JP2013228441A - Abrasion estimation device of photoreceptor and abrasion estimation program of photoreceptor - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an abrasion estimation device of a photoreceptor and an abrasion estimation program of the photoreceptor that can estimate abrasion of the photoreceptor by use of a different material system in consideration to a mechanical configuration such as a cleaning blade and the like.SOLUTION: When the photoreceptor is put into friction with a cleaning blade, an index value acquisition part 22 calculates a cross-sectional area of a region of the photoreceptor in which stress exceeding yield stress to be calculated by the following primary expression (1) occurs as an index value, yield stress=a×elastic deformation rate of the photoreceptor+b (1) where a and b are coefficients determined by a preliminary performed test. An estimation part 24 estimates, on the basis of the index value, an abrasion velocity while the photoreceptor comes into contact with another object in friction, from a relation of the index value between the abrasion velocity of the photoreceptor obtained on the basis of the test determining a and b.

Description

  The present invention relates to a photoreceptor wear prediction apparatus and a photoreceptor wear prediction program.

  Patent Document 1 describes a photoconductor that uses a polyarylate resin having a higher ratio of terephthalic acid as a binder resin and has excellent mechanical properties.

  Further, Non-Patent Document 1 finds that there is a correlation between the amount of film slip (amount of wear) of the charge transport layer of the photoreceptor and the elastic power, and the elastic power is optimized for the resin material structure and blending ratio. It is described as an index.

JP 2001-312077 A

Sharp Technical Report No. 97, May 2008

  SUMMARY OF THE INVENTION An object of the present invention is to provide a photoconductor wear prediction apparatus and a photoconductor wear prediction program capable of predicting photoconductor wear using different material systems in consideration of a mechanical configuration such as a cleaning blade.

In order to achieve the above object, the invention of the photoconductor wear prediction apparatus according to claim 1 is that when the photoconductor is rubbed with another object, a stress exceeding the yield stress calculated by the following linear expression (1) is applied. Index value acquisition means for obtaining the cross-sectional area of the area of the photoconductor as an index value;
Yield stress = a × elastic deformation rate of photoconductor + b (1)
Here, a and b are based on the coefficient determined by an experiment performed in advance, and based on the relationship between the index value and the wear rate of the photoconductor obtained based on the experiment determining a and b. And a predicting means for predicting a wear rate when the photoconductor contacts with other objects while rubbing against each other.

  According to a second aspect of the present invention, in the first aspect of the invention, the a and b are constant regardless of the material of the photoconductor.

According to the invention of the photoconductor wear prediction program according to the third aspect, when the photoconductor is rubbed with another object, a stress exceeding the yield stress calculated by the following linear expression (1) is generated. Index value acquisition means for determining the cross-sectional area of the area of the photoreceptor as an index value;
Yield stress = a × elastic deformation rate of photoconductor + b (1)
Here, a and b are based on the coefficient determined by an experiment performed in advance, and based on the relationship between the index value and the wear rate of the photoconductor obtained based on the experiment determining a and b. The photosensitive member functions as a predicting means for predicting the wear rate when the photosensitive member comes into contact with another object while rubbing against it.

  According to the first aspect of the present invention, it is possible to predict the wear of the photosensitive member using different material systems while taking into consideration the mechanical configuration of the cleaning blade or the like.

  According to the invention of claim 2, it is possible to calculate the yield stress uniformly even with different materials.

  According to the third aspect of the present invention, it is possible to provide a program capable of predicting the wear of the photosensitive member using different material systems while taking into consideration the mechanical configuration of the cleaning blade or the like.

It is a figure which shows the structural example of the photoreceptor drum and the cleaning blade which are the prediction objects of the abrasion prediction apparatus concerning embodiment. FIG. 5 is a partial cross-sectional view illustrating a state where an external additive is sandwiched between the surface of the photosensitive drum and the cleaning blade in the nip portion according to the embodiment. It is a functional block diagram of the example of composition of the wear prediction device concerning an embodiment. In an embodiment, it is a figure showing an example of relation between nip pressure and index value which a nip pressure-index value relation acquisition part related about one material. It is a figure which shows the example of the relationship between the abrasion rate of a photoconductor and the index value which the abrasion rate-index value relationship acquisition part concerning embodiment concerns. It is a flowchart of the operation example of the abrasion prediction apparatus concerning embodiment. It is a flowchart of the other operation example of the abrasion prediction apparatus concerning embodiment. It is explanatory drawing of the parameter input into a structural analysis program.

  Hereinafter, modes for carrying out the present invention (hereinafter referred to as embodiments) will be described with reference to the drawings.

  FIG. 1 shows a configuration example of a photosensitive drum and a cleaning blade which are prediction targets of the wear prediction apparatus according to the embodiment. In FIG. 1, a cleaning blade 102 is rubbed against the photosensitive drum 100, and the cleaning blade 102 is applied to the surface of the photosensitive drum 100 with a constant pressure for cleaning the surface of the photosensitive drum 100. It is pressed. Hereinafter, a region where the photosensitive drum 100 and the cleaning blade 102 are in contact is referred to as a nip portion 104. In general, an external additive for cleaning the surface of the photosensitive drum 100 is also used. The photosensitive drum 100 rotates in the direction of arrow R in the figure.

  FIG. 2 is a partial cross-sectional view showing a state where the external additive 106 is sandwiched between the surface of the photosensitive drum 100 and the cleaning blade 102 in the nip portion 104. In FIG. 2, when the external additive 106 is sandwiched between the surface of the photoconductor 108 constituting the photoconductor drum 100 and the cleaning blade 102, the cleaning blade 102 side is largely deformed and the photoconductor constituting the photoconductor drum 100. The pressure from the cleaning blade 102 acts on the surface of the body 108 via the external additive 106.

  The wear prediction apparatus according to the present embodiment obtains a stress generated on the surface of the photoconductor 108 constituting the photoconductor drum 100 by the pressure from the cleaning blade 102, and uses an index value described later on the surface of the photoconductor 108. Predict the amount of wear.

  FIG. 3 shows a functional block diagram of a configuration example of the wear prediction apparatus according to the present embodiment. 3, the wear prediction apparatus includes a nip pressure calculation unit 10, a stress calculation unit 12, a yield stress setting unit 14, an index value calculation unit 16, a nip pressure-index value relationship acquisition unit 18, and a wear rate-index value relationship acquisition unit. 20, an index value acquisition unit 22, a prediction unit 24, and a storage unit 26.

  The wear prediction device includes a CPU, a ROM, a RAM, a nonvolatile memory, an I / O, and the like, and is configured as a computer that performs various calculations.

  The nip pressure calculator 10 calculates an average value of pressure acting on the surface of the photoconductor 108 from the cleaning blade 102 when the photoconductor drum 100 is rotating in the nip 104 shown in FIG. Pressure) is calculated by a method of dynamic analysis (structural analysis). Specifically, the following numerical values are given as parameters, and the nip pressure is calculated using a commercially available structural analysis program. FIG. 8 is an explanatory diagram of parameters input to the structural analysis program.

(1) Shape parameter (a) The thickness of the photosensitive layer constituting the photosensitive drum 100 and the thickness of each material (the back layer rubber 110 and the surface layer rubber 112) constituting the cleaning blade 102.
(B) FL (Free Length): a length obtained by subtracting the length of the fixing portion 114 from the length of the cleaning blade 102.
(C) Length of the cleaning blade 102

(2) Operation parameters of the apparatus (d) Biting amount: the length by which the tip of the cleaning blade 102 (the pressing portion against the photosensitive drum 100) is displaced in the y direction in FIG.
(E) BSA (Blade set angle): Installation angle of the cleaning blade 102 (f) Blade offset: The length by which the tip of the cleaning blade 102 is displaced in the x direction of FIG.
(G) Process speed: The speed of the surface of the photosensitive drum 100.
(H) Diameter of the photosensitive drum 100

(3) Physical properties (i) Young's modulus, Poisson's ratio, density, rebound resilience of each material constituting the photoreceptor and the cleaning blade 102 constituting the photoreceptor drum 100.
(J) Friction coefficient between the photoreceptor and the surface layer rubber 112.

  A plurality of pressures that the cleaning blade 102 presses the surface of the photosensitive drum 100 are set within the design range of the photosensitive drum 100, and a nip pressure is calculated for each pressure. The set pressure value is input from an appropriate input device and stored in the storage unit 26, and this value is read by the nip pressure calculation unit 10 and used for the calculation of the nip pressure.

  Based on the nip pressure calculated by the nip pressure calculation unit 10, the stress calculation unit 12 determines the stress generated on the surface and inside of the photoconductor 108 when the external additive 106 is interposed in the nip 104. Based on the Young's modulus and the friction coefficient, it is calculated by static analysis (analysis assuming that the photosensitive drum 100 is stationary). The range in which this stress occurs is shown as a region P in the cross section of the photoconductor 108 in FIG. The stress calculation unit 12 calculates the stress for each of the plurality of nip pressures based on the Young's modulus and the friction coefficient for a plurality of different materials used for the photoconductor 108. The Young's modulus and friction coefficient data are stored in the storage unit 26 in advance, and the stress calculation unit 12 reads out these data and uses them for the calculation of stress.

  The yield stress setting unit 14 sets the yield stress of the photoconductor 108 provided on the photoconductor drum 100 as a temporary value by a linear expression of the elastic deformation rate of the material constituting the photoconductor 108. The primary formula (1) is shown below.

Yield stress = a × elastic deformation rate of photoconductor + b (1)
Here, a and b are real-valued coefficients, which are first set as temporary values, and appropriate values are determined by simulation processing described later.

  The yield stress setting unit 14 also sets the yield stress for each of the plurality of different nip pressures based on the respective elastic deformation rates for a plurality of different materials used for the photoreceptor 108. In this case, the values of a and b are set to constant values. Note that the elastic deformation rate data of the material is stored in the storage unit 26 in advance, and the yield stress setting unit 14 reads out these data and uses them for setting the yield stress. Also, temporarily set values of a and b are stored in the storage unit 26.

  The index value calculation unit 16 calculates the area (cross-sectional area) of the region where the stress generated in the region P calculated by the stress calculation unit 12 exceeds the yield stress set by the yield stress setting unit 14 by using the plurality of nip pressures and the plurality of nip pressures. It is calculated as an index value for each material. The area calculation method may be performed by a conventionally known method, and is not particularly limited.

  The nip pressure-index value relationship acquisition unit 18 obtains the nip pressure calculated by the nip pressure calculation unit 10 and the yield stress set by the yield stress setting unit 14 based on the stress generated in the region P calculated by the stress calculation unit 12 as an index value. Is related to the area of the region exceeding. In this case, a plurality of nip pressures are calculated, and a plurality of index values are also calculated for each of the plurality of nip pressures and the plurality of materials. Correlate with pressure. Data regarding the relationship between the nip pressure and the index value is stored in the storage unit 26.

FIG. 4 shows an example of the relationship between the nip pressure and the index value related by the nip pressure-index value relationship acquisition unit 18 for one material. In FIG. 4, the horizontal axis is the nip pressure (average pressure in nip MPa), and the vertical axis is the area (μm ² ) of the region where the stress generated in the region P whose index value is above the yield stress.

  The wear rate-index value relationship acquisition unit 20 associates the wear rate of the photoconductor 108 with the index value. In this case, the wear rate is measured every time the photoconductor drum 100 rotates 1000 times, measured with a constant nip pressure for a plurality of different materials used for the photoconductor 108 whose stress is calculated by the stress calculation unit 12. This is a decrease in the thickness of the body 108 (nm / kilocycle). As the nip pressure, a design value of the photosensitive drum 100 is used. In addition, the index value is determined based on the constant nip pressure and the relationship illustrated in FIG. 4 created for each material of the photoconductor 108. Data on the relationship between the wear rate and the index value is stored in the storage unit 26.

FIG. 5 shows an example of the relationship between the wear rate of the photoconductor 108 and the index value related by the wear rate-index value relationship acquisition unit 20. In FIG. 5, the horizontal axis is the index value (μm ² ), and the vertical axis is the wear rate (nm / kilocycle). Even if the nip pressure is constant, if the material of the photoconductor 108 is different, the Young's modulus, the friction coefficient, and the elastic deformation rate are different, so that the stress generated in the index value region P exceeds the yield stress. The area value varies depending on the material.

The wear rate in FIG. 5 was measured as follows. Note that the following actual measurement conditions of the wear rate are examples, and the present embodiment is not limited to the following actual measurement examples.
・ Device used: Docucentre IIC7500 (Tarzan) manufactured by Fuji Xerox Co., Ltd.
-Photoconductor drum diameter 60 mm, charge transport layer 2 μm, overcoat layer 7 μm
・ Cleaning blade Docucentre IIC7500 (Tarzan) double-layer blade (details are shown in Table 1)
Nip pressure: Pressure when the amount of biting explained in FIG. 8 is 1.2 mm.
- experimental conditions the temperature in the apparatus 28 ° C., 85% humidity photosensitive drum rotation speed 100 km rotation ⁽¹⁰⁵ rotation)
-Photoconductor film thickness measurement The same spot was measured with an interference film thickness meter (ST2000-DLXn, manufactured by K-MAC) before and after rotating the photosensitive drum. The measurement points were 132 points of 33 points in the axial direction of the photosensitive drum × 4 points in the circumferential direction, and the average of the measured values was the film thickness of the photoconductor.

なお、表１におけるＦＬ及びＢＳＡは、図８で説明した構造解析プログラムに入力するパラメータと同じである。

Note that FL and BSA in Table 1 are the same as the parameters input to the structural analysis program described in FIG.

  The actual measurement was performed on 11 types of materials (m1 to m11) used as the material of the photoreceptor.

  The wear rate-index value relationship acquiring unit 20 causes the yield stress setting unit 14 to reset the yield stress by changing the coefficients a and b of the formula (1) at predetermined intervals, and this reset yield stress. Based on the above, the index value calculation unit 16 and the nip pressure-index value relationship acquisition unit 18 are recalculated to reacquire the index value for each photosensitive material at the nip pressure used in the experiment. On the other hand, since the wear rate of the photoconductor is obtained as the experimental value, the wear rate-index value relationship acquisition unit 20 re-acquires the relationship between the wear rate of the photoconductor 108 and the index value. The wear rate-index value relationship acquisition unit 20 repeats such processing to determine coefficients a and b that give the highest correlation between the wear rate and the index value. The straight line illustrated in FIG. 5 indicates the value obtained by the least square method from each point when the correlation coefficient of the relationship between the wear rate and the index value is 0.86.

  The coefficients a and b finally determined by the wear rate-index value relationship acquisition unit 20 by repeating the above-described processing are values that give the highest correlation coefficient between the index value and the wear rate for each photosensitive material. Therefore, it can be applied to the material, and as a result, the value is constant regardless of the material.

  Next, the index value acquisition unit 22 is given a certain value as the pressure with which the cleaning blade 102 presses the surface of the photosensitive drum 100, and gives Young's modulus, friction coefficient, and elastic deformation rate as material data of the photosensitive member 108. Then, the index value is acquired from the relationship illustrated in FIG. In the present embodiment, the material of the photoconductor 108 handled by the index value acquisition unit 22 is the nip pressure-index value relationship acquisition unit 18 acquires the relationship between the nip pressure and the index value, and the wear rate-index value relationship acquisition unit 20. Is a material that has acquired the relationship between the wear rate and the index value.

  Based on the index value acquired by the index value acquisition unit 22, the prediction unit 24 predicts the wear rate of the photoreceptor 108 given using the straight line illustrated in FIG.

  The storage unit 26 is necessary for the above processes such as data such as Young's modulus, friction coefficient, and elastic deformation rate of the photosensitive member, CPU operation program, etc. in a nonvolatile memory such as a hard disk device or a solid state drive (SSD). Memorize information.

  FIG. 6 shows a flowchart of an operation example of the wear prediction apparatus according to the present embodiment. FIG. 6 is an example of processing for acquiring the relationship between the wear rate of the photoconductor 108 and the index value.

  In FIG. 6, the nip pressure calculation unit 10 rotates the photosensitive drum 100 when the cleaning blade 102 applies pressure to press the surface of the photosensitive drum 100 in the nip portion 104 shown in FIG. 1. The nip pressure acting on the surface of the photosensitive member 108 from the cleaning blade 102 is calculated (S1). A plurality of nip pressures are calculated for a plurality of pressures at which the cleaning blade 102 presses the surface of the photosensitive drum 100.

  Next, based on the nip pressure calculated by the nip pressure calculation unit 10, the stress calculation unit 12 statically analyzes the stress generated on the surface and inside of the photoconductor 108 when the external additive 106 is interposed in the nip 104. (S2). For each of the plurality of nip pressures calculated in S1, a plurality of stresses are calculated based on the respective Young's moduli and friction coefficients for a plurality of different materials used for the photoconductor.

  Further, the yield stress setting unit 14 uses the elastic deformation rate and the coefficients a and b of the material constituting the photoconductor 108 as a temporary value according to the above-described primary expression (1), using the yield stress of the photoconductor 108. Set (S3).

  The index value calculation unit 16 calculates the area (cross-sectional area) of the region where the stress generated in the region P of the cross section of the photoconductor 108 calculated by the stress calculation unit 12 in S2 exceeds the yield stress set by the yield stress setting unit 14 in S3. ) Is calculated as an index value for each of the plurality of nip pressures and the plurality of materials (S4).

  The nip pressure-index value relationship acquisition unit 18 associates the nip pressure calculated by the nip pressure calculation unit 10 in S1 with the index value calculated by the stress calculation unit 12 in S4 (S5). Thereby, the relationship illustrated in FIG. 4 is acquired.

  The wear rate-index value relationship acquisition unit 20 associates the experimentally determined wear rate of the photoreceptor 108 with the index value (S6). The wear rate is measured with a constant nip pressure for a plurality of different materials used for the photoreceptor 108. Further, the index value is determined based on the relationship between the nip pressure and the index value for each material of the photoconductor 108 illustrated in FIG. 4 from the nip pressure used for the measurement of the wear rate.

  Next, the wear rate-index value relationship acquisition unit 20 determines whether or not the correlation coefficient of the relationship between the wear rate and the index value acquired in S6 is equal to or greater than a predetermined threshold (S7).

  In S7, when the correlation coefficient is not equal to or greater than the threshold value (smaller than the threshold value), the yield stress setting unit 14 changes the coefficients a and b used in S3 in predetermined increments. Repeat steps.

  In S7, when the correlation coefficient is equal to or greater than the threshold value, the wear rate-index value relationship acquisition unit 20 displays data indicating the relationship between the wear rate and the index value at the output destination of the storage unit 26 or the like. Is output (S8). At this time, it is preferable to output the relationship between the wear rate and the index value as linear data illustrated in FIG.

  FIG. 7 shows a flowchart of another operation example of the wear prediction apparatus according to the present embodiment. FIG. 7 shows the wear rate when a certain value is given as the pressure with which the cleaning blade 102 presses the surface of the photoconductor drum 100, and the material of the photoconductor 108 is given from among the materials handled in FIG. It is an example of the process to predict.

  In FIG. 7, the index value acquisition unit 22 calculates the nip pressure based on the pressure with which the cleaning blade 102 presses the surface of the photosensitive drum 100, and is obtained using the above-described linear expression (1) and the like. An index value is acquired from the relationship exemplified in 4 (S11).

  Next, the prediction unit 24 predicts the wear rate of the photoreceptor 108 given using the straight line illustrated in FIG. 5 based on the index value acquired by the index value acquisition unit 22. The predicted wear rate is output to the storage unit 26 and other appropriate devices (S12).

  The above-described program for executing the steps of FIGS. 6 and 7 can be stored in a recording medium, and the program may be provided by communication means. In that case, for example, the above-described program may be regarded as an invention of a “computer-readable recording medium recording a program” or an invention of a “data signal”.

  DESCRIPTION OF SYMBOLS 10 Nip pressure calculation part, 12 Stress calculation part, 14 Yield stress setting part, 16 Index value calculation part, 18 Nip pressure-index value relationship acquisition part, 20 Wear rate-index value relationship acquisition part, 22 Index value acquisition part, 24 Prediction unit, 26 storage unit, 100 photoconductor drum, 102 cleaning blade, 104 nip unit, 106 external additive, 108 photoconductor, 110 back layer rubber, 112 surface layer rubber, 114 fixing unit.

Claims (3)

Index value acquisition means for obtaining, as an index value, a cross-sectional area of a region of the photoconductor in which a stress exceeding the yield stress calculated by the following linear expression (1) is generated when the photoconductor is rubbed with another object;
Yield stress = a × elastic deformation rate of photoconductor + b (1)
Here, a and b are coefficients determined by an experiment performed in advance. Based on the index value, obtained based on the experiment in which a and b are determined, the relationship between the index value and the wear rate of the photoconductor. Predicting means for predicting the wear rate when the photoconductor comes in contact with other objects while rubbing against each other;
An apparatus for predicting wear of a photoreceptor, comprising:   2. The photoconductor wear prediction apparatus according to claim 1, wherein a and b are constant regardless of the material of the photoconductor. Computer
Index value obtaining means for obtaining, as an index value, a cross-sectional area of a region of the photoconductor in which a stress exceeding the yield stress calculated by the following linear expression (1) is generated when the photoconductor rubs against another object;
Yield stress = a × elastic deformation rate of photoconductor + b (1)
Here, a and b are coefficients determined by an experiment performed in advance. Based on the index value, obtained based on the experiment in which a and b are determined, the relationship between the index value and the wear rate of the photoconductor. , A predicting means for predicting the wear rate when the photoconductor comes in contact with another object while rubbing against it,
A program for predicting wear of a photoreceptor, characterized in that

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