JP3576354B2 - Inspection method for induction hardened parts - Google Patents

Description

[0001]
TECHNICAL FIELD OF THE INVENTION
The present invention relates to an inspection method for induction hardened parts.
[0002]
[Prior art]
In order to partially increase the hardness of the work, there is a step of partially quenching by high-frequency heating. In the quenching step, for example, as shown in FIG. 3A, an annular quenching coil (2) is externally fitted to an axial work (1), and a predetermined rotation is applied to the coil (2) while rotating the work (1). After applying a quenching voltage and current for a predetermined time and quenching and heating by high-frequency induction heating, the work (1) is rapidly cooled with a predetermined temperature and amount of cooling water. Examples of the work include a work having a bent portion, for example, a crankshaft, in addition to the shaft-like work (1).
[0003]
At this time, the quenching quality is affected by the heating conditions of the quenching voltage, current and time, and the cooling conditions of the cooling temperature and amount, and the heated surface (1a) of the work (1) is determined in accordance with each of these conditions. It changes color. For example, during quenching and heating, the workpiece heated surface (1a) glows red as shown in FIG. 3A, and after quenching and cooling, the same heated surface (1a) as shown in FIG. 3B. Turns blackish. Therefore, during quenching heating and after quenching and cooling, the worker visually checks the discoloration state of the appearance of the workpiece heated surface (1a) to check the quenching condition.
[0004]
[Problems to be solved by the invention]
According to the above-mentioned inspection means for induction hardened parts, since the operator visually checks the discoloration of the work appearance during quenching heating and after quenching and cooling, the inspection result varies depending on the operator, or is overlooked. There is a problem that occurs.
[0005]
SUMMARY OF THE INVENTION An object of the present invention is to provide an inspection method for an induction hardened part, which automates an inspection process of the induction hardened part by fuzzy inference, prevents variation and oversight of the inspection by an operator, and saves labor.
[0006]
[Means for Solving the Problems]
The present invention provides a process for inspecting a work hardened by high-frequency heating, in which the surface of the work being hardened and heated is imaged to detect the brightness of the work surface under heating conditions of a predetermined hardening voltage, current and time. A step of imaging the surface of the work cooled by the cooling liquid later to detect the density of the work surface at the above-mentioned heating conditions and a predetermined cooling temperature and liquid amount; and a work surface at each time during the entire heating time during the quenching heating. Inspection of high-frequency quenched work by judging the degree of coincidence of lightness data on lightness of light and lightness data on lightness at each position over the entire circumference of the work surface after quenching and cooling with reference data by fuzzy inference and comprehensively judging each degree of coincidence And the step of performing
BEST MODE FOR CARRYING OUT THE INVENTION
An embodiment of an inspection method for an induction hardened component according to the present invention will be described below with reference to FIGS. 1 (a) to 1 (d) and FIGS. 2 (a) and 2 (b). First, as shown in FIG. 1 (a), after a work (4) is inserted into a hardening coil (3), a predetermined hardening voltage (V) and a current (I) are applied to the hardening coil (3) for a predetermined time (t). The workpiece (4) is quenched and heated by applying the voltage. Then, when the work (4) during quenching and heating is imaged by a camera (5) from a predetermined direction, for example, from above, as shown in FIG. 1B, the work surface at a predetermined hardening voltage (Va) and a current (Ia) is obtained. An analog measurement data curve (Da) showing the temporal change of the brightness (F) is drawn.
[0008]
Therefore, the measurement data curve (Da) is image-processed and divided into predetermined time coordinates (ta) (tb)..., And the analog measurement data curve (Da) is digitized. Then, the degree of coincidence (Ua) (Ub)... Between the lightness (Fa) (Fb)... And the reference lightness (Fra) (Frb) at each time coordinate (ta) (tb). Further, the quality (F) is determined by fuzzy determination over all time coordinates (ta) (tb).
[0009]
At that time, the determination is made by the determination means based on the probability. For example, as shown in FIG. 2A, a membership function (M) of a fuzzy set of lightness (F) at a predetermined voltage (Va), current (Ia) and time (t) during quenching heating, where (M) ZRa) sets reference data, (PSa) (NSa) each fuzzy set の of outlier data, and determination probability (D) for each time coordinate (ta) (tb). Therefore, for example, the respective fitness levels (Aa) and (Ba) with respect to the reference data and the shift data of the brightness (Fa) at time (ta) are detected. Then, as the fitness (Aa) is larger and the fitness (Ba) is smaller, the reference data is closer to the reference data. Therefore, these are compared with the determination probability (Da). For example, when Aa>Da> Ba, the time coordinate is calculated. The lightness (Fa) at (ta) is determined to be normal, and the determination operation is performed for all time coordinates (ta) (tb). From the results of all the determinations, the quality (F) of the lightness (F) is determined based on, for example, the number of times of normal determination or the multiplied value of the total fitness, and the quality of the quenching heating state is also determined. Further, the same determination is made based on other quenching voltage (V) and current (I), and the optimum heating condition can be selected.
[0010]
Further, the work (4) after quenching and heating is cooled with a predetermined cooling temperature and a predetermined amount of cooling water, and then the work (4) is entirely surrounded from the side. For example, as shown in FIG. 1 (c), three cameras (6), (7) and (8) surround the entire periphery of the work (4) from the side with the illustrated dotted line as a visual field boundary for each camera. Therefore, when the work-side surface is imaged from all directions, as shown in FIG. 1D, the spatial variation of the work surface density (L) under a predetermined heating condition, cooling temperature (及 び a), and quantity (Qa) is obtained. , An analog measurement data curve (Db) is drawn. Note that (Ea), (Eb), and (Ec) indicate the fields of view by the cameras (6), (7), and (8), respectively, and the three fields of view (Ea), (Eb), and (Ec) cover the entire field of view. Alternatively, the number of cameras may be increased to four, five, or the like to cover the entire field of view with four or more visual fields.
[0011]
Therefore, the measurement data curve (Db) is image-processed and divided into predetermined visual field coordinates (Xa), (Xb)..., And the analog measurement data curve (Db) is digitized. Then, the degree of coincidence (Va) (Vb)... Between the shades (La) (Lb)... And the reference shades (Lra) (Lrb)... At each view coordinate (Xa) (Xb). . Further, the quality of the shading (L) is determined by fuzzy determination over the entire visual field coordinates (Xa) (Xb).
[0012]
At that time, the determination is made by the determination means based on the probability. For example, as shown in FIG. 2 (b), predetermined heating conditions (voltage, current, time) at the time of quenching heating, and the density (L) after quenching and cooling at a predetermined cooling temperature (Θa) and an amount (Qa) are determined. Fuzzy set membership function (N) {where (ZRb) is reference data, (PSb) (NSb) each fuzzy set of outliers}, and determination probability (G) is set for each view coordinate (Xa) ... I do. Therefore, for example, the degree of conformity (Ab) and (Bb) with respect to the reference data and the shift data of the shading (La) in the visual field coordinates (Xa) are detected. Then, as the fitness (Ab) is larger and the fitness (Bb) is smaller, the data becomes closer to the reference data. Therefore, they are compared with the judgment probability (Ga). For example, when Ab>Ga> Bb, the field of view coordinates The density (La) in (Xa) is determined to be normal, and the determination operation is performed for all visual field coordinates (Xa) (Xb). From the results of all the determinations, for example, the quality of the shading (L) is determined based on, for example, the number of normal determinations or the multiplied value of the overall fitness, and the quality of the quenching quality is also determined. Further, the same judgment is made based on other heating and cooling conditions, and the optimum heating and cooling conditions can be selected.
[0013]
Further, the degree of hardening is comprehensively determined from the determination results of the lightness (F) and the shading (L). Note that the greater the number of divisions of time and field coordinates, the higher the accuracy of determination.
[0014]
【The invention's effect】
According to the present invention, when inspecting an induction hardened part, the brightness of the part surface during quenching heating and the density of the part surface after quenching and cooling were measured, and the degree of coincidence with reference data was determined and inspected by fuzzy inference. Thus, the inspection process of the induction hardened parts is automated, and labor is saved, and the inspection can be prevented from being uneven or overlooked by the operator, and the inspection accuracy is greatly improved.
[Brief description of the drawings]
FIG. 1A is a side sectional view showing a workpiece during induction hardening and heating and an imaging camera thereof. 2B is a graph illustrating a temporal change in the brightness of the workpiece imaged by the camera in FIG. (C) is a top view showing the imaging camera of the workpiece after quenching and cooling. FIG. 2D is a graph showing a spatial change in the density of the work imaged by the camera of FIG.
FIG. 2 (a) is a membership function of the brightness of a workpiece during quenching and heating. (B) is a membership function of the density of the work after quenching and cooling.
FIG. 3A is a perspective view of a workpiece and a quenching coil during induction hardening and heating. (B) is a side view showing the work after quenching and cooling.
[Explanation of symbols]
4 Work F Lightness L Shading

Claims (1)

In inspecting a workpiece quenched by high-frequency heating, a step of imaging the surface of the workpiece during quenching and heating, and detecting the brightness of the workpiece surface under heating conditions of a predetermined quenching voltage, current and time, and using a coolant after quenching and heating. A step of imaging the surface of the cooled work to detect the density of the work surface at the above-mentioned heating conditions and the predetermined cooling temperature and liquid amount; and a lightness relating to the lightness of the work surface at each time during the entire heating time during the quenching heating. determine the fuzzy inference the degree of coincidence with respect to the reference data of the shading degree data about shading degree at each position across the workpiece surface the entire circumference after the data and quenching cooling, and a step of inspecting the induction hardening work by comprehensively determining the degree of matching Inspection method of induction hardened parts characterized by including.

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