Comprehensive evaluation of the fabric crease recovery property by the whole recovery process

Abstract

Current standard methods specify the recovery angle of a folded wrinkle in a controlled recovery period as the evaluation standard for the fabric crease recovery property. Nevertheless, there are limitations in the characterization of the whole recovery process by using the single recovery angle. We proposed a whole-process test method and comprehensive evaluation method for assessing the fabric crease recovery property. Firstly, a specimen was tested on the automatic fabric crease recovery testing device to obtain the “time-recovery angle” data. Then, the “time-average recovery angle” data was calculated by the recovery angle at the corresponding moment in the recovery period from repeated testing. The “time-average recovery angle” data was fitted into power function equation f(t) = at^b. Parameter a reflects the degree of initial recovery. Parameter b reveals the speed degree at which the sample recovery reaches stable status. The K value, the ratio of a to b, could be calculated. Finally, the $\bar{K}$ value, the average of the K values of four folded ways, was used to evaluate the crease recovery property of the fabric. The experimental results demonstrate that the $\bar{K}$ values have positive correlation with the recovery angle of the fifth minute in the recovery period (r = 0.92). In addition, for fabrics with the similar recovery angle results obtained from the wrinkle recovery angle evaluation method, the proposed method could differentiate the property of the fabrics. Therefore, the evaluation method can accurately reflect the initial resilience and comprehensive crease recovery property of textile materials.

Keywords

crease recovery power function evaluation fabric

The crease or wrinkle recovery property of a fabric directly affects its appearance and performance. According to the standard methods, the property is mainly assessed by measuring the crease angle of recovery,¹ evaluating the smoothness appearance grade of fabric after cleansing² or assessing the smoothness rating of fabric wrinkled under a wrinkling device.³

Concerning the smoothness appearance assessment of fabrics treated under specified methods, surface analysis techniques have been studied by a number of researchers to replace the manual rating method and improve the accuracy and efficiency of evaluation. For example, Xu and Reed⁴ described the application of computer image analysis techniques to the characterization and quantification of fabric wrinkling for the purpose of devising an automated rating system of fabric wrinkle recovery. Amirbayat and Alagha⁵ applied laser scanning to the surface of the plates and extracted certain geometrical features to assess the wrinkle recovery of fabrics according to the grades of the replica plates supplied by the American Association of Textile Chemists and Colorists (AATCC). Xu et al.⁶ developed a new profilometer for assessing fabric smoothness appearance by using laser triangulation and image processing techniques. Wei and Yang⁷ developed linear regression models to investigate the relationship between the wrinkle recovery angle (WRA) and tensile strength of the treated cotton and the carbonyl band absorbance in the infrared spectra for predicting the performance of durable-press finished cotton fabrics. Kang et al.⁸ proposed a wavelet-fractal method to calculate the fractal dimension to objectively evaluate the surface roughness of fabric wrinkles, smoothness appearance and seam pucker. Zaouali et al.⁹ used image processing to extract four characteristics for objectively estimating the wrinkle grade of multidirectional realistic fabric wrinkling generated by the French method of “cylindre creux”.

Several fabric wrinkle resistance analytical methods, which are different from the standard methods, were reported to illustrate the fabric wrinkle recovery property from new perspectives. Fridrichova and Zelova¹⁰ proposed an objective method of multidirectional evaluation of creasing by angle recovery image processing. Zaouali et al.¹¹ showed that the energy modeling can be estimated by the ability of the fabric to recover to its initial state. Liu¹² proposed the measurement for fabric wrinkle-simulating actual wear, and established the equations of wrinkle density (WD) with WRAs. Abrishami et al.¹³ analyzed the evaluation of bending rigidity and crease recovery of fabrics in various directions and used an exponential function to express the non-linear relation between bending rigidity and the crease recovery in different directions of the fabric.

The researches about the fabric wrinkle recovery property evaluated by the recovery angle do not receive similar attention to that of the smoothness rating method. Nevertheless, because the crease recovery angle appears to be a reliable quantitative testing method,¹⁴ it has been widely used for assessing the property improvement of durable-press finished fabrics. The main standard methods based on the recovery angle are ISO 2313-1972,¹ AATCC 66-2014¹⁵ and GB/T 3819-1997.¹⁶ In these methods, samples with specified size were pressured under a hammer with the prescribed weight for 5 minutes, and freely recovered after the pressure was released. Then, the recovery angle of the fifth minute in the recovery period was measured to assess the fabric crease recovery property. At present, the test instruments for evaluating the fabric crease recovery property mainly include the “Shirley” crease recovery tester, the “SDL Atlas” crease recovery tester, the YG541 digital crease recovery tester, etc. However, the measurement and evaluation approaches have the following problems. (a) In the testing process, it is necessary to transfer the creased sample after being pressed from the loading device to a recovery angle measurement device for recording the test result. This procedure is particularly affected by manual operation or environmental factors and, as a result, the degree of automation is still low. (b) It is impossible to obtain the initial recovery status (within 5 or 10 seconds) when the pressure is released, as the sample needs to be transferred between pressing and testing procedures. (c) Only the recovery angle at the fifth minute is used as the index to assess the crease recovery property of fabrics, which causes the one-sided assessment of the evaluation and cannot fully reflect the recovery performance of the sample in the entire recovery process. For instance, two fabrics have the same recovery angle at the fifth minute in the recovery period. However, in the recovery process, the recovery angle of one of the fabrics rapidly rises to the angle at the fifth minute, while the recovery angle of the other fabric always gradually increases. Moreover, the existing method limits the establishment of an evaluation system for the crease recovery property.

In our previous study, a device for dynamic measurements of the fabric crease recovery angle was proposed.¹⁷ In view of the above-mentioned problems, we have conducted further investigation on the evaluation index establishment for the fabric crease recovery process, including improving the device, validating its feasibility and clarifying it as more reasonable and comprehensive than the WRA evaluation method. According to the physical properties of the dynamic process of fabric crease recovery, this paper provides a method for evaluating the crease recovery property of fabrics based on the power function equation. A sample is automatically folded to create a sharp crease and then unfolded by itself. The video image of the fabric in the crease recovery period is captured and processed to realize the measurement of the recovery angle of each frame image. In this approach, the data of the recovery angle varying with time can be obtained. In addition, the “time-average recovery angle” data are figured out from repeated tests. Then, the data is fitted to a power function equation by the means of data analysis technology. A new index is extracted based on the physical meaning of the equation coefficient for evaluating the crease recovery property of fabrics. Different types of fabrics were selected to conduct a contrastive test between the WRA evaluation method and the proposed method to prove the applicability of the assessment for the entire recovery process.

Methodology

Fabric crease recovery testing device

The fabric crease recovery device (see Figure 1) for testing the crease recovery of fabrics consists of a numerical control (NC) interface system, a camera, a sample placement area, a pressing block and a pressurized cylinder.

Figure 1.

The fabric crease recovery device.

The NC interface system is connected with the pressurized cylinder and the camera, which can accurately adjust the pressurized time and pressure of the pressurized cylinder. The pressurized cylinder is connected with the pressing block. The pressing block is placed toward the sample placement area. The sample placement area realizes the function of fixing the sample. The pressurized cylinder controls the pressing block to move toward or away from the sample placement area. When the pressing block moves toward the sample placement area, it presses the folded sample for a certain period of time under constant pressure to create a crease on the sample. When the pressing block moves away from the sample placement area, the recovery angle formed by the fixed part and the free part of the sample gradually increases with the recovery of the crease. The camera is located right above the sample placement area. The camera captures video images of the sample crease recovery status and transmits the video information to the NC interface system for image processing and recovery angle calculation. The video frame rate, the size of each video image and the recording duration of the video capture are set as 1 frame/s, 1280 × 960 pixels and 5 minutes, respectively.

The NC interface system contains a video image processing module and an evaluation index extraction module. The video image processing module is applied to calculate the angle value of each video image frame. The main processing steps are video single frame image extraction, image binarization, morphological operation and recovery angle calculation.¹⁸ The evaluation index extraction module used the “time-average recovery angle” to fit into power function equation. The data of the “time-average recovery angle” were obtained from the average recovery angle at the corresponding time after repeated tests. Take the 1# fabric in the Experimental details section as an example, the fitting curve of the average recovery angle of warp face-to-face folded samples of the fabric is shown in Figure 2. It is obvious that the curve can achieve a better fitting effect. Then, the sub-item index of fabric crease recovery with different folding ways was calculated by the coefficients from the power function equation. Finally, the composite index of fabric crease recovery can be figured out by the average value of the sub-item indexes, that is, the index for evaluating the fabric crease recovery property. The detailed evaluation method is described in the next section.

Figure 2.

The fitting curve of the average recovery angle.

Fabric crease recovery evaluation

The evaluation index for the fabric crease recovery property was determined by the angle change in the recovery process. Firstly, three sets of “time-recovery angles” measured from the specimens in the same repeated test were used to calculate the average angle at the corresponding recovery time and the “time-average recovery angle” was obtained. For example, three samples in the warp direction were prepared to be face-to-face folded for a repeated test. The measured results were given as the recovery angle at the first second of sample 1, m₁, the recovery angle at the first second of sample 2, m₂, and the recovery angle at the first second of sample 3, m₃. The average value of the recovery angle at the first second of the samples is

{\bar{m}}_{1} = (m_{1} + m_{2} + m_{3}) / 3

(1)

Similarly, the average recovery angle at t time is ${\bar{m}}_{t}$ . Thus, the average recovery angle changes with the time of the samples, that is, the “time-average recovery angle” data can be obtained. For the samples folded in the same way in the repeated test, the average value of the standard deviation of the recovery angles at each moment is less than 3°.

Then, the “time-average recovery angle” data are fitted into the power function equation, written as in Equation (2), by using the non-linear curve fitting method

f (t) = {at}^{b}

(2)

In Equation (2), t represents the recovery time, f(t) represents the recovery angle and a and b are related to the fabric crease recovery property. The equation displays the relationship between the time and recovery angle. The fitting function of the non-linear curve is shown in Equation (3)

min_{t} ‖ f (t) - {\bar{m}}_{t} ‖ 2 2 = min_{t} \sum_{i} (f (i) - {\bar{m}}_{t}) 2

(3)

The initial values of a and b were determined by the empirical value according to the physical property of fabric wrinkle resistance. If the initial values of a and b are close to the fitting results, the number of iterations for calculating the parameters of the fitting equation can be shortened and the results can be obtained more quickly. Parameter a is concerned with the initial recovery degree. Considering that the initial recovery degree of general textile materials is between tens and hundreds of degrees, the initial value of a was set as 10. Parameter b reflects how fast the recovery angle reaches the stable status and its initial value was set as 0.1, as the empirical data are from 0 to 0.1. Thus, parameters a and b in Equation (2) could be calculated when the minimum binary expression of Equation (3) is valid.

Furthermore, parameter a is equal to the angle value of fabric crease recovery at the first unit time in the recovery period. The larger the value of a, the better the recovery property of the sample. Parameter b is equal to the ratio of the instantaneous recovery speed at the end of the first unit time in the recovery period to the angle value of fabric crease recovery at the first unit time. It is defined as the recovery index, which reflects the speed at which the sample recovers to a stable state. The smaller the value of b, the better the recovery property of the sample.

Next, an index K for assessing the crease recovery property of the corresponding folded sample was constructed by parameters a and b in Equation (2). The equation of index K is written as follows

K = a / b

(4)

In the light of Equation (4), the fitting equations of the samples tested by four folded ways, that is, warp face-to-face folded, warp back-to-back folded, weft face-to-face folded and weft back-to-back folded, were calculated to obtained the sub-indexes K₁, K₂, K₃ and K₄, respectively.

Finally, the average value of the sub-indexes was calculated to evaluate the crease recovery property of the fabric, as shown in Equation (5)

\bar{K} = (K_{1} + K_{2} + K_{3} + K_{4}) / 4

(5)

In Equation (5), $\bar{K}$ demonstrates the crease recovery property of the entire fabric and is called the comprehensive index of fabric crease recovery.

Experimental details

Material

In the experiment, 16 types of fabrics were selected as the test samples. Eleven of the fabrics were provided by Cotton Incorporated, which were standard samples of the AATCC for laboratory comparison tests of the recovery angle method. Three types of wool fabrics were made by Danyang Dansheng Textile Co., Ltd. Two types of flax fabrics were purchased from retailers. The first 10 fabrics were two kinds of gray cloth treated by different finishing methods. The specifications of the gray cloth are shown in Table 1. The pretreatment processing of the gray fabric is gray fabric preparation, singeing, desizing, scouring and bleaching. The gray cloth did not undergo finishing.

Table 1.

The gray cloth parameters

Gray cloth	Material	Weave	Yarn count/tex		Yarn density/(numbers·(10 cm)^–1)
Gray cloth	Material	Weave	Warp	Weft	Warp	Weft
A	100% Cotton	Plain	14.6	15.8	555	568
B	100% Cotton	3/1↖Twill	29.2	64.8	465	200

The above gray cloth was treated by four finishing processes, namely soft finishing, 6% resin finishing (with softener), 12% resin finishing (with softener) and 18% resin finishing (with softener). Including the fabric without finishing, there were in total 10 types of fabrics. The corresponding relationships between sample number and fabric are shown in Table 2.

Table 2.

List of Samples 1#–10#

Sample	Gray cloth	Finishing method
1#	A	No finishing
2#	A	Soft Finishing
3#	A	6% Resin finishing (with softener)
4#	A	12% Resin finishing (with softener)
5#	A	18% Resin finishing (with softener)
6#	B	No finishing
7#	B	Soft finishing
8#	B	6% Resin finishing (with softener)
9#	B	12% Resin finishing (with softener)
10#	B	18% Resin finishing (with softener)

The sample parameters of the remaining fabrics are listed in Table 3. Sample 11# is made of cotton and polyester blended yarn without finishing. Samples 12#–14# are 100% wool fabrics with durable-press resin finishing. The finishing process of wool fabrics is singeing, scouring, crabbing, dehydration, dyeing, drying, brushing, shearing and heat setting. The finishing process of Samples 15# and 16# is singeing, desizing, scouring, chlorine bleaching, oxygen bleaching and drying.

Table 3.

The parameters of Samples 11#–16#

Sample	Material	Weave	Yarn count/tex		Yarn density/(numbers·(10 cm)^–1)
Sample	Material	Weave	Warp	Weft	Warp	Weft
11#	50% Cotton/50% polyester	Plain	18.2	18.2	392	218
12#	100% Wool	Plain	16.2	16.2	306	283
13#	100% Wool	Plain	16.2	16.2	238	220
14#	100% Wool	Plain	18.2	18.2	186	181
15#	65% Cotton/35% flax	Plain	28.0	29.4	213	201
16#	100% Flax	Cord	14.8	19.7	338	322

The fabrics were placed in relative humidity (RH) of 65 ± 2% and temperature of 21 ± 1℃ for at least 24 hours before the testing.

Test procedures

For the method for evaluating crease recovery of fabrics based on the power function equation, the schematic diagram is shown in Figure 3. The testing and evaluating steps are as follows.

Figure 3.

Schematic diagram of the test procedures.

Step 1: cut 12 specimens of 40 mm × 15 mm for each fabric. Six specimens are aligned in the warp direction, and the remaining specimens in the weft direction.

Step 2: place a warp specimen on the sample placement area. One wing of a specimen is fixed on it, and the other wing of the specimen face-to-face bends and overlaps with the fixed wing.

Step 3: set the pressure and time on the NC interface system. Start the testing. The pressurized cylinder controls the pressing block to push toward the sample placement area, and presses the overlapping wing of the specimen. When the pressure time set by the NC interface system is reached, the pressurized cylinder controls the pressing block moving away from the sample placement area, so that the free wing of the specimen can freely recover. At the same time, the camera records the video image of the specimen crease recovery.

Step 4: the video image processing module in the NC interface system processes the fabric crease recovery video image and calculates the recovery angle of each frame in the video image. The result of the “time-recovery angle” of the specimen is obtained.

Step 5: repeat steps 2–4 to measure the other two specimens of the same fabric folded in the same way. Calculate the average recovery angle at the corresponding recovery time of the three specimens folded in the same way. Get the result of the “time-average recovery angle” data.

Step 6: the “time-average recovery angle” data are fitted into the power function equation by the evaluation index extraction module in the NC interface system. The sub-index of the warp face-to-face folded specimens K₁ is figured out by the parameters of the fitting equation.

Step 7: repeat steps 2–6 to test the specimens of the other ways of folding (warp back-to-back folded, weft face-to-face folded and weft back-to-back folded) and obtain the corresponding sub-indexes of the samples, that is, K₂, K₃ and K₄. As a result, the comprehensive index of fabric crease recovery $\bar{K}$ of the fabric can be found.

Results and discussion

The crease recovery angles at the fifth minute of the recovery period tested by the proposed method and the manual WRA method have high consistency. The difference is less than 2° between the two methods. The fitting curves of the average recovery angle of warp face-to-face folded samples with different materials (including Samples 6#, 11#, 13#–16#) are shown in Figure 4. The equation curves of the samples treated by different finishing methods (including Samples 1#–10#) are shown in Figure 5.

Figure 4.

The recovery angle fitting curve of the samples with different materials: (a) Sample 6#; (b) Sample 11#; (c) Sample 13#; (d) Sample 14#; (e) Sample 15#; (f) Sample 16#.

Figure 5.

The recovery angle fitting curve of the samples treated by different finishing methods: (a) Samples 1#–5#; (b) Samples 6#–10#.

From Figure 4, it is demonstrated that the fitting results of the pure cotton, polyester/cotton blended, pure wool, cotton/flax blended and pure flax fabrics are good. In Figure 5(a), the fabric crease recovery property of Samples 1#–5# shows a tendency to gradually improve. In addition, Samples 6#–10# is the same, as shown in Figure 5(b).

The detailed results of the test samples obtained by the proposed test and evaluation methods are listed in Table 4. Therein, parameters a and b are the constants in the power function fitting equation of the “time-average recovery angle.” R² is the resolvable coefficient of goodness-of-fit. K is the sub-item index of fabric crease recovery and

\bar{K}

is the composite index of fabric crease recovery. F_t and F_c are the measured angle by the video image and calculated angle by the fitting equation at the fifth minute of the recovery period, respectively. ∆ is the difference between F_t and F_c. F_jw is the evaluation index of the existing standard method, which is the sum of the warp and weft crease recovery angles. The codes of the four folding modes, I, II, III and IV, represent warp face-to-face folded, warp back-to-back folded, weft face-to-face folded and weft back-to-back folded, respectively.

Table 4.

Test results by the proposed method and the wrinkle recovery angle standard method

Sample	Folding mode	a	b	R ²	K	$\bar{K}$	F_t/°	F_c/°	$Δ F$ /°	F_jw/°
1#	I	46.8	0.0740	0.98	632.1	689.3	70.7	71.4	0.7	149.0
	II	46.5	0.0755	0.97	616.1		70.7	71.5	0.9
	III	51.2	0.0699	0.98	732.3		75.4	76.3	0.9
	IV	54.7	0.0704	0.99	776.5		81.1	81.7	0.6
2#	I	51.7	0.0759	0.97	680.8	850.3	78.7	79.7	0.9	173.0
	II	62.0	0.0622	0.98	995.6		87.3	88.4	1.1
	III	62.3	0.0694	0.99	898.4		91.7	92.6	0.8
	IV	59.4	0.0719	0.96	826.3		88.2	89.6	1.4
3#	I	92.5	0.0539	0.96	1718.1	1649.4	124.7	125.8	1.2	240.1
	II	91.0	0.0566	0.95	1608.3		124.3	125.6	1.3
	III	88.4	0.0521	0.97	1697.9		118.0	119.0	1.1
	IV	84.3	0.0536	0.96	1573.2		113.1	114.4	1.3
4#	I	97.6	0.0499	0.93	1956.1	2097.5	128.2	129.7	1.5	258.8
	II	102.6	0.0457	0.95	2246.3		131.9	133.1	1.2
	III	98.4	0.0479	0.97	2054.8		128.3	129.4	1.1
	IV	99.9	0.0469	0.95	2132.9		129.2	130.5	1.3
5#	I	109.1	0.0419	0.95	2601.2	2811.4	137.6	138.6	1.0	276.6
	II	113.7	0.0389	0.92	2923.9		140.7	141.9	1.2
	III	111.4	0.0391	0.95	2847.4		138.2	139.2	1.0
	IV	110.5	0.0385	0.94	2873.0		136.6	137.6	1.1
6#	I	35.0	0.0698	0.96	502.2	805.4	51.4	52.2	0.7	148.5
	II	53.1	0.0658	0.98	807.3		76.5	77.3	0.8
	III	66.3	0.0622	0.96	1066.0		93.4	94.6	1.2
	IV	53.6	0.0634	0.94	846.2		75.7	77.0	1.2
7#	I	36.2	0.1016	0.98	356.3	916.7	63.8	64.6	0.8	181.3
	II	70.2	0.0665	0.98	1054.4		101.6	102.6	1.0
	III	85.9	0.0575	0.91	1494.1		117.6	119.2	1.6
	IV	53.9	0.0707	0.96	761.9		79.6	80.7	1.1
8#	I	59.5	0.0762	0.95	780.7	1370.1	90.3	91.8	1.5	223.2
	II	89.9	0.0573	0.97	1568.7		123.3	124.6	1.3
	III	98.5	0.0516	0.97	1911.2		130.9	132.2	1.4
	IV	73.1	0.0599	0.95	1219.9		101.8	102.9	1.1
9#	I	84.8	0.0508	0.90	1669.3	1987.6	112.2	113.3	1.1	244.4
	II	99.3	0.0464	0.96	2140.1		128.0	129.3	1.3
	III	109.0	0.0420	0.96	2594.4		137.1	138.5	1.4
	IV	83.2	0.0538	0.95	1546.5		111.4	113.0	1.6
10#	I	93.3	0.0424	0.92	2199.9	3019.0	117.4	118.8	1.4	273.2
	II	121.3	0.0367	0.94	3300.7		148.2	149.5	1.4
	III	121.8	0.0380	0.97	3204.4		150.2	151.2	1.0
	IV	109.4	0.0325	0.95	3371.1		130.6	131.7	1.1
11#	I	98.5	0.0390	0.94	2527.5	2461.0	122.0	123.0	1.0	244.2
	II	101.7	0.0374	0.94	2722.2		125.1	125.9	0.8
	III	91.9	0.0437	0.96	2103.1		116.9	117.8	0.9
	IV	99.5	0.0400	0.96	2491.3		124.3	125.0	0.7
12#	I	147.6	0.0246	0.98	6009.4	6062.9	169.5	169.7	0.3	331.6
	II	139.6	0.0242	0.97	5769.7		159.8	160.3	0.5
	III	140.0	0.0249	0.97	5630.9		160.7	161.3	0.6
	IV	153.0	0.0224	0.97	6841.5		173.3	173.8	0.5
13#	I	152.0	0.0211	0.98	7220.9	6113.1	170.8	171.4	0.6	336.2
	II	149.7	0.0212	0.97	7053.3		168.3	169.0	0.7
	III	138.9	0.0300	0.98	4628.7		164.3	164.8	0.5
	IV	146.2	0.0263	0.96	5549.4		169.1	169.9	0.8
14#	I	151.3	0.0222	0.94	6824.0	7217.6	170.9	171.7	0.9	342.4
	II	147.4	0.0228	0.97	6478.2		166.9	167.8	0.9
	III	153.3	0.0208	0.98	7377.3		172.1	172.6	0.5
	IV	157.1	0.0192	0.96	8190.8		174.9	175.3	0.5
15#	I	49.0	0.0625	0.96	785.0	825.0	69.2	70.0	0.8	172.4
	II	34.7	0.0636	0.94	545.4		48.7	49.9	1.2
	III	55.8	0.0964	1.00	579.1		96.1	96.7	0.6
	IV	90.4	0.0650	0.99	1390.3		130.7	130.9	0.2
16#	I	31.1	0.1351	1.00	230.1	432.6	66.7	67.1	0.4	137.8
	II	40.7	0.1161	0.99	350.6		78.1	78.9	0.8
	III	40.1	0.1046	1.00	383.9		72.7	72.9	0.2
	IV	42.3	0.0553	0.94	765.9		58.0	58.0	0.0

From the data in Table 4, the following can be concluded.

The goodness-of-fit of the power function equation: the values of R² of the fitting equation are larger than 0.9, which shows that the “time-average recovery angle” equation has a high fitting accuracy. The values of $Δ F$ are less than 2°, which illustrates that the fitted value of the fifth minute in the recovery period is quite close to the measured result. This indicates the good reliability of the forecast and goodness-of-fit.

The relationship between the characteristic parameters of the proposed method and the WRA method: there is a significant positive correlation between the initial recovery degree a and the measured recovery angle of the fifth minute F_t(r = 0.99). The result showed that the initial recovery status can reflect the recovery degree after a few minutes in the recovery period to a certain extent. However, F_t is negatively associated with the recovery index b(r = –0.83). This reveals that the fabric with better crease recovery property tends to take less time to recover to a stable state. The correlation coefficient between F_t and the sub-item index of fabric crease recovery K is 0.89. In addition, the composite index of fabric crease recovery $\bar{K}$ shows a positive correlation with F_jw(r = 0.92). These indicate that the proposed $\bar{K}$ value is feasible to characterize the crease recovery property of fabrics.

Applicability of the power function evaluation method: the results of $\bar{K}$ and F_jw of samples 2#–5# indicate that the higher the resin content in the finishing process, the better the crease recovery property. The use of softener increases the crease recovery property of 100% cotton fabrics, when comparing the results of Samples 1# and 2#. Samples 6#–10# have the same features as Samples 1#–5#. From the results of Samples 1#–10#, it is demonstrated that the proposed method can differentiate durable-press finished fabrics with different crease recovery performances. From the results of all the samples, it is proved that this method is applicable for fabrics made of a variety of materials.

The advantages of the power function evaluation method: the new evaluation index $\bar{K}$ is more effective in assessing the crease recovery property of fabrics, as it takes full account of the creased fabric recovery deformation in the entire process. For example, the F_jw values of Samples 1# and 6# are 149.0° and 148.5°, respectively, which are close to each other. It is difficult to estimate the crease recovery properties of the two fabrics according to the WRA method. The composite indexes of fabric crease recovery $\bar{K}$ are 689.3 and 805.4, respectively. This reveals that with the proposed method it is easy to establish that the crease recovery property of Sample 6# is better than that of Sample 1#. Similarly, the values of F_jw of Samples 5# and 10# are 276.6° and 273.2°, respectively. The values of $\bar{K}$ are 2811.4 and 3019.0, respectively. It is obvious that the crease recovery performance of Sample 10# is better than that of Sample 5#.

Conclusions

This paper investigated a comprehensive evaluation method for the fabric crease recovery property by fitting the power function equation with the data of recovery angle change with time. The evaluating indicator, the composite index of fabric crease recovery, was obtained from the coefficients of the power function equations of four different ways of folding. The experimental results demonstrate that the recovery angles at different moments in the recovery period are fitted well by a power function equation. As can be seen from the results of fabrics treating with different finishing baths, the proposed method can differentiate durable-press finished fabrics with different crease recovery properties. The result of the fabrics made of a variety of materials proves that this method has good adaptability. In addition, compared with the recovery angle of the WRA method, our approach is more effective to characterize the crease recovery property, while the WRA method can only give similar angle results. Thus, it is demonstrated that it is a feasible method for the evaluation of the fabric crease recovery property. Alternatively, if the change trends of the crease recovery angle do not accord with the power function, the proposed evaluation should not be applicable to this type of fabric.

Footnotes

Acknowledgements

The authors wish to acknowledge Ken Greeson at Cotton Incorporated for providing the test fabric samples and the information about the fabric finish.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Key R&D Program of China (No. 2017YFB0309200), the National Natural Science Foundation of China (No. 61802152), the Natural Science Foundation of Jiangsu Province (No. BK20180602), the China Postdoctoral Science Foundation Funded Project (No. 2018M640453), the Jiangsu Province Postdoctoral Science Foundation (No. 2018K037B) and the Fundamental Research Funds for the Central Universities (No. JUSRP11805).

ORCID iD

Lei Wang

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