor sensors 10 was 20 in Example 4, compared to 35 in Example 3. 20 sensors 10 in which the contribution rate of the full width at half maximum (FWHM) was high in Example 3, i.e., the representative value Rb better represented the characteristics of the spice odor compared to the area value S, were selected, and Example 4 was evaluated.

[0096] Here, the contribution rate corresponds to the value obtained by dividing the eigenvalue of each principal component by the sum when principal component analysis is performed on the frequency change values of the detection results using 35 films. The full width at half maximum (FWHM) is not directly related to the value of the difference frequency (fd). However, since the full width at half maximum (FWHM) tends to increase as the difference frequency (fd) increases, in the calculation of the principal component analysis, the contribution rate tends to increase as the value of the full width at half maximum (FWHM) increases. Note that other detection targets, detection procedures, etc. are the same as those in Example 3, and therefore description thereof will be omitted.

[0097] FIG. 13 shows, in an icosagonal chart, the area value S·full width at half maximum FWHM (representative value Rb) values for each of the 20 odor sensors 10 as the analysis results (representative values) of the odor data F1 for each of the spices A to D based on the analysis method of the present invention. FIG. 13 shows that the differences in the detection results for each of the spices A to D become clear even when detected using the 20 odor sensors 10 by expressing the representative value Rb as S·full width at half maximum FWHM. It can be seen that using the representative value Rb enables more accurate odor discrimination. The numbers around the chart in FIG. 13 are the serial numbers of the 20 odor sensors 10 selected from the 35 used in Example 3.

[0098] [Example 5] 14 is a diagram showing the evaluation results of Example 5. In Example 5, a similar evaluation was performed using the same spices A to D as in Example 3, but the number of odor sensors 10 was 10 in Example 5, compared to 35 in Example 3. Ten sensors 10 in Example 3 with a high contribution rate due to the full width at half maximum (FWHM), i.e., with a representative value Rb that better represents the characteristics of the spice odor compared to the area value S, were selected, and evaluation of Example 5 was performed. Note that other detection targets, detection procedures, etc. are the same as in Example 3, and therefore description thereof will be omitted.

[0099] FIG. 14 shows, in a decagonal chart, the area value S·full width at half maximum FWHM (representative value Rb) values for each of the ten odor sensors 10 as the analysis results (representative values) of the odor data F1 for each of the spices A to D based on the analysis method of the present invention. FIG. 14 shows that the differences in the detection results for each of the spices A to D become clear even when detected using the ten odor sensors 10 by expressing the representative value Rb as S·full width at half maximum FWHM. It can be seen that using the representative value Rb enables more accurate odor discrimination. The numbers around the chart in FIG. 14 are the serial numbers of the ten odor sensors 10 selected from the 35 used in Example 3.

[0100] Although the preferred embodiments of the present invention have been described above, the present invention is not limited to these and various modifications and changes are possible within the scope of the gist of the present invention. For example, the present invention includes the following aims.

[0101] [Objective 1] An odor data analysis device having an odor sensor and an analysis unit, The odor sensor has an adsorption film that adsorbs an odor substance, detects the odor substance by the odor substance being adsorbed by the adsorption film, and converts the amount of the odor substance adsorbed into a predetermined physical quantity to output odor data that is time-series data. the analysis unit analyzes the odor data output from the odor sensor, (1) The analysis unit sets the odor data output by the odor sensor in a state where the odor substance is not substantially detected as reference data, (2) the odor sensor detects the odor substance during a detection period from a detection start time to a detection end time, and outputs the odor data; (3) The analysis unit calculates an integral value obtained by integrating the difference between the odor data corresponding to the detection period and the reference data over the detection period; (4) The analysis unit calculates a differential value obtained by time-differentiating the odor data during the detection period; (5) When the integral value in (3) is S, the minimum value of the differential value in (4) is Kmin, and the maximum value of the differential value in (4) is Kmax, The odor data analysis device, wherein the analysis unit calculates a representative value R=(S·Kmin) / Kmax or a representative value R=(S·Kmax) / Kmin.

[0102] [Objective 2] An odor data analysis device having an odor sensor and an analysis unit, The odor sensor has an adsorption film that adsorbs an odor substance, detects the odor substance by the odor substance being adsorbed by the adsorption film, and converts the amount of the odor substance adsorbed into a predetermined physical quantity to output odor data that is time-series data. The analysis unit detects the odor from the odor sensor. The output odor data is analyzed, (1) The analysis unit sets the odor data output by the odor sensor in a state where the odor substance is not substantially detected as reference data, (2) the odor sensor detects the odor substance during a detection period from a detection start time to a detection end time, and outputs the odor data; (3) The analysis unit calculates an integral value obtained by integrating the difference between the odor data corresponding to the detection period and the reference data over the detection period; (6) The analysis unit calculates a value of a half width during the detection period, (7) When the integral value in (3) is S and the half width value in (6) is HW, The odor data analysis device, wherein the analysis unit calculates a representative value R=S·HW.

[0103] [Objective 3] An odor data analysis device having an odor sensor and an analysis unit, The odor sensor has an adsorption film that adsorbs an odor substance, detects the odor substance by the odor substance being adsorbed by the adsorption film, and converts the amount of the odor substance adsorbed into a predetermined physical quantity to output odor data that is time-series data. the analysis unit analyzes the odor data output from the odor sensor, (1) The analysis unit sets the odor data output by the odor sensor in a state where the odor substance is not substantially detected as reference data, (2) the odor sensor detects the odor substance during a detection period from a detection start time to a detection end time, and outputs the odor data; (8) The analysis unit calculates a difference value between a detected peak value of the odor data corresponding to the detection period and the reference data, (4) The analysis unit calculates a differential value obtained by time-differentiating the odor data during the detection period; (9) When the difference value in (8) is D, the minimum value of the differential value in (4) is Kmin, and the maximum value of the differential value in (4) is Kmax, The odor data analysis device, wherein the analysis unit calculates a representative value R=(D·Kmin) / Kmax or a representative value R=(D·Kmax) / Kmin.

[0104] [Objective 4] An odor data analysis device having an odor sensor and an analysis unit, The odor sensor has an adsorption film that adsorbs an odor substance, detects the odor substance by the odor substance being adsorbed by the adsorption film, and converts the amount of the odor substance adsorbed into a predetermined physical quantity to output odor data that is time-series data. the analysis unit analyzes the odor data output from the odor sensor, (1) The analysis unit sets the odor data output by the odor sensor in a state where the odor substance is not substantially detected as reference data, (2) the odor sensor detects the odor substance during a detection period from a detection start time to a detection end time, and outputs the odor data; (8) The analysis unit calculates a difference value between a detected peak value of the odor data corresponding to the detection period and the reference data, (6) The analysis unit calculates a value of a half width during the detection period, (10) When the difference value in (8) is D and the half width value in (6) is HW, The odor data analysis device, wherein the analysis unit calculates a representative value R=D·HW.

[0105] [Objective 5] The predetermined physical quantity may be a frequency or an amount of charge.

[0106] [Objective 6] The odor sensor may be a plurality of sensors, and the plurality of adsorption membranes of the plurality of odor sensors may each be capable of interacting with a different odor substance.

[0107] [Objective 7] the adsorption film contains a conductive polymer and a dopant that changes the material properties of the conductive polymer; The content or type of the dopant may be different among the plurality of odor sensors.

[0108] [Objective 8] The plurality of odor sensors may be arranged one-dimensionally or two-dimensionally within a predetermined plane, and the arrangement of the plurality of odor sensors may be changeable.

[0109] [Objective 9] An odor data analysis method for analyzing odor data, which is time-series data output from an odor sensor, by an analysis unit, comprising: The odor sensor has an adsorption film that adsorbs an odor substance, detects the odor substance by the odor substance being adsorbed by the adsorption film, and converts the amount of the odor substance adsorbed into a predetermined physical quantity to output odor data that is time-series data. the analysis unit analyzes the odor data output from the odor sensor, (1) the analysis unit sets the odor data output by the odor sensor in a state where the odor substance is not substantially detected as reference data; (2) the odor sensor detects the odor substance during a detection period from a detection start time to a detection end time, and outputs the odor data; (3) a step in which the analysis unit calculates an integral value obtained by integrating a difference between the odor data corresponding to the detection period and the reference data over the detection period; (4) the analysis unit calculates a differential value obtained by time-differentiating the odor data during the detection period; (5) When the integral value in (3) is S, the minimum value of the differential value in (4) is Kmin, and the maximum value of the differential value in (4) is Kmax, The odor data analysis method includes a step in which the analysis unit calculates a representative value R=(S·Kmin) / Kmax or a representative value R=(S·Kmax) / Kmin.

[0110] [Objective 10] An odor data analysis method for analyzing odor data, which is time-series data output from an odor sensor, by an analysis unit, comprising: The odor sensor has an adsorption film that adsorbs an odor substance, detects the odor substance by the odor substance being adsorbed by the adsorption film, and converts the amount of the odor substance adsorbed into a predetermined physical quantity to output odor data that is time-series data. the analysis unit analyzes the odor data output from the odor sensor, (1) the analysis unit sets the odor data output by the odor sensor in a state where the odor substance is not substantially detected as reference data; (2) the odor sensor detects the odor substance during a detection period from a detection start time to a detection end time, and outputs the odor data; (3) a step in which the analysis unit calculates an integral value obtained by integrating a difference between the odor data corresponding to the detection period and the reference data over the detection period; (6) the analysis unit calculates a value of the half width during the detection period; (7) When the integral value in (3) is S and the half width value in (7) is HW, The odor data analysis method includes a step in which the analysis unit calculates a representative value R=S·HW.

[0111] [Objective 11] An odor data analysis method for analyzing odor data, which is time-series data output from an odor sensor, by an analysis unit, comprising: The odor sensor has an adsorption film that adsorbs an odor substance, detects the odor substance by the odor substance being adsorbed by the adsorption film, and converts the amount of the odor substance adsorbed into a predetermined physical quantity to output odor data that is time-series data. the analysis unit analyzes the odor data output from the odor sensor, (1) the analysis unit sets the odor data output by the odor sensor in a state where the odor substance is not substantially detected as reference data; (2) the odor sensor detects the odor substance during a detection period from a detection start time to a detection end time, and outputs the odor data; (8) a step in which the analysis unit calculates a difference value between a detected peak value of the odor data corresponding to the detection period and the reference data; (4) the analysis unit calculates a differential value obtained by time-differentiating the odor data during the detection period; (9) When the difference value in (8) is D, the minimum value of the differential value in (4) is Kmin, and the maximum value of the differential value in (4) is Kmax, The odor data analysis method includes a step in which the analysis unit calculates a representative value R=(D·Kmin) / Kmax or a representative value R=(D·Kmax) / Kmin.

[0112] [Objective 12] An odor data analysis method for analyzing odor data, which is time-series data output from an odor sensor, by an analysis unit, comprising: The odor sensor has an adsorption film that adsorbs an odor substance, detects the odor substance by the odor substance being adsorbed by the adsorption film, and converts the amount of the odor substance adsorbed into a predetermined physical quantity to output odor data that is time-series data. the analysis unit analyzes the odor data output from the odor sensor, (1) the analysis unit sets the odor data output by the odor sensor in a state where the odor substance is not substantially detected as reference data; (2) the odor sensor detects the odor substance during a detection period from a detection start time to a detection end time, and outputs the odor data; (8) a step in which the analysis unit calculates a difference value between a detected peak value of the odor data corresponding to the detection period and the reference data; (6) the analysis unit calculates a value of the half width during the detection period; (10) When the difference value in (8) is D and the half width value in (6) is HW, The odor data analysis method includes a step in which the analysis unit calculates a representative value R=D·HW.

[0113] [Objective 13] An odor data analysis program for analyzing odor data, which is time-series data output from an odor sensor, The odor sensor has an adsorption film that adsorbs an odor substance, detects the odor substance by the odor substance being adsorbed by the adsorption film, and converts the amount of the odor substance adsorbed into a predetermined physical quantity to output odor data that is time-series data. The odor data analysis program is installed on a computer. (1) setting the odor data output by the odor sensor in a state where the odor substance is not substantially detected as reference data; (2) causing the odor sensor to detect the odor substance during a detection period from a detection start time to a detection end time and outputting the odor data; (3) calculating an integral value obtained by integrating the difference between the odor data corresponding to the detection period and the reference data over the detection period; (4) calculating a differential value obtained by time-differentiating the odor data during the detection period; (5) When the integral value in (3) is S, the minimum value of the differential value in (4) is Kmin, and the maximum value of the differential value in (4) is Kmax, and calculating a representative value R=(S·Kmin) / Kmax or a representative value R=(S·Kmax) / Kmin.

[0114] [Objective 14] An odor data analysis program for analyzing odor data, which is time-series data output from an odor sensor, by an analysis unit, The odor sensor has an adsorption film that adsorbs an odor substance, detects the odor substance by the odor substance being adsorbed by the adsorption film, and converts the amount of the odor substance adsorbed into a predetermined physical quantity to output odor data that is time-series data. The odor data analysis program is installed on a computer. (1) setting the odor data output by the odor sensor in a state where the odor substance is not substantially detected as reference data; (2) causing the odor sensor to detect the odor substance during a detection period from a detection start time to a detection end time and outputting the odor data; (3) calculating an integral value obtained by integrating the difference between the odor data corresponding to the detection period and the reference data over the detection period; (6) calculating a half-width value during the detection period; (7) When the integral value in (3) is S and the half width value in (7) is HW, and a step of calculating a representative value R=S·HW.

[0115] [Objective 15] An odor data analysis program for analyzing odor data, which is time-series data output from an odor sensor, by an analysis unit, The odor sensor has an adsorption film that adsorbs an odor substance, detects the odor substance by the odor substance being adsorbed by the adsorption film, and converts the amount of the odor substance adsorbed into a predetermined physical quantity to output odor data that is time-series data. The odor data analysis program is installed on a computer. (1) setting the odor data output by the odor sensor in a state where the odor substance is not substantially detected as reference data; (2) causing the odor sensor to detect the odor substance during a detection period from a detection start time to a detection end time and outputting the odor data; (8) calculating a difference value between the detected peak value of the odor data corresponding to the detection period and the reference data; (4) calculating a differential value obtained by time-differentiating the odor data during the detection period; (9) When the difference value in (8) is D, the minimum value of the differential value in (4) is Kmin, and the maximum value of the differential value in (4) is Kmax, and calculating a representative value R=(D·Kmin) / Kmax or a representative value R=(D·Kmax) / Kmin.

[0116] [Objective 16] An odor data analysis program for analyzing odor data, which is time-series data output from an odor sensor, by an analysis unit, The odor sensor has an adsorption film that adsorbs an odor substance, detects the odor substance by the odor substance being adsorbed by the adsorption film, and converts the amount of the odor substance adsorbed into a predetermined physical quantity to output odor data that is time-series data. The odor data analysis program is installed on a computer. (1) setting the odor data output by the odor sensor in a state where the odor substance is not substantially detected as reference data; (2) detecting the odor substance during a detection period from a detection start time to a detection end time, and outputting the odor data; (8) calculating a difference value between the detected peak value of the odor data corresponding to the detection period and the reference data; (6) calculating a half-width value during the detection period; (10) When the difference value in (8) is D and the half width value in (6) is HW, and a step of calculating the representative value R=D·HW. [Explanation of symbols]

[0117] D: Difference value DB: Odor database f: frequency f0: Reference frequency (reference data) fd: difference frequency fm: intermediate frequency fp: Peak frequency (detected peak value) F1: Odor data (time series data of physical quantities) G1~G3: Gas HW: Time width (half width) Kmin: Minimum slope (minimum differential value) Kmax: Maximum gradient (maximum differential value) P: Analysis program (Odor data analysis program) Q1 to Q10: Odor sensors R, Ra1, Ra2: Representative values (calculated data) S: Area value (integral value) S1: Odor data analysis device t: time tp: Peak time te: End time (detection end time) ts: Start time (detection start time) TW: detection period W1, W2: Intersection 2, 202: Base 20a: CPU (Central Processing Unit) 20b: Memory (storage device) 20c: Input / output port 4, 4a~4c, 204a~204e: Adsorption film 5, 205: Conductive polymer film 6, 6a-6c, 206a-206e: Additives 10, 210: Odor sensor 20:Analysis Department

Claims

1. An odor data analysis device having an odor sensor and an analysis unit, The odor sensor has an adsorption film that adsorbs an odor substance, detects the odor substance by the odor substance being adsorbed by the adsorption film, and converts the amount of the odor substance adsorbed into a predetermined physical quantity to output odor data that is time-series data. the analysis unit analyzes the odor data output from the odor sensor, (1) The analysis unit sets the odor data output by the odor sensor in a state where the odor substance is not substantially detected as reference data, (2) the odor sensor detects the odor substance during a detection period from a detection start time to a detection end time and outputs the odor data; (3) The analysis unit calculates an integral value obtained by integrating the difference between the odor data corresponding to the detection period and the reference data over the detection period; (4) The analysis unit calculates a differential value obtained by time-differentiating the odor data during the detection period; (5) When the integral value in (3) is S, the minimum value of the differential value in (4) is Kmin, and the maximum value of the differential value in (4) is Kmax, The odor data analysis device, wherein the analysis unit calculates the representative value R=(S·Kmin) / Kmax or the representative value R=(S·Kmax) / Kmin.

2. An odor data analysis device having an odor sensor and an analysis unit, The odor sensor has an adsorption film that adsorbs an odor substance, detects the odor substance by the odor substance being adsorbed by the adsorption film, and converts the amount of the odor substance adsorbed into a predetermined physical quantity to output odor data that is time-series data. The analysis unit detects the odor from the odor sensor. The output odor data is analyzed, (1) The analysis unit sets the odor data output by the odor sensor in a state where the odor substance is not substantially detected as reference data, (2) the odor sensor detects the odor substance during a detection period from a detection start time to a detection end time and outputs the odor data; (3) The analysis unit calculates an integral value obtained by integrating the difference between the odor data corresponding to the detection period and the reference data over the detection period; (6) The analysis unit calculates a value of a half width during the detection period, (7) When the integral value in (3) is S and the half width value in (6) is HW, The odor data analysis device, wherein the analysis unit calculates a representative value R=S·HW.

3. An odor data analysis device having an odor sensor and an analysis unit, The odor sensor has an adsorption film that adsorbs an odor substance, detects the odor substance by the odor substance being adsorbed by the adsorption film, and converts the amount of the odor substance adsorbed into a predetermined physical quantity to output odor data that is time-series data. the analysis unit analyzes the odor data output from the odor sensor, (1) The analysis unit sets the odor data output by the odor sensor in a state where the odor substance is not substantially detected as reference data, (2) the odor sensor detects the odor substance during a detection period from a detection start time to a detection end time and outputs the odor data; (8) The analysis unit calculates a difference value between a detected peak value of the odor data corresponding to the detection period and the reference data, (4) The analysis unit calculates a differential value obtained by time-differentiating the odor data during the detection period; (9) When the difference value in (8) is D, the minimum value of the differential value in (4) is Kmin, and the maximum value of the differential value in (4) is Kmax, The odor data analysis device, wherein the analysis unit calculates the representative value R=(D·Kmin) / Kmax or the representative value R=(D·Kmax) / Kmin.

4. An odor data analysis device having an odor sensor and an analysis unit, The odor sensor has an adsorption film that adsorbs an odor substance, detects the odor substance by the odor substance being adsorbed by the adsorption film, and converts the amount of the odor substance adsorbed into a predetermined physical quantity to output odor data that is time-series data. the analysis unit analyzes the odor data output from the odor sensor, (1) The analysis unit sets the odor data output by the odor sensor in a state where the odor substance is not substantially detected as reference data, (2) the odor sensor detects the odor substance during a detection period from a detection start time to a detection end time and outputs the odor data; (8) The analysis unit calculates a difference value between a detected peak value of the odor data corresponding to the detection period and the reference data, (6) The analysis unit calculates a value of a half width during the detection period, (10) When the difference value in (8) is D and the half width value in (6) is HW, The odor data analysis device, wherein the analysis unit calculates a representative value R=D·HW.

5. The odor data analysis device according to claim 1 , wherein the predetermined physical quantity is a frequency or an amount of electric charge.

6. An odor data analysis device according to any one of claims 1 to 4, wherein there are a plurality of odor sensors, and the plurality of adsorption membranes possessed by the plurality of odor sensors are each capable of interacting with a different odor substance.

7. the adsorption film contains a conductive polymer and a dopant that changes the material properties of the conductive polymer; The odor data analyzer according to claim 6 , wherein the content or type of the dopant differs among the plurality of odor sensors.

8. 7. The odor data analyzing device according to claim 6, wherein the plurality of odor sensors are arranged one-dimensionally or two-dimensionally within a predetermined plane, and the arrangement of the plurality of odor sensors is changeable.

9. An odor data analysis method for analyzing odor data, which is time-series data output from an odor sensor, by an analysis unit, comprising: The odor sensor has an adsorption film that adsorbs an odor substance, detects the odor substance by the odor substance being adsorbed by the adsorption film, and converts the amount of the odor substance adsorbed into a predetermined physical quantity to output odor data that is time-series data. the analysis unit analyzes the odor data output from the odor sensor, (1) the analysis unit sets the odor data output by the odor sensor in a state where the odor substance is not substantially detected as reference data; (2) a step in which the odor sensor detects the odor substance during a detection period from a detection start time to a detection end time and outputs the odor data; (3) a step in which the analysis unit calculates an integral value obtained by integrating a difference between the odor data corresponding to the detection period and the reference data over the detection period; (4) the analysis unit calculates a differential value obtained by time-differentiating the odor data during the detection period; (5) When the integral value in (3) is S, the minimum value of the differential value in (4) is Kmin, and the maximum value of the differential value in (4) is Kmax, The odor data analysis method includes a step in which the analysis unit calculates a representative value R=(S·Kmin) / Kmax or a representative value R=(S·Kmax) / Kmin.

10. An odor data analysis method for analyzing odor data, which is time-series data output from an odor sensor, by an analysis unit, comprising: The odor sensor has an adsorption film that adsorbs an odor substance, detects the odor substance by the odor substance being adsorbed by the adsorption film, and converts the amount of the odor substance adsorbed into a predetermined physical quantity to output odor data that is time-series data. the analysis unit analyzes the odor data output from the odor sensor, (1) the analysis unit sets the odor data output by the odor sensor in a state where the odor substance is not substantially detected as reference data; (2) a step in which the odor sensor detects the odor substance during a detection period from a detection start time to a detection end time and outputs the odor data; (3) a step in which the analysis unit calculates an integral value obtained by integrating a difference between the odor data corresponding to the detection period and the reference data over the detection period; (6) the analysis unit calculates a value of a half width during the detection period; (7) When the integral value in (3) is S and the half width value in (7) is HW, The odor data analysis method includes a step in which the analysis unit calculates a representative value R=S·HW.

11. An odor data analysis method for analyzing odor data, which is time-series data output from an odor sensor, by an analysis unit, comprising: The odor sensor has an adsorption film that adsorbs an odor substance, detects the odor substance by the odor substance being adsorbed by the adsorption film, and converts the amount of the odor substance adsorbed into a predetermined physical quantity to output odor data that is time-series data. the analysis unit analyzes the odor data output from the odor sensor, (1) the analysis unit sets the odor data output by the odor sensor in a state where the odor substance is not substantially detected as reference data; (2) a step in which the odor sensor detects the odor substance during a detection period from a detection start time to a detection end time and outputs the odor data; (8) A step in which the analysis unit calculates a difference value between a detected peak value of the odor data corresponding to the detection period and the reference data; (4) the analysis unit calculates a differential value obtained by time-differentiating the odor data during the detection period; (9) When the difference value in (8) is D, the minimum value of the differential value in (4) is Kmin, and the maximum value of the differential value in (4) is Kmax, The odor data analysis method includes a step in which the analysis unit calculates a representative value R=(D·Kmin) / Kmax or a representative value R=(D·Kmax) / Kmin.

12. An odor data analysis method for analyzing odor data, which is time-series data output from an odor sensor, by an analysis unit, comprising: The odor sensor has an adsorption film that adsorbs an odor substance, detects the odor substance by the odor substance being adsorbed by the adsorption film, and converts the amount of the odor substance adsorbed into a predetermined physical quantity to output odor data that is time-series data. the analysis unit analyzes the odor data output from the odor sensor, (1) the analysis unit sets the odor data output by the odor sensor in a state where the odor substance is not substantially detected as reference data; (2) a step in which the odor sensor detects the odor substance during a detection period from a detection start time to a detection end time and outputs the odor data; (8) A step in which the analysis unit calculates a difference value between a detected peak value of the odor data corresponding to the detection period and the reference data; (6) the analysis unit calculates a value of a half width during the detection period; (10) When the difference value in (8) is D and the half width value in (6) is HW, The odor data analysis method includes a step in which the analysis unit calculates a representative value R=D·HW.

13. An odor data analysis program for analyzing odor data, which is time-series data output from an odor sensor, The odor sensor has an adsorption film that adsorbs an odor substance, detects the odor substance by the odor substance being adsorbed by the adsorption film, and converts the amount of the odor substance adsorbed into a predetermined physical quantity to output odor data that is time-series data. The odor data analysis program is installed on a computer. (1) setting the odor data output by the odor sensor in a state where the odor substance is not substantially detected as reference data; (2) causing the odor sensor to detect the odor substance during a detection period from a detection start time to a detection end time and output the odor data; (3) calculating an integral value obtained by integrating the difference between the odor data corresponding to the detection period and the reference data over the detection period; (4) calculating a differential value obtained by time-differentiating the odor data during the detection period; (5) When the integral value in (3) is S, the minimum value of the differential value in (4) is Kmin, and the maximum value of the differential value in (4) is Kmax, and calculating a representative value R=(S·Kmin) / Kmax or a representative value R=(S·Kmax) / Kmin.

14. An odor data analysis program for analyzing odor data, which is time-series data output from an odor sensor, by an analysis unit, The odor sensor has an adsorption film that adsorbs an odor substance, detects the odor substance by the odor substance being adsorbed by the adsorption film, and converts the amount of the odor substance adsorbed into a predetermined physical quantity to output odor data that is time-series data. The odor data analysis program is installed on a computer. (1) setting the odor data output by the odor sensor in a state where the odor substance is not substantially detected as reference data; (2) causing the odor sensor to detect the odor substance during a detection period from a detection start time to a detection end time and output the odor data; (3) calculating an integral value obtained by integrating the difference between the odor data corresponding to the detection period and the reference data over the detection period; (6) calculating a half-width value during the detection period; (7) When the integral value in (3) is S and the half width value in (7) is HW, and calculating a representative value R=S·HW.

15. An odor data analysis program for analyzing odor data, which is time-series data output from an odor sensor, by an analysis unit, The odor sensor has an adsorption film that adsorbs an odor substance, detects the odor substance by the odor substance being adsorbed by the adsorption film, and converts the amount of the odor substance adsorbed into a predetermined physical quantity to output odor data that is time-series data. The odor data analysis program is installed on a computer. (1) setting the odor data output by the odor sensor in a state where the odor substance is not substantially detected as reference data; (2) causing the odor sensor to detect the odor substance during a detection period from a detection start time to a detection end time and output the odor data; (8) calculating a difference value between a detected peak value of the odor data corresponding to the detection period and the reference data; (4) calculating a differential value obtained by time-differentiating the odor data during the detection period; (9) When the difference value in (8) is D, the minimum value of the differential value in (4) is Kmin, and the maximum value of the differential value in (4) is Kmax, and calculating a representative value R=(D·Kmin) / Kmax or a representative value R=(D·Kmax) / Kmin.

16. An odor data analysis program for analyzing odor data, which is time-series data output from an odor sensor, by an analysis unit, The odor sensor has an adsorption film that adsorbs an odor substance, detects the odor substance by the odor substance being adsorbed by the adsorption film, and converts the amount of the odor substance adsorbed into a predetermined physical quantity to output odor data that is time-series data. The odor data analysis program is installed on a computer. (1) setting the odor data output by the odor sensor in a state where the odor substance is not substantially detected as reference data; (2) detecting the odor substance during a detection period from a detection start time to a detection end time, and outputting the odor data; (8) calculating a difference value between a detected peak value of the odor data corresponding to the detection period and the reference data; (6) calculating a half-width value during the detection period; (10) When the difference value in (8) is D and the half width value in (6) is HW, and calculating a representative value R=D·HW.

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