Object condition analysis system, object condition analysis method, and program

Abstract

To provide an object condition analysis system, an object condition analysis method, and a program which achieve a strain sensor having the improved measurement accuracy of strain.SOLUTION: An object condition analysis system comprises: a sensor section which includes a temperature sensor and a strain sensor and which is attached to an object such as a railroad rail; a relation specification section for obtaining the relation between a temperature and a strain value on the basis of collected data output from the sensor section; and a calculation section for calculating a transmission rate Tr indicating such a rate that the strain of the object is transmitted to the strain sensor and an offset Δεs of an output value of the strain sensor on the basis of the obtained relation.SELECTED DRAWING: Figure 16

Description

[Technical Field]

[0001] The present invention relates to an object state analyzing system, an object state analyzing method, and a program. [Background technology]

[0002] The volume of objects such as metals and resins changes depending on the temperature of the object. When the volume of an object changes due to a change in temperature, distortion occurs in the object, which can have a negative impact on the use of the object.

[0003] For example, in railway rails (hereinafter also referred to as "rails"), an increase in axial force due to temperature rise can cause the rails to bulge or buckle (hereinafter also referred to as "abnormal conditions") If an abnormal condition occurs in the rails, railway vehicles (hereinafter also referred to as "electric trains" or "trains") cannot operate safely or normally, and this may ultimately cause disruption to railway operations.

[0004] Therefore, in order to prevent or suppress the occurrence of abnormal conditions in the rails such as buckling and to maintain safe train operation, work has been carried out to measure the axial force of the rails and monitor the rail condition. In other words, if the axial force occurring in the rails can be measured before the rails buckle, appropriate countermeasures can be taken depending on the magnitude of the axial force, which can contribute to the safe operation of trains.

[0005] On the other hand, strain sensors have been developed as devices for measuring the strain of an object with high precision, in which multiple piezoresistors, amplifiers, A / D converters, and various other circuits are formed on the surface of a semiconductor substrate. An example of such a strain sensor module is described in Patent Document 1. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] Patent No. 6293982 Summary of the Invention [Problem to be solved by the invention]

[0007] However, when measuring strain in an object using a strain sensor, the strain sensor is attached to the object via an intermediary such as an adhesive. The strain generated in the object is transmitted to the semiconductor chip via the intermediary. The state of the intermediary is not always constant; there is individual variation and deterioration occurs over time. For this reason, it is very difficult to improve the accuracy of strain measurement using a strain sensor.

[0008] An object of the present invention is to provide a technique that can improve the accuracy of measuring the strain of an object using a strain sensor. [Means for solving the problem]

[0009] A representative embodiment of the present invention is an object state analysis system that analyzes the state of an object, comprising: a sensor unit that is attached to the object and includes a strain sensor and a temperature sensor; a relationship determination unit that determines the relationship between temperature and the output value of the strain sensor based on data output from the sensor unit; and a calculation unit that calculates, based on the determined relationship, a transmission rate that indicates the rate at which strain in the object is transmitted to the strain sensor, and an offset of the output value of the strain sensor.

[0010] A representative embodiment of the present invention is an object state analysis method for analyzing the state of an object, which determines the relationship between temperature and the output value of the strain sensor based on data output from a sensor unit attached to the object and including a strain sensor and a temperature sensor, and calculates a transmission rate indicating the proportion of strain in the object transmitted to the strain sensor and an offset of the output value of the strain sensor based on the determined relationship.

[0011] Furthermore, a representative embodiment of the present invention is a program for causing a computer to function as a relationship determination unit that determines the relationship between temperature and the output value of a strain sensor based on data output from a sensor unit that is attached to an object and includes a strain sensor and a temperature sensor, and a calculation unit that calculates, based on the determined relationship, a transmission rate that indicates the rate at which strain in the object is transmitted to the strain sensor, and an offset of the output value of the strain sensor. [Effects of the Invention]

[0012] According to the present invention, it is possible to improve the accuracy of measuring the strain of an object using a strain sensor. [Brief explanation of the drawings]

[0013] [Figure 1] 1 is a schematic plan view showing a configuration of a semiconductor chip including a strain sensor and a temperature sensor according to an embodiment of the present invention. [Figure 2] FIG. 2 is a top view of the sensor module. [Figure 3] FIG. 2 is a top view showing a state in which the sealing resin of the sensor module has been removed. [Figure 4] 4 is a cross-sectional view taken along the line AA in FIG. 3. [Figure 5] FIG. 10 is a diagram for explaining measurement of rail axial force. [Figure 6] FIG. 1 is a diagram showing functional blocks realized by a computer. [Figure 7] FIG. 10 is a diagram showing an example of the relationship between rail temperature and strain sensor output value based on the output of a sensor module attached to a stationary section of the rail. [Figure 8] FIG. 8 is a diagram comparing some of the strain sensor output values ​​shown in FIG. 7 with the relationship between strain and temperature calculated from the thermal expansion coefficient of the rail. [Figure 9] FIG. 1 is a first diagram for explaining the data correction process for a stationary section of the rail. [Figure 10] FIG. 2 is a second diagram for explaining the data correction process for a stationary section of the rail. [Figure 11]FIG. 10 is a diagram showing an example of typical data of strain sensor output values ​​in a movable section of the rail. [Figure 12] FIG. 10 is a diagram showing a data profile of strain sensor output values ​​during temperature rise. [Figure 13] FIG. 10 is a diagram for explaining data correction processing for a movable section of the rail. [Figure 14] 10A and 10B are diagrams for explaining a procedure for subtracting the influence of an offset from a strain sensor output value. [Figure 15] 10A and 10B are diagrams for explaining a procedure for subtracting the influence of the transmissibility from the strain sensor output value. [Figure 16] FIG. 4 is a diagram for explaining the flow of processing of a data correction algorithm according to the present embodiment. [Figure 17] FIG. 10 is a graph showing an example of extracted data during temperature rise. [Figure 18] FIG. 10 is a diagram for explaining an experimental method. [Figure 19] FIG. 10 shows the results of a tensile test after crack formation. [Figure 20] FIG. 10 is a diagram showing the results of measuring the transmissibility intermittently and continuously over a long period of time. [Figure 21] FIG. 21 is a diagram showing the rate of change of the transmission ratio Tr based on the data in FIG. 20. [Figure 22] FIG. 10 is a flow chart showing an example of an algorithm for monitoring the soundness of an adhesive layer by the measurement object state analyzing system according to the present embodiment. [Figure 23] FIG. 10 is a flowchart showing another example of an algorithm for monitoring the soundness of an adhesive layer by the measurement object state analyzing system according to the present embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0014] Hereinafter, an embodiment of the present invention will be described. In all drawings used to explain the present embodiment, the same components are generally designated by the same reference numerals, and repeated explanations will be omitted. In order to make the drawings easier to understand, hatching may be used even in plan views.

[0015] In this embodiment, a sensor module including a strain sensor and a temperature sensor is attached to a measurement object, the module is connected to a computer, and the computer corrects the output value of the strain sensor to measure or monitor the strain of the measurement object with high accuracy. Note that the sensor module is an example of a "sensor unit" in this application. Also, the measurement object is an example of an "object" in this application.

[0016] <Strain and temperature sensors> FIG. 1 is a schematic plan view showing the configuration of a semiconductor chip 1 including a strain sensor and a temperature sensor according to this embodiment. As shown in FIG. 1, the semiconductor chip 1 includes, on a silicon substrate 9, piezoresistors 2x-1, 2y-1, 2x-2, and 2y-2 as sensor elements, an amplifier 3, an A / D converter 4, memory and calculation units 5 and 6, a temperature sensor 7, and pads 8 as electrodes for electrically connecting to an external device. The silicon substrate 9, piezoresistors 2x-1, 2y-1, 2x-2, and 2y-2, the amplifier 3, the A / D converter 4, and the memory and calculation units 5 and 6 constitute a strain sensor and are an example of the "strain sensor" in this application. The temperature sensor 7 is an example of the "temperature sensor" in this application.

[0017] The piezoresistive elements 2x-1, 2y-1, 2x-2, and 2y-2 are the core of the strain sensor, and have the property that the resistance value changes depending on the force applied to these piezoresistive elements 2x-1, 2y-1, 2x-2, and 2y-2.

[0018] 1, piezoresistors 2x-1, 2y-1, 2x-2, and 2y-2 are arranged parallel to the outer shape of silicon substrate 9. Specifically, piezoresistors 2x-1 and 2x-2 are arranged in the X direction of silicon substrate 9, and piezoresistors 2y-1 and 2y-2 are arranged in the Y direction of silicon substrate 9. These four sensor elements form a bridge, and the center of the bridge is approximately the same as the center of silicon substrate 9.

[0019] In this embodiment, the sensor elements are piezoresistance elements 2x-1, 2y-1, 2x-2, and 2y-2, which are silicon elements with impurities diffused therein. Note that the sensor elements are not limited to piezoresistance elements, and may be made of a material whose resistance changes with strain, such as a thin film of silicon carbide (SiC) or chromium nitride (CrN).

[0020] Also, although only four piezoresistance elements are shown in Figure 1, many elements may be formed by dividing them in the same direction, and the bridge shown in Figure 1 may be considered as a circuit made up of many resistance elements.

[0021] Next, we will discuss the outputs of piezoresistors 2x-1, 2y-1, 2x-2, and 2y-2 when strain is applied. The changes in resistance of piezoresistors 2x-1 and 2x-2 caused by strain εx in the X direction are approximately equal. Therefore, the sum of the resistance changes of both piezoresistors, i.e., 2x-1 and 2x-2, is denoted as ΔRx. Similarly, the sum of the resistance changes of piezoresistors 2y-1 and 2y-2 caused by strain εy in the Y direction is denoted as ΔRy. The strain sensor used in this embodiment generates an output value equivalent to the difference between strain εx in the X direction and strain εy in the Y direction, i.e., εx - εy. Therefore, when strain is applied, the outputs of the piezoresistance elements 2x-1, 2y-1, 2x-2, and 2y-2 correspond to the resistance change of ΔRx−ΔRy.

[0022] To explain in more detail, let's consider the output when a tensile stress σx is applied only in the X direction. When tensile stress σx is applied only in the X direction to piezoresistor elements 2x-1, 2y-1, 2x-2, and 2y-2, a strain εx in the X direction is generated. In this case, no stress is applied in the Y direction, but a compressive strain εy = -νεx occurs due to the material's Poisson's ratio ν. As a result, a signal value equivalent to the strain εx - εy = εx (1 + ν) is output.

[0023] Furthermore, as described above, the semiconductor chip 1 used in this embodiment includes an amplifier 3 that amplifies the signal of the bridge circuit, an A / D converter 4, memory and calculation units 5 and 6, and a temperature sensor 7. The memory and calculation units 5 and 6 include, for example, a memory unit such as a semiconductor memory, and a calculation unit such as a CPU (Central Processing Unit) or an MCU (Micro Controller Unit).

[0024] The memory sections of the memory and calculation units 5 and 6 store correction data for correcting the output of the bridge circuit. The calculation sections of the memory and calculation units 5 and 6 correct the output of the bridge circuit based on the correction data stored in the memory sections. One of the memory and calculation units 5 stores, for example, an output adjustment logic, which is a program for adjusting the output in response to strain, in its memory section, and the calculation section adjusts the output of the bridge circuit based on the output adjustment logic. The other memory and calculation unit 6 stores, for example, a temperature characteristic error correction logic, which is a program for correcting errors due to temperature characteristics, in its memory section, and the calculation section corrects the output of the bridge circuit based on the detection result of the temperature sensor 7 and the temperature characteristic error correction logic.

[0025] <Sensor module> Strain generated in the object to be measured must be transmitted to the strain sensor in the semiconductor chip 1 described above. However, directly attaching the semiconductor chip 1 to the object to be measured is not practical from the viewpoint of handling. It is also difficult to extract signals from the semiconductor chip 1. Therefore, this embodiment proposes a sensor module that can be easily attached to the object to be measured. An example of this is shown in Figure 2.

[0026] 2 is a top view of the sensor module 10. The sensor module 10 includes an FPC (Flexible Printed Circuit) 13 as a base material, a thin metal plate 11 disposed on a first surface of the FPC 13, and a sealing resin 12 disposed on a second surface of the FPC 13. The sensor module 10 is an example of a "sensor unit" in the present application. The thin metal plate 11 is an example of a "metal plate" in the present application.

[0027] 2, the FPC 13 has a long shape, with a metal sheet 11 and a sealing resin 12 disposed on one end side of the FPC 13, and an output terminal 131 disposed on the other end side of the FPC 13. The output terminal 131 is connected to a computer (described later) via a connector, a cable, or the like.

[0028] The thin metal plate 11 is bonded to the semiconductor chip 1 (not shown in FIG. 2) described with reference to FIG. 1, and includes a sealing resin 12 for protecting the semiconductor chip 1.

[0029] When using the sensor module 10, the back surface of the thin metal plate 11 of the sensor module 10 in Figure 2 is attached to the object to be measured. Attachment methods include spot welding or mechanical fastening with screws, but spot welding causes localized strain in the thin metal plate 11, and screw fastening causes torsional strain in the thin metal plate 11 due to friction with the screw head. These strains are known as noise, and are undesirable because they are a major factor in reducing the measurement accuracy of the sensor module 10.

[0030] The inventors have come to the realization that when attaching the sensor module 10 to the object to be measured, particularly a railway rail, it is most appropriate to use an adhesive to attach it in order to suppress distortion occurring in the thin metal plate 11.

[0031] When the sensor module 10 is attached to the object to be measured with an adhesive, the strain of the object to be measured is transmitted to the thin metal plate 11 via the adhesive, and the strain of the thin metal plate 11 is transmitted to the semiconductor chip 1.

[0032] 3 is a top view showing the sensor module 10 with the sealing resin 12 removed. The semiconductor chip 1 is placed at the center of a punched hole 132 provided in the FPC 13. As shown in FIGS. 2 and 3, the thin metal plate 11, the semiconductor chip 1, and the punched hole 132 are all positioned at approximately the same center and are arranged point-symmetrically (see also FIG. 4). This arrangement is expected to reduce thermal strain caused by differences in the thermal expansion coefficients of the thin metal plate 11, the FPC 13, and the semiconductor chip 1.

[0033] 4 is a cross-sectional view taken along the line AA in FIG. 3. As shown in FIG. 4, the semiconductor chip 1 is bonded to the thin metal plate 11 by a bonding layer 15. In this embodiment, gold-tin eutectic solder is used for the bonding layer 15, but the bonding layer 15 is not limited to this. The bonding layer 15 only needs to have a strong bonding strength and a sufficient elastic modulus to transmit the strain of the thin metal plate 11 to the semiconductor chip 1. The bonding layer 15 may be formed using a method such as diffusion bonding, which involves heating while applying pressure, or surface activation bonding, which involves forming a clean surface in a vacuum and then applying pressure.

[0034] In this embodiment, the pad 8 (not shown in FIG. 4) shown in FIG. 1 is connected to a wiring (not shown) formed on the FPC 13 by a gold wire 14, and a signal is output from an output terminal 131 formed at the end of the FPC 13. The thin metal plate 11 is attached to the rail 100, which is the object to be measured, using an adhesive 16. The adhesive 16 is an example of the "adhesive" in this application.

[0035] <Attaching the sensor module to the rail> In this embodiment, an example will be described in which the sensor module 10 is attached to a rail as a measurement object to measure an axial force (hereinafter also referred to as rail axial force) generated by distortion of the rail.

[0036] 5 is a diagram for explaining measurement of rail axial force. In FIG. 5, a sensor module 10 is attached to a rail 100 placed on a sleeper 101.

[0037] The position where the sensor module 10 is attached is not functionally limited, but considering the need to avoid interference with railway wheels, ease of attachment work, and other factors, it is desirable to attach the sensor module 10 to the position shown in FIG. 5 , i.e., the side position known as the "belt" of the rail 100. In this embodiment, the sensor module 10 is attached to the rail 100 using a heat-curing epoxy adhesive. More specifically, the sensor module 10 is attached to the rail 100 by heating the rail and hardening the epoxy adhesive while pressing the sensor module 10 against the rail with a predetermined force. In this embodiment, a method is used in which an aluminum heat block (not shown) heated by a heater is pressed against the surface of the rail 100 opposite the surface where the sensor module 10 is attached.

[0038] Various methods can be used to heat the rail 100, adhesive, etc., such as pressing a heat block heated by a heater against the strain sensor from the attachment side so as to surround it, or applying high-temperature hot air.

[0039] 5, a computer 20 is connected to the sensor module 10. The computer 20 has a processor 21, a memory 22, a storage device 23, and an interface 24, which are connected to one another via a bus 25. The processor 21 is configured, for example, by a CPU. The memory 22 is configured, for example, by a RAM (Random Access Memory), a ROM (Read Only Memory), etc. The storage device 23 is what is known as storage, and is configured, for example, by a HDD (Hard Disk Drive), an SSD (Solid State Drive), etc.

[0040] A program PG is stored in the memory 22 or the storage device 23. The processor 21 reads the stored program PG and executes it using the memory 22, the storage device 23, etc., thereby functioning as each functional block.

[0041] FIG. 6 is a diagram showing functional blocks realized by the computer 20. As shown in FIG. 6, the computer 20 functions as a relationship identification unit 31, a calculation unit 32, a correction unit 33, a characteristic identification unit 34, and a notification unit 35. These functional blocks work together to execute various processes and algorithms. The various processes and algorithms executed include data correction processing, data preprocessing, a data correction algorithm, and a data monitoring algorithm. Details of each functional block, the various processes, and the various algorithms will be described later.

[0042] <Example of measurement results using strain sensors 1> Here, an example of measurement of strain sensor output values ​​in a stationary section of the rail and a data correction process for correcting the strain sensor output values ​​will be described.

[0043] Generally, rails are fixed to the sleepers that align them, and longitudinal movement is restricted by the cumulative force of this fixing. Therefore, the rails are less likely to undergo longitudinal thermal expansion even when the temperature rises. This area of ​​the rail is called the "immovable section."

[0044] On the other hand, the cumulative fixing force is small at the ends and joints of the rail, so when the rail temperature rises, the thermal expansion force exceeds the fixing force, causing thermal expansion in the longitudinal direction. This area of ​​the rail is called the "moving section."

[0045] Fig. 7 is a diagram showing an example of the relationship between rail temperature T and strain sensor output value εs based on the output of a sensor module attached to a stationary section of the rail. The graph shown in Fig. 7 shows the measurement results for four strain sensors H1 to H4 attached to a stationary section of the rail. In the graph shown in Fig. 7, the horizontal axis represents rail temperature T, and the vertical axis represents strain sensor output value εs. The strain sensor output value εs is a value that represents strain in the longitudinal direction of the rail, with a positive value representing tensile strain and a negative value representing compressive strain.

[0046] Here, we will explain the strain sensor output value εs again. When the temperature rises, strain occurs in the strain sensor due to the difference in thermal expansion coefficient between the rail and the strain sensor. This strain is called εth. However, the rail and the thin metal plate 11 that makes up the strain sensor are made of the same iron-based material, and their thermal expansion coefficients are almost the same, so the impact of the difference in thermal expansion coefficient is small. However, to ensure accuracy, we attached the strain sensor in advance to an iron material of the same quality as the rail that is unconstrained and allows free thermal expansion, and then changed the temperature to measure the strain sensor output with respect to temperature, i.e., the strain εth caused by the difference in thermal expansion coefficient between the rail and the strain sensor. This strain εth value was subtracted from the strain sensor output to cancel the effect of εth.

[0047] As explained above, the strain sensor output value is calculated from the difference between the resistance change ΔRx of the internal piezoresistor in the X direction and the resistance change ΔRy of the internal piezoresistor in the Y direction. That is, an output value corresponding to the difference between the strain amount εx in the X direction and the strain amount εy in the Y direction, i.e., εx - εy, is generated. In the example of FIG. 7, the rail longitudinal direction is the X direction and the rail height direction is the Y direction, and details will be explained below.

[0048] Because the rail is constrained in the longitudinal direction, i.e., the X direction, the thermal expansion of the attached strain sensor in the X direction is suppressed, causing compressive strain. This strain is εx.

[0049] On the other hand, the rail is not constrained in the height direction, i.e., the Y direction, and is therefore free to expand thermally. The attached strain sensor also expands thermally, and the difference in thermal expansion generates strain. However, as explained above, the thermal expansion coefficient of the rail and that of the thin metal plate 11 that makes up the strain sensor are nearly equal, so the impact of the difference in thermal expansion coefficient is small. Furthermore, this effect can be ignored because it is canceled out as strain εth.

[0050] More precisely, because the rail is constrained in the longitudinal direction, compressive strain occurs as the temperature rises. As a result, tensile strain of Poisson's ratio ν occurs in the rail height direction. This strain is also reflected in the strain sensor. This strain is εy.

[0051] As discussed above, the output value of the strain sensor corresponding to εx-εy due to temperature rise is the sum of the compressive strain generated by the longitudinal constraint of the rail and the tensile strain in the height direction, which is equal to Poisson's ratio ν.

[0052] In this example, the rail temperature T was measured using the output of the temperature sensor included in the sensor module. The graph in Fig. 7 shows the rail temperature change over several days and the strain sensor output value εs that occurred at that time.

[0053] Here, the relationship between axial force and strain in a rail will be explained. In terms of material mechanics, the relationship between axial force and strain is expressed by the following formula (1). Axial force = strain × elastic modulus × rail cross-sectional area (1)

[0054] In the above formula (1), the elastic modulus and rail cross-sectional area are constant, so strain can be considered to represent axial force. The rail expands with increasing temperature, but because it is completely fixed to the sleepers, thermal expansion is suppressed and the strain becomes compressive. In other words, there is a linear relationship between temperature increase and strain.

[0055] The temperature at which the sensor module 10 is attached to the rail is defined as Ts. The rail is heated to harden the adhesive, and the temperature Ts indicates the temperature at which the adhesive is cooled after hardening. When heated, the molecules that make up the adhesive polymerize and harden. Generally, adhesives shrink as they harden. The hardening of adhesives does not necessarily occur uniformly; it generally begins and progresses within a certain temperature range. Therefore, the shrinkage of the adhesive layer is not necessarily uniform, resulting in non-uniform strain. As a result, the non-uniform strain is transmitted to the thin metal plate 11, causing strain in the sensor module 10. This strain is not the axial force of the rail 100, but an offset Δεs that occurs in the sensor module 10 due to the adhesion.

[0056] As shown in Fig. 7, the offset Δεs is not constant because it depends on the state of the adhesive. The fact that this offset Δεs is not constant is problem (1) in measuring rail strain using a strain sensor.

[0057] In Figure 7, the gradient of strain sensor output value εs / rail temperature T is defined as E. Generally, the gradient E does not coincide with the thermal expansion coefficient α of the rail, which is the theoretical strain / temperature gradient. This is because the rail strain is attenuated as it is transmitted to the semiconductor chip 1 via the adhesive and thin metal plate 11. Furthermore, the gradient E is not a constant value because it depends on the state of the adhesive. The fact that this gradient E is not constant is issue (2) in measuring rail strain using a strain sensor.

[0058] <Correction process for stationary section data> The data correction process for the stationary section, which is applied to the output value data of the strain sensor attached to the stationary section of the rail, will be described with reference to FIGS. 8, 9, and 10. FIG.

[0059] Before describing the data correction process for the stationary section, terms will be defined.

[0060] Figure 8 compares a portion of the strain sensor output value εs shown in Figure 7 with the relationship between strain and temperature calculated from the rail's thermal expansion coefficient α. Figure 8 shows a data profile P1 as part of this strain sensor output value εs. Here, temperature T0 is the temperature when the rail is fixed. Also, the rail strain at this temperature T0 is assumed to be zero. In other words, the strain sensor output value εs when the rail temperature T is temperature T0 is assumed to be the offset Δε. As shown in Figure 8, the gradient expressed by the strain sensor output value εs / rail temperature T is assumed to be gradient E1. From gradient E1 and the rail's thermal expansion coefficient α, the transmissibility Tr is defined as shown in the following equation (2). Tr=E1 / α ··············(2)

[0061] The strain in the rail is transmitted to the semiconductor chip via the adhesive and thin metal plate, so it is attenuated before being transmitted to the semiconductor chip. The transmissibility Tr is a value that quantitatively indicates this attenuation, and is a value that indicates the proportion of the magnitude of strain generated in the measurement object that is transmitted to the semiconductor chip of the strain sensor.

[0062] Based on the output data of the sensor module collected within a certain set period, the computer's processor, i.e., relationship identifying unit 31, determines the gradient E1 and the strain sensor output value εs for temperature T0 as representing the relationship between the strain sensor output value εs and the rail temperature T. Furthermore, the processor, i.e., calculation unit 32, determines the transmissibility Tr and the offset Δε based on the relationship, i.e., the gradient E1 and the strain sensor output value εs for temperature T0.

[0063] Next, an outline of the data correction process for the stationary section will be explained.

[0064] Fig. 9 is the first diagram for explaining the data correction process for a stationary section of the rail. First, the processor, i.e., the correction unit 33, calculates εs1 by subtracting the offset Δε from the strain sensor output value εs according to the following equation (3). In Fig. 9, the strain sensor output value εs before subtracting the offset Δε is shown by a dotted line, and the strain sensor output value εs1 after subtraction is shown by a solid line. εs1=εs-Δε (3)

[0065] Fig. 10 is the second diagram for explaining the data correction process for the stationary section of the rail. Next, the correction unit 33 calculates εs2 by dividing the strain sensor output value εs1 by the transmissibility Tr according to the following equation (4). In Fig. 10, the dotted line indicates the data profile P1 of the strain sensor output value εs1 before division by the transmissibility Tr, and the solid line indicates the data profile P2 of the strain output value εs2 after division. εs2=εs1 / Tr (4)

[0066] Based on the corrected εs2 thus obtained, the strain, i.e., the axial force, in the stationary section of the rail can be determined with high accuracy.

[0067] The above-mentioned data correction process for the stationary section can solve the above-mentioned problems (1) and (2) in measuring rail strain using strain sensors.

[0068] Next, a measurement example of strain sensor output values ​​in a movable section of the rail and a data correction process for the movable section that corrects the strain sensor output values ​​will be described.

[0069] <Example of measurement results using strain sensors 2> The behavior of the movable section is complex because the axial force is released when minute slippage occurs between the rail and the fixture. Furthermore, this behavior is not constant but varies depending on the friction between the rail and the fixture.

[0070] Fig. 11 shows an example of typical data for strain sensor output values ​​in a movable section of the rail. The configuration of the graph shown in Fig. 11 is the same as that in Fig. 7. In Fig. 11, the solid line shows the data profile PA of the strain sensor output value εs when the rail temperature is rising (heating up), and the dotted line shows the data profile PB of the strain sensor output value εs when the rail temperature is falling (heating down). Furthermore, the arrows indicate the direction of change in the strain sensor output value as the rail temperature T rises and the direction of change in the strain sensor output value as the rail temperature T falls, respectively.

[0071] In the movable section, as in the stationary section, compressive strain occurs in the rail in proportion to the rise in rail temperature. However, when the rail temperature rises above a certain level, the compressive strain of the rail, i.e., the compressive axial force, exceeds the rail's fixing force, causing minute slippage between the rail and the fixing fixture, and the rail thermally expands. As a result, the compressive strain is released, and the relationship between the strain sensor output value εs and the rail temperature T becomes non-proportional.

[0072] When the rail temperature T drops from a state in which the rail has thermally expanded, the rail attempts to contract while the positional relationship between the rail and the fasteners, which was in a slipping state, remains fixed, resulting in tensile strain proportional to the temperature drop. When the temperature drops to a certain level, the axial force caused by the tensile strain in the rail exceeds the rail's fixing force, causing slippage between the rail and the fasteners. As a result, the state of the rail and the fasteners returns to the state it was in when the rail temperature began to rise. In other words, the strain sensor output value εs on the graph depicts hysteresis that follows different trajectories when the temperature is rising and when the temperature is falling.

[0073] As described above, the data changes in the strain sensor output value εs versus rail temperature T in the movable section are more complex than in the stationary section. However, if appropriate preprocessing is performed on the data of the strain sensor output value εs in the movable section, the calculation algorithm proposed in this application is effective, and its effect is no different from that in the stationary section.

[0074] The nature of the hysteresis depends on the frictional force between the rail and the fixture, and therefore varies depending on factors such as the strength of the rail fastening and the condition of the friction surface. In other words, the shape of the hysteresis on the graph is not constant. Therefore, for example, the strain sensor output value εs may not exhibit hysteresis and may return to the same profile as when the rail temperature rises when the rail temperature drops.

[0075] <Preprocessing of movable section data> The pre-processing of the strain sensor output data in the movable section of the rail described above will now be described.

[0076] When the strain sensor output value εs exhibits hysteresis, as shown in the graph in Figure 11, using data from both temperature rise and temperature fall makes it impossible to accurately grasp the behavior of the rail. Therefore, in the case of a movable section, it is best to use data from either temperature rise or temperature fall as the strain sensor output value data used in the data correction algorithm. In this example, only data from temperature rise is extracted.

[0077] 12 is a diagram showing the data profile of the strain sensor output value εs during temperature rise. Note that if the data change of the strain sensor output value εs with respect to the rail temperature T does not cause hysteresis and the data profile during temperature rise returns to the original profile during temperature fall, there is no need to extract only the data during temperature rise.

[0078] Next, from the graph shown in Fig. 12, the temperature range of rail temperature T where the rail temperature T and strain sensor output value εs are proportional, i.e., linear, is defined. In the data correction process for the movable section described below, data within this defined temperature range is used for analysis. The purpose of this preprocessing, which defines the temperature range for the data to be analyzed, is to eliminate the effect of axial force release due to minute rail slippage. The method for this is explained in detail in the next section.

[0079] <Moving area data correction processing> FIG. 13 is a diagram for explaining the data correction process for the movable section of the rail. First, the processor, i.e., the relationship identification unit 31, extracts a linear region from a data profile such as that shown in FIG. 12, performs linear approximation, and determines the slope (gradient) E1 of the approximated line. As explained in FIG. 11, the data profile PA of the strain sensor output values ​​εs maintains a straight line on the low rail temperature T side. However, on the high rail temperature T side, slight slippage occurs between the rail and the fixture, causing the data profile of the strain sensor output values ​​εs to deviate from the straight line. In other words, the key to extracting the linear region in the data profile PA is to determine where to set the upper limit temperature of the temperature range of the strain sensor output values ​​εs that is the target of data analysis.

[0080] In this embodiment, the method to be described below is used as a method for extracting a linear region in the data profile of the strain sensor output value εs.

[0081] The relationship identifying unit 31 first assumes that a preset temperature T0 is the upper limit temperature, performs linear approximation on the data profile of the strain sensor output value εs, and determines the slope E0 of the approximated line. Next, the relationship identifying unit 31 sets the upper limit temperature to temperature T0 plus a preset temperature range ΔT, i.e., temperature T0 + ΔT, and performs linear approximation on the data profile of the strain sensor output value εs in the temperature range below the upper limit temperature, and determines the slope E1(0) of the approximated line. Note that there are no particular restrictions on the temperature range ΔT, and it is sufficient if temperature T0 + ΔT is a temperature that can be assumed to be the rail temperature T.

[0082] Next, the relationship specifying unit 31 compares the slope E1(0) with the slope E0. If the difference is equal to or greater than a specified value, an infinitesimal temperature width dT, which is smaller than the temperature width ΔT, is subtracted from the temperature T0+ΔT, and the upper limit temperature is set to the temperature T0+ΔT-dT. The infinitesimal temperature width dT is determined in advance. There are no particular restrictions on the infinitesimal temperature width dT, but considering the calculation accuracy, a width of, for example, about one-tenth of the temperature width ΔT is appropriate.

[0083] The relationship determination unit 31 performs a linear approximation on the data profile of the strain sensor output value εs in a temperature range where the upper limit temperature is temperature T0 + ΔT - dT, and calculates the slope E1(1) of the approximated line. Next, the slope E1(1) is compared with the slope E0, and if the difference is equal to or greater than a specified value, the slope E1(1) is further subtracted by a small temperature width dT from the currently set upper limit temperature, and the upper limit temperature is set to temperature T0 + ΔT - 2dT. The relationship determination unit 31 performs a linear approximation on the data profile of the strain sensor output value εs in a temperature range where the upper limit temperature is temperature T0 + ΔT - 2dT, and calculates the slope E1(2) of the approximated line. Next, the slope E1(2) is compared with the slope E0, and if the difference is equal to or greater than a specified value, the slope E1(2) is further subtracted by a small temperature width dT from the currently set upper limit temperature, and the upper limit temperature is set to temperature T0 + ΔT - 3dT.

[0084] That is, the relationship identifying unit 31 repeats this series of calculations until the difference between the slope E1(m) calculated based on the set upper limit temperature and the slope E0 becomes equal to or less than a certain value, and determines the temperature T0+ΔT-ndT at which the difference from the slope E0 becomes equal to or less than the specified value as the final upper limit temperature. In this embodiment, the temperature at which E1(n) / E0 is equal to or greater than 0.95 and equal to or less than 1.05 is determined as the upper limit temperature. E1(n) (hereinafter referred to as E1) obtained by this method is determined as the slope in the linear region of the data profile of the strain sensor output value εs.

[0085] There are various methods for extracting the linear region of the data profile in the graph. The method for extracting the linear region is not limited to the above method and can be any method that can extract the linear region appropriately. For example, a method may be used in which the strain sensor output value εs and temperature data are graphed, and then the data region is identified by image processing to extract the linear region.

[0086] The data correction performed after the extraction of the linear region is the same as the correction of the movable section data. The calculation unit 32 uses the gradient E1 obtained by the above procedure to calculate the transmissibility Tr using equation (2), and calculates the offset Δε from the strain sensor output value εs for the temperature T0.

[0087] Fig. 14 is a diagram for explaining the procedure for subtracting the effect of the offset Δε from the strain sensor output value εs. First, the correction unit 33 performs a correction by subtracting the offset Δε from the strain sensor output value εs, as shown in Fig. 14. In Fig. 14, the data profile PA of the strain sensor output value εs before the correction is shown by a dotted line, and the data profile PA1 of the strain sensor output value εs1 after the correction is shown by a solid line. This sets the strain at temperature T0 when the rail is fixed to zero.

[0088] FIG. 15 is a diagram illustrating the procedure for subtracting the influence of the transmissibility from the strain sensor output value. Next, as shown in FIG. 15, the correction unit 33 performs a correction by dividing the strain sensor output value εs1 by the transmissibility Tr to obtain the strain sensor output value εs2. In FIG. 15, the dotted line represents the data profile PA1 of the strain sensor output value εs1 before the correction, and the solid line represents the data profile PA2 of the strain sensor output value εs2 after the correction. This correction ensures that the strain / temperature gradient in the linear region of the strain sensor output value εs2 is the thermal expansion coefficient α. This series of corrections can solve problems (1) and (2) in rail strain measurement using strain sensors, even for strain sensor output value data in the movable section.

[0089] <Data correction algorithm> The data correction algorithm used by the measurement object state analyzing system according to this embodiment will now be described. This data correction algorithm is executed by a processor included in a computer connected to the sensor module.

[0090] 16 is a diagram illustrating the flow of processing of the data correction algorithm according to this embodiment. In FIG. 16, symbols D1, D2, and D3 each represent data. Symbols S1 to S8 represent each step of the correction algorithm.

[0091] First, we will explain the data to be used. After attaching a sensor module containing the above-mentioned strain sensor and temperature sensor to the rail, which is the object to be measured, a processor in a computer connected to the sensor module executes the processing steps described below. That is, the processor associates the strain sensor output value and rail temperature data input from the sensor module via an interface with the date and time data input from a clock unit in the computer indicating when the data was acquired, and continuously stores this data in the computer's storage device as continuously collected data D1. The processor also extracts continuous data D2 within a set period of time that is set intermittently from the stored data under preset conditions, and stores the extracted data in the storage device.

[0092] In an example actually performed by the inventors, the data for the first week of every four weeks was extracted as continuous data D2 for a fixed period. In this case, in step S7 described below, the processor performs a correction calculation using the data D2 for one week, and corrects the data for the following four weeks. The processor also performs a correction calculation again using the uncorrected data for the last week, and corrects the data for the following four weeks, and this process is repeated.

[0093] However, the measurement time and interval of the continuous data D2 are not limited to the above example. If necessary, they may be set longer or shorter than the above period. The measurement time and interval of the continuous data D2 may be set according to the condition of the object to be monitored.

[0094] Next, the specific procedure for the correction process will be described. In step S1, the processor, i.e., the relationship specifying unit 31, determines whether the attachment position of the strain sensor that outputted the data to be processed, i.e., the measurement section of the rail, is a movable section or an immovable section.

[0095] To explain the process of step S1 more specifically, first, the relationship specifying unit 31 extracts only data during temperature rise from the continuous data D2.

[0096] Fig. 17 is a graph showing an example of extracted data during temperature rise. In the graph shown in Fig. 17, the vertical axis represents the strain sensor output value εs, and the horizontal axis represents the rail temperature T (°C) detected by the same sensor. When the measurement section is a movable section, as shown in Fig. 17, a straight line is maintained on the low side of the rail temperature T, but on the high side of the rail temperature T, slight slippage occurs between the rail and the fixture, causing the strain sensor output to deviate from the straight line.

[0097] Next, the relationship specifying unit 31 determines a temperature Tc0 that serves as a reference for calculation, and then calculates the strain / temperature gradient En between the temperature Tcn and the temperature Tc0.

[0098] In the movable section, the rail and fixture slide on the high-temperature side, releasing the strain, so the absolute value of En becomes small. However, in the immovable section, the gradient En is almost constant with respect to temperature. In this embodiment, a threshold is set for the rate of change of the gradient En with respect to temperature to determine whether the section is movable or immovable.

[0099] Note that the determination of the movable section and the immobile section can be made using various algorithms, and is not limited to the above method, as long as the distinction between the two can be appropriately determined. As another example of the determination method in step S1, the continuous data D2 may be graphed, and then the movable section and the immobile section may be determined by image processing.

[0100] If the relationship identifying unit 31 determines Yes in step S1, that is, if it determines that the continuous data D2 is a movable section, the relationship identifying unit 31 proceeds to step S2 and performs the data preprocessing described with reference to Figures 11 and 12. Furthermore, the relationship identifying unit 31 also calculates the gradient E1 in step S3 using the procedure described with reference to Figure 13.

[0101] On the other hand, if the relationship determination unit 31 determines No in step S1, i.e., that the continuous data D2 is a stationary section rather than a movable section, it skips the data preprocessing in step S2 and proceeds to step S3. After calculating the gradient E1, in step S4, the relationship determination unit 31 determines the validity of the gradient E1, i.e., whether the calculated gradient E1 value is valid. The ideal value of gradient E1 is equal to the thermal expansion coefficient α of the rail. However, since the gradient E1 is transmitted to the semiconductor chip via the adhesive and the thin metal plate, it is attenuated. Nevertheless, basic experimental results of the sensor module have shown that a valid range for gradient E1 can be set. In the case of the sensor module used in this example, the range is 0.95 × α > E1 > 0.6 × α, so the following formula was set as the valid range.

[0102] Thus, in step S4, if the calculated value of gradient E1 is 0.95×α or greater or 0.6×α or less, the relationship identification unit 31 determines No, i.e., the value of gradient E1 is invalid, returns the process to step S1, and repeatedly executes the processes from step S1 to step S4 described above.

[0103] In this way, by repeating the processes of steps S1 to S4, the judgment conditions and the pre-processing conditions of step S2 are reviewed.

[0104] Furthermore, after reviewing the conditions in steps S1 and S2, if E1 again deviates from the specified range in step S4, there may be a problem with the attachment of the strain sensor. In this case, an alarm is issued in step S44 to request a review of the attachment. Note that the appropriate range for gradient E1 depends on the structure of the sensor module. It is not necessarily limited to the range 0.95 x α > E1 > 0.6 x α. A reasonable range should be determined based on the results of basic experiments on the sensor module to be used.

[0105] Once a valid gradient E1 is calculated, the processor, i.e., the calculation unit 32, calculates the transmission rate Tr in step S5 and the offset Δε in step S6. Note that the calculation of the offset Δε requires the rail temperature T0 when the rail is fixed to the sleeper. Therefore, the temperature T0 must be set in advance. However, the temperature T0 is likely to change with each track maintenance work. Therefore, in the system according to this embodiment, it is necessary to allow the temperature T0 to be overwritten.

[0106] The transmission ratio Tr and the offset Δε calculated in steps S5 and S6 are returned to the data D1 by the processor, that is, the relationship specifying unit 31.

[0107] In step S7, the processor, i.e., the correction unit 33, corrects the measured strain using the calculated transmissibility Tr and offset Δε using equations (3) and (4) in the procedure described with reference to Figures 14 and 15, and outputs the corrected strain sensor output value εs2 in step S8. At the same time, the relationship identification unit 31 adds the detection period of the data on which the calculation was based to the transmissibility Tr and offset Δε, and stores them as data D3.

[0108] <Adhesive layer integrity monitoring> In this embodiment, the sensor module 10 is attached to the rail, which is the object to be measured, using a thermosetting epoxy adhesive. Attachment using an adhesive minimizes distortion caused by attachment, allowing for stable adhesion. Additionally, epoxy adhesive is a highly stable material, and has, for example, excellent weather resistance.

[0109] However, even such highly stable materials will deteriorate over the long term if they are repeatedly subjected to thermal cycles and strain due to the expansion and contraction of the object being measured, as well as exposure to moisture, ultraviolet rays, etc. Specifically, epoxy adhesives first experience a decrease in their elastic modulus due to the scission of polymerization in the resin. Next, the epoxy adhesive will develop cracks and peeling at the interface between the adhesive layer and the thin metal plate, or between the adhesive layer and the object being measured, where stress is concentrated.

[0110] If the elastic modulus of the epoxy adhesive decreases or peeling occurs at the interface between the adhesive layer and the object being measured, the strain of the object being measured will not be transmitted to the thin metal plate, and the output of the strain sensor will decrease. However, it is difficult to predict a decrease in the elastic modulus or peeling at the interface from the strain sensor output alone. This is the challenge(3) in measuring rail strain using strain sensors.

[0111] As described above, the transmitted strain decreases, i.e., the transmissibility Tr decreases, depending on the degree to which the integrity of the adhesive layer is impaired. Therefore, if the transmissibility Tr is measured intermittently and continuously over a long period of time, the transition or rate of change of the measured transmissibility Tr can be determined, and the integrity of the adhesive layer can be estimated.

[0112] The experiments conducted to verify this and their results are described below.

[0113] Fig. 18 is a diagram for explaining the experimental method. As shown in Fig. 18, the sensor module 10 was attached to the test piece 200 using a thermosetting epoxy adhesive. As described above, the sensor module 10 has the thin metal plate 11 joined to the semiconductor chip 1, and the thin metal plate 11 is attached to the test piece 200 via an adhesive layer 300. Note that the sealing resin 12 is not shown here in order to show the position of the semiconductor chip 1.

[0114] The dimensions of the semiconductor chip 1 are 2.3 mm x 2.3 mm in the XY plane. The dimensions of the thin metal plate 11 are 10 mm x 10 mm in the XY plane, with a thickness of 0.3 mm, and the material of the thin metal plate 11 is SUS403. The thickness of the adhesive layer 300 is approximately 0.05 mm. The test piece 200 is a tensile test piece with a thickness of 10 mm, and is made of SUS304.

[0115] After the sensor module 10 was attached, the test piece 200 was tested using a tensile tester. However, the strain range applied was limited to a range that would not damage the adhesive layer 300. In this test example, the strain sensor output value, i.e., the strain or strain amount, was up to 500 × 10 -6 The output of the strain sensor was compared with the theoretical strain of the test piece 200 obtained from the output of a load cell attached to the tensile tester, and the transmissibility Tr was calculated.

[0116] After the above test, a crack 301 was formed in the adhesive layer 300 from the tip of the metal sheet 11. An attempt was made to form a crack at the interface between the adhesive layer 300 and the test piece 200, but the adhesive layer 300 was difficult to process due to its thin thickness, and the adhesive layer 300 was almost completely removed. The crack 301 below the metal sheet 11 was formed by penetrating through in the Y direction. The width of the crack measured from the tip of the metal sheet 11 is defined as A.

[0117] After forming a crack with a peeling distance (i.e., crack width A) of 1 mm, the tensile test was conducted again and the transmissibility Tr was calculated. Then, the crack width A was further increased, and the tensile test and calculation of the transmissibility Tr were repeated. The test results are shown in Figure 19.

[0118] Figure 19 shows the results of a tensile test after crack formation. As shown in Figure 19, the reduction in transmissibility Tr is gradual until the crack width A is about 2 mm. When the crack width A exceeds 2 mm, the reduction in transmissibility Tr increases, and when the crack width A is 3 mm or more, the transmissibility Tr drops sharply. This is thought to be because the crack reached directly below the semiconductor chip 1, causing a sharp drop in the amount of strain transmitted to the semiconductor chip 1. These results confirm that there is a clear correlation between the reduction in transmissibility Tr and the soundness of the adhesive layer.

[0119] Figure 20 shows the results of intermittent and continuous measurements of transmissibility Tr over a long period of time. Figure 20 is a diagram showing the characteristics of the strain sensor, with the horizontal axis representing time (days) and the vertical axis representing transmissibility Tr. Measurements were taken a total of 15 times, including the day the sensor module was attached. The transmissibility Tr was calculated from continuous data over approximately one week. As shown in Figure 20, the transmissibility Tr is approximately constant initially, i.e., for several months after attachment, but gradually decreases over time, and the decrease in transmissibility Tr accelerates toward the end. The decrease in transmissibility Tr is expected to be due to deterioration and peeling of the adhesive layer.

[0120] Figure 21 is a graph showing the rate of change of transmissibility Tr based on the data in Figure 20. The horizontal axis represents time (days), and the vertical axis represents the value obtained by dividing the difference ΔTr between the transmissibility Tr before and after the measurement by the measurement time interval. In Figure 20, if even a small decrease in transmissibility Tr is shown as a rate of change, the change becomes clearer.

[0121] By continuously calculating the transmissibility Tr and storing it in chronological order in an arbitrary storage device as data D3 shown in Fig. 16, it is possible to predict abnormalities in the adhesive layer. For example, as shown in Fig. 20, a reference value 1 of the transmissibility Tr corresponding to the timing of replacing the sensor module is determined in advance, and an alarm is issued when the transmissibility Tr reaches that reference value. Alternatively, the rate of change of the transmissibility Tr is calculated each time, and an alarm is issued when the rate of change of the transmissibility Tr reaches reference value 2.

[0122] FIG. 22 is a flow chart showing an example of an algorithm for monitoring the soundness of an adhesive layer by the measurement object state analyzing system according to this embodiment.

[0123] 22, in step J1, the processor of the computer connected to the sensor module, i.e., the characteristic specifying unit 34, determines whether a new transmissibility Tr has been calculated. If it is determined that a new transmissibility Tr has not been calculated (J1: No), the characteristic specifying unit 34 returns the processing step to step J1. If it is determined that a new transmissibility Tr has been calculated (J1: Yes), the characteristic specifying unit 34 proceeds to step J2.

[0124] In step J2, the characteristic specifying unit 34 reads out the time-series transmissibility Tr calculated up to that point from the storage device.

[0125] In step J3, the characteristic specifying unit 34 determines whether the most recent transmission ratio Tr that has been read out is below a set reference value 1. If the characteristic specifying unit 34 determines that the transmission ratio Tr is below the reference value (J3: Yes), it proceeds to step J4, and if it determines that the transmission ratio Tr is not below the reference value (J3: No), it proceeds to step J5.

[0126] In step J4, the processor, i.e., the notification unit 35, issues an alarm. The alarm may be, for example, a sound output and a text display on the display unit. This allows the user to know that, for example, the adhesive layer of the sensor module has deteriorated or an abnormality has occurred, and that it is time to replace the sensor module.

[0127] In step J5, the characteristic identification unit 34 determines whether there is a reason to terminate the data monitoring algorithm. If it is determined that there is such a reason (J5: Yes), the characteristic identification unit 34 terminates the data monitoring algorithm. If it is determined that there is no such reason (J5: No), the characteristic identification unit 34 returns to the processing step J1.

[0128] FIG. 23 is a flow chart showing another example of an algorithm for monitoring the soundness of an adhesive layer by the measurement object state analyzing system according to this embodiment.

[0129] 23, in step J11, the processor of the computer connected to the sensor module, i.e., the characteristic specifying unit 34, determines whether a new transmissibility Tr has been calculated. If it is determined that a new transmissibility Tr has not been calculated (J11: No), the characteristic specifying unit 34 returns the processing step to step J11. If it is determined that a new transmissibility Tr has been calculated (J11: Yes), the characteristic specifying unit 34 proceeds to step J12.

[0130] In step J12, the characteristic specifying unit 34 reads out the time-series transmissibility Tr calculated up to that point from the storage device.

[0131] In step J13, the characteristic specifying unit 34 calculates the time change rate of the transmissibility Tr. Specifically, the characteristic specifying unit 34 divides the difference ΔTr between the transmissibility Tr before and after the time series transmissibility Tr by the measurement time interval.

[0132] In step J14, the characteristic specifying unit 34 determines whether the time rate of change of the transmissibility Tr calculated from the latest transmissibility Tr read out exceeds a set reference value 2. If the characteristic specifying unit 34 determines that the time rate of change of the transmissibility Tr exceeds the reference value 2 (J14: Yes), the characteristic specifying unit 34 proceeds to step J15, and if the characteristic specifying unit 34 determines that the time rate of change of the transmissibility Tr does not exceed the reference value 2 (J14: No), the characteristic specifying unit 34 proceeds to step J16.

[0133] In step J15, the processor, i.e., the notification unit 35, issues an alarm. The alarm may be, for example, a sound output and a text message displayed on the display unit. This allows the user to grasp the degree of deterioration or abnormality of the adhesive layer of the sensor module and to know that it is almost time to replace the sensor module.

[0134] In step J16, the characteristic identification unit 34 determines whether there is a reason to terminate the data monitoring algorithm. If it is determined that there is such a reason (J16: Yes), the characteristic identification unit 34 terminates the data monitoring algorithm. If it is determined that there is no such reason (J16: No), the characteristic identification unit 34 returns to the processing step J11.

[0135] This data monitoring algorithm makes it possible to predict a decrease in the elastic modulus of the strain sensor included in the sensor module or peeling at the interface, and to determine when to replace the sensor module, making it possible to continue stable monitoring of the strain of the object being measured without interruption due to unexpected problems.In other words, this data monitoring algorithm can solve the above-mentioned problem (3) in measuring rail strain using strain sensors.

[0136] In this embodiment, for simplicity of explanation, the output of one sensor module is used as an example. However, in reality, it is conceivable that multiple sensor modules are attached to the object to be measured, and the data correction algorithm and the data monitoring algorithm are applied to the outputs of the multiple sensor modules, respectively.

[0137] Furthermore, the embodiments of the present invention are not limited to those described above, and a method for analyzing the state of an object performed by the above system is also an embodiment of the present invention. That is, an object state analysis method for analyzing the state of an object, which determines a relationship between temperature and output values ​​of the strain sensor based on data output from a sensor unit attached to the object and including a strain sensor and a temperature sensor, and calculates a transmissibility indicating the rate at which strain in the object is transmitted to the strain sensor and an offset of the output value of the strain sensor based on the determined relationship, is also an example of an embodiment.

[0138] In addition to the above-described embodiments of the present invention, a program executed by a computer in the above-described system is also an embodiment of the present invention. That is, a program that causes a computer to function as a relationship determining unit that determines the relationship between temperature and the output value of a strain sensor based on data output from a sensor unit that is attached to an object and includes a strain sensor and a temperature sensor, and a calculation unit that calculates, based on the determined relationship, a transmissibility indicating the rate at which strain in the object is transmitted to the strain sensor and an offset of the output value of the strain sensor is also an example of an embodiment. Furthermore, a tangible computer-readable storage medium that non-temporarily stores the program is also an embodiment of the present invention. [Explanation of symbols]

[0139] 1...semiconductor chip, 2x-1, 2y-1, 2x-2, 2y-2...piezoresistive element, 3...amplifier, 4...A / D converter, 5, 6...memory calculation unit, 7...temperature sensor, 8...pad, 9...silicon substrate, 10...sensor module, 11...thin metal plate, 12...sealing resin, 13...FPC, 14...gold wire, 15...bonding layer, 16...adhesive, 20...computer, 21...processor, 22...memory, 23...storage device, 24...interface, 25...bus, 31...relationship determination unit, 32...calculation unit, 33...correction unit, 34...characteristic determination unit, 35...notification unit, 100...rail, 131...output terminal, 132...punched hole, 300...adhesive layer, εs...strain sensor output value, εs1, εs2...strain sensor output value after correction, Δεs...offset, α...thermal expansion coefficient of rail, Tr...transmissibility, PG...program

Claims

1. a sensor unit that is attached to a railway rail as an object using an adhesive and includes a strain sensor and a temperature sensor; a calculation unit that calculates a gradient obtained by dividing an output value of the strain sensor by the temperature of the railway rail, and then divides the gradient by the thermal expansion coefficient of the railway rail to obtain a transmission rate that indicates the rate at which the magnitude of strain in the railway rail is transmitted to the strain sensor, and calculates the output value of the strain sensor when the railway rail is fixed to a sleeper as an offset of the output value of the strain sensor; and a correction unit that corrects the output value of the strain sensor by dividing a value obtained by subtracting the offset from the output value of the strain sensor by the transmissibility; Equipped with Object condition analysis system.

2. 2. The object state analysis system according to claim 1, A characteristic specifying unit is provided, the calculation unit calculates a plurality of the transmission rates in time series, the characteristic specifying unit determines a characteristic of a time change of the transmissibility based on the calculated time series of the transmissibility. Object condition analysis system.

3. 3. The object state analyzing system according to claim 2, a notification unit that issues an alarm when the future transmissibility up to a set time point estimated based on the characteristics falls below a reference value; Object condition analysis system.

4. 2. The object state analysis system according to claim 1, a notification unit that issues an alarm when the calculated transmissibility falls below a reference value; Object condition analysis system.

5. 2. The object state analysis system according to claim 1, the calculation unit calculates the transmissibility based on data output from the strain sensor, the data having a linear gradient representing a change in the output value of the strain sensor relative to a change in temperature of the railway rail. Object condition analysis system.

6. 2. The object state analysis system according to claim 1, the sensor unit includes a semiconductor chip including the strain sensor and the temperature sensor, and a metal plate joined to the semiconductor chip; The metal plate is adhered to the railroad rail with the adhesive. Object condition analysis system.

7. In the object state analysis system according to any one of claims 1 to 6, The corrected output value of the strain sensor represents the axial force in the stationary section of the railway rail. Object condition analysis system.

8. A processor comprising: a sensor unit that is attached to a railway rail as an object using an adhesive and includes a strain sensor and a temperature sensor, and calculates a gradient obtained by dividing the output value of the strain sensor by the temperature of the railway rail, and dividing the gradient by the thermal expansion coefficient of the railway rail, as a transmission rate that indicates the proportion of the magnitude of strain in the railway rail that is transmitted to the strain sensor; and calculates the output value of the strain sensor when the railway rail is fixed to a sleeper as an offset of the output value of the strain sensor. correcting the output value of the strain sensor by subtracting the offset from the output value of the strain sensor and dividing the resultant value by the transmissibility; Method for analyzing object condition.

9. Computer, a calculation unit that is attached to a railway rail as an object using an adhesive, and that calculates, based on data output from a sensor unit including a strain sensor and a temperature sensor, a gradient expressed by dividing the output value of the strain sensor by the temperature of the railway rail, and then divides the gradient by the thermal expansion coefficient of the railway rail to obtain a transmissibility indicating the proportion of the magnitude of strain in the railway rail that is transmitted to the strain sensor; and that calculates the output value of the strain sensor when the railway rail is fixed to a sleeper as an offset of the output value of the strain sensor; and a correction unit that corrects the output value of the strain sensor by dividing a value obtained by subtracting the offset from the output value of the strain sensor by the transmissibility; A program to function as a

Images