具体实施方式

应当理解，此处所描述的具体实施例仅仅用以解释本发明，并不用于限定本发明。

下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本发明的一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。

需要说明，本发明实施例中所有方向性指示(诸如上、下、左、右、前、后……)仅用于解释在某一特定姿态(如附图所示)下各部件之间的相对位置关系、运动情况等，如果该特定姿态发生改变时，则该方向性指示也相应地随之改变。

在本发明中，除非另有明确的规定和限定，术语“连接”、“固定”等应做广义理解，例如，“固定”可以是固定连接，也可以是可拆卸连接，或成一体；可以是机械连接，也可以是电连接；可以是直接相连，也可以通过中间媒介间接相连，可以是两个元件内部的连通或两个元件的相互作用关系，除非另有明确的限定。对于本领域的普通技术人员而言，可以根据具体情况理解上述术语在本发明中的具体含义。

另外，在本发明中如涉及“第一”、“第二”等的描述仅用于描述目的，而不能理解为指示或暗示其相对重要性或者隐含指明所指示的技术特征的数量。由此，限定有“第一”、“第二”的特征可以明示或者隐含地包括至少一个该特征。另外，各个实施例之间的技术方案可以相互结合，但是必须是以本领域普通技术人员能够实现为基础，当技术方案的结合出现相互矛盾或无法实现时应当认为这种技术方案的结合不存在，也不在本发明要求的保护范围之内。

如图1所示，图1是本发明实施例方案涉及的micro-LED的坏点检测设备硬件运行环境的设备结构示意图。

如图1所示，在micro-LED的坏点检测设备的硬件运行环境中，该micro-LED的坏点检测设备可以包括：处理器1001，例如CPU，网络接口1004，用户接口1003，存储器1005，通信总线1002。其中，通信总线1002用于实现这些组件之间的连接通信。用户接口1003可以包括显示屏（Display）、输入单元比如键盘（Keyboard），可选用户接口1003还可以包括标准的有线接口、无线接口。网络接口1004可选的可以包括标准的有线接口、无线接口（如WI-FI接口）。存储器1005可以是高速RAM存储器，也可以是稳定的存储器（non-volatile memory），例如磁盘存储器。存储器1005可选的还可以是独立于前述处理器1001的存储装置。

本领域技术人员可以理解，图1中示出的micro-LED的坏点检测设备结构并不构成对micro-LED的坏点检测设备的限定，可以包括比图示更多或更少的部件，或者组合某些部件，或者不同的部件布置。

如图1所示，作为一种计算机存储介质的存储器1005中可以包括操作系统、网络通信模块、用户接口模块以及micro-LED的坏点检测程序。

在图1所示的设备中，网络接口1004主要用于连接后台服务器，与后台服务器进行数据通信；用户接口1003主要用于连接客户端（用户端），与客户端进行数据通信；而处理器1001可以用于调用存储器1005中存储的micro-LED的坏点检测程序，并执行以下操作：

对晶圆上的micro-LED进行自动光学检测，得到自动光学检测结果，并对所述晶圆上的micro-LED进行光致发光检测，得到光致发光检测结果；

根据所述自动光学检测结果和所述光致发光检测结果确定疑似点集合、好点集合和第一坏点集合；

对所述疑似点集合和所述好点集合中的各个micro-LED进行电致发光检测，得到第二坏点集合；

将所述第一坏点集合和所述第二坏点集合的并集作为坏点检测结果。

基于上述硬件结构，提出本发明micro-LED的坏点检测方法各个实施例的整体构思。

现如今，micro-LED检测可分为无接触检测和接触检测。其中，无接触检测速度快，但检测精度低；接触检测精度高，但检测速度慢。一方面，虽然无接触检测能够满足速度上的需求，但由于精度较低，可能导致漏检或误检，从而影响了micro-LED的坏点检测质量。另一方面，接触检测虽然精度高，但检测速度慢，从而限制了其在高速生产线上的应用。

因此，如何提高micro-LED坏点检测的效率，是本领域技术人员尚待解决的技术问题。

为解决上述问题，本发明提出一种micro-LED的坏点检测方法。

基于上述本发明micro-LED的坏点检测方法各个实施例的整体构思，提出本发明micro-LED的坏点检测方法的各个实施例。

需要说明的是，本发明micro-LED的坏点检测方法的执行主体为micro-LED的坏点检测设备，该设备可以是电脑、服务器等终端设备。为便于说明，在以下实施例中，均省略执行主体进行阐述。

请参照图2，图2为本发明micro-LED的坏点检测方法第一实施例的流程示意图。需要说明的是，虽然在流程图中示出了逻辑顺序，但是在某些情况下，当然可以以不同于此处的顺序执行本发明micro-LED的坏点检测方法的各个步骤。

在本实施例中，所述micro-LED的坏点检测方法包括：

步骤S10，对晶圆上的micro-LED进行自动光学检测，得到自动光学检测结果，并对所述晶圆上的micro-LED进行光致发光检测，得到光致发光检测结果；

需要说明的是，晶圆上的micro-LED指的是晶圆上的发光点，自动光学检测指的是AOI检测，光致发光检测指的是PL检测。

在本实施例中，在对晶圆上的micro-LED进行自动光学检测时，可以通过图像传感器采集micro-LED的发光图像，进而通过机器学习、大数据分析等方式对发光图像进行处理，从而可以得到自动光学检测结果；在对晶圆上的micro-LED进行光致发光检测时，可以通过光谱仪、光度计、色度计获取发光信息，从而可以基于发光信息中的发光强度、色度以及亮度等信息，得到光致发光结果。

需要说明的是，本发明对自动光学检测和光致发光检测的实现方式不作限定。

步骤S20，根据所述自动光学检测结果和所述光致发光检测结果确定疑似点集合、好点集合和第一坏点集合；

需要说明的是，疑似点集合指的是疑似点所组成的集合，疑似点指的是疑似不发光的发光点。好点指的是可以正常发光的发光点，好点集合指的是正常发光的发光点所组成的集合。坏点指的是不可以发光的发光点，坏点集合指的是不可以发光的发光点所组成的集合。

在本实施例中，自动光学检测结果包括自动光学检测出的疑似点、好点和坏点，而光致发光检测结果也包括光致发光检测出的疑似点、好点和坏点。因此，可以对自动光学检测出的好点以及光致发光检测出的好点进行整理，得到好点集合，还可以对自动光学检测出的疑似点以及光致发光检测出的疑似点进行整理，得到疑似点集合，还可以对自动光学检测出的坏点以及光致发光检测出的坏点进行整理，得到第一坏点集合。

作为一种示例，可以将自动光学检测出的好点以及光致发光检测出的好点的并集，作为好点集合。

可选地，在一种可行的实施例中，上述步骤S20，还包括：

步骤S201，基于所述自动光学检测结果中的好点与所述光致发光检测结果中的好点的交集，得到好点集合；

步骤S202，基于所述自动光学检测结果中的坏点与所述光致发光检测结果中的坏点的并集，得到第一坏点集合；

步骤S203，将所述晶圆上不属于所述好点集合，且，不属于所述第一坏点集合的点作为疑似点，得到疑似点集合。

作为一种示例，为提高坏点检测的精度，还可以将自动光学检测结果中的好点与光致发光检测结果中的好点的交集，作为好点集合，可以将自动光学检测结果中的坏点与光致发光检测结果中的坏点的并集，作为第一坏点集合。然后将晶圆上既不属于好点集合也不属于第一坏点集合的点作为疑似点，然后对多个疑似点进行汇总，得到疑似点集合。

步骤S30，对所述疑似点集合和所述好点集合中的各个micro-LED进行电致发光检测，得到第二坏点集合；

在本实施例中，在得到疑似点集合和好点集合后，还可以对疑似点集合和好点集合中的各个micro-LED进行电致发光检测，从而得到第二坏点集合。

作为一种示例，发光点1为疑似点集合中的一个发光点，在对发光点1进行电致发光检测时，若检测到发光点1不可以发光，则发光点1为坏点。在将疑似点集合和好点集合中的发光点检测完毕后，能够将所有的坏点汇总为第二坏点集合。

步骤S40，将所述第一坏点集合和所述第二坏点集合的并集作为坏点检测结果。

在本实施例中，在得到第一坏点集合和第二坏点集合后，可以将第一坏点集合和第二坏点集合的并集作为坏点检测结果。

在本实施例中，通过对晶圆上的micro-LED进行自动光学检测，得到自动光学检测结果，并对所述晶圆上的micro-LED进行光致发光检测，得到光致发光检测结果，能够通过自动光学检测和光致发光检测对晶圆上的micro-LED进行快速检测；然后根据所述自动光学检测结果和所述光致发光检测结果确定疑似点集合、好点集合和第一坏点集合，能够根据快速检测的结果初步筛选出坏点；然后对所述疑似点集合和所述好点集合中的各个micro-LED进行电致发光检测，得到第二坏点集合，能够针对疑似点和好点进一步检测，从而能够在减少检测时间的基础上，准确的检测出坏点；然后将所述第一坏点集合和所述第二坏点集合的并集作为坏点检测结果，能够得到晶圆上的坏点集合。

本发明通过快速检测结果筛选出第一坏点集合，能够在较短时间内确定出部分坏点，然后对好点集合和疑似点集合进行电致发光检测，不仅能够减少电致发光检测的整体耗时，还能够兼顾micro-LED检测的精度，从而实现了兼顾坏点检测速度和坏点检测精度的效果，从而达到了提高micro-LED坏点检测效率的目的。

进一步地，基于上述本发明micro-LED的坏点检测方法的第一实施例，提出本发明micro-LED的坏点检测方法的第二实施例。

在本实施例中，在上述步骤S20之后，所述方法还包括：

步骤S100，随机抽取所述好点集合中的好点，得到随机好点集合；

需要说明的是，随机好点集合指的是抽取出的好点所组成的集合。

在本实施例中，在得到好点集合后，还可以随机抽取好点集合中的部分好点，以便于对好点进行验证。即，通过电致发光检测对抽取出的好点进行二次检测，以判断自动光学检测和光致发光检测的准确性。

基于此，上述步骤S30,还包括：

步骤S301，对所述疑似点集合和所述随机好点集合中的各个micro-LED进行电致发光检测，得到第二坏点集合。

在一种可行的实施例中，还可以对疑似点集合和随机好点集合中的各个micro-LED进行电致发光检测，从而得到第二坏点集合。

在本实施例中，本发明通过抽取部分好点进行电致发光检测的方式，能够进一步减少电致发光检测时待检测的发光点数量，从而能够进一步减少坏点检测的整体所需时长。

可选地，在一种可行的实施例中，上述步骤S301,还包括：

步骤S3011，获取所述疑似点集合和所述随机好点集合中各个micro-LED各自对应的坐标，并基于各所述坐标确定最短路径；

步骤S3012,按照所述最短路径对所述疑似点集合和所述随机好点集合中各个micro-LED进行电致发光检测，得到第二坏点集合。

需要说明的是，在对晶圆上的micro-LED进行自动光学检测以及光致发光检测时，需要确定晶圆上的各个micro-LED的坐标。例如，能够将晶圆左上角的micro-LED的坐标设置为（1,1），然后按照矩阵编号方式对其他micro-LED的坐标进行编号。

在本实施例中，还可以获取疑似点集合和随机好点集合中各个micro-LED的坐标，进而基于Dijkstra算法、Floyd算法等算法确定各个坐标之间的最短路径。然后按照最短路径，依次对最短路径上的各个疑似点和好点进行电致发光检测，从而可以进一步确定各个疑似点以及好点中的坏点。然后可以对电致发光检测检测出的坏点进行汇总，得到第二坏点集合。

请参照图3，图3为本发明micro-LED的坏点检测方法不进行最短路径规划时的电致发光路径图。图3中的星标表示micro-LED的位置，x表示横向，y表示纵向，线条表示测试路径。在不进行最短路径规划时，线条是互相交错的，从而需要较长的检测时间。

请参照图4，图4为本发明micro-LED的坏点检测方法一实施例的电致发光检测路径图。其中，在进行路径规划后，各个micro-LED之间的线条不再交错，从而，能够减少检测时间。

在本实施例中，本发明通过计算最短路径，进而根据最短路径对各个micro-LED进行电致发光检测的方式，能够减少电致发光检测中，在各个micro-LED中来回移动所需的时间，从而能够在较短时间内，完成对各个micro-LED的电致发光检测。

可选地，在一种可行的实施例中，在上述步骤S3011之后，所述方法还包括：

步骤S3013，基于预设的轨迹规划原则对所述最短路径进行优化；

需要说明的是，电致发光检测是点到点运动，点到点运动要求在保证定位精度的同时希望有效运动时间占比尽可能多，从而以提高检测效率。举例来说，请继续参照图3，图3中的线条长度是不一致的，为减少点与点之间路径的耗时，在线条较长时，还需要提高点至点之间移动的速度，从而减少移动所需的时间，从而提高有效运动时间的占比。而通过Dijkstra算法、Floyd算法等确定的最短路径只能保证整体耗时是较短的，并不能保证有效运动时间的占比较大。因此，还可以基于预先设定的轨迹规划原则对Dijkstra算法、Floyd算法得到的最短路径进行优化，以进一步提高电致发光检测时，发光点之间的移动速度。

作为一种示例，轨迹规划原则可以是：

其中，为参数速度，为参数加速度，为位移，Vmax和分别为运动系统能提供的最大速度和最大加速度，v(0)和v（）分别表示0时刻和时刻的速度，表示位移为时运动系统位置，Px表示x方向上的位置，Py表示y方向上的位置，Px（u）表示位移为u时，在x方向上的位置，Py（u）表示位移为u时，在y方向上的位置，为的微分，为的导数，为的导数。

基于此，上述步骤S3012，还包括：

步骤S3012-A,按照优化后的所述最短路径对所述疑似点集合和所述好点集合中各个micro-LED进行电致发光检测，得到第二坏点集合。

在本实施例中，本发明还通过预设的轨迹规划原则进一步提高了有效运动时间的占比，从而提高了坏点检测的效率。

进一步地，基于上述本发明micro-LED的坏点检测方法的第一实施例、第二实施例，提出本发明micro-LED的坏点检测方法的第三实施例。

在本实施例中，在上述步骤S30之后，所述方法还包括：

步骤S200，确定所述好点集合和所述第二坏点集合的交集，并确定所述交集中micro-LED的第一数量；

步骤S300,确定所述好点集合中micro-LED的第二数量，并将所述第一数量和所述第二数量的比值作为坏点检出率。

需要说明的是，坏点检出率指的是从好点中检测出坏点的概率。

在本实施例中，在得到第二坏点集合后，还可以确定好点集合和第二坏点集合的交集，进而可以确定交集中micro-LED的数量，即，得到第一数量。然后可以确定好点集合中发光点的数量，即，得到第二数量，进而能够基于第一数量和第二数量的比值，得到坏点检出率。从而，能够基于坏点检出率的数值确定自动光学检测和光致发光检测的可靠性。

可选地，在一种可行的实施例中，在上述步骤S10之前，所述方法还包括：

步骤S400,通过迭代学习算法控制预设的运动台进行栅格扫描运动，其中，所述运动台上固定有所述晶圆。

可以理解的是，在通过运动台进行扫描检测时，需要预先将待检测的晶圆固定在该运动台上，并利用运动台调整晶圆位置，使发光器件排列方向与运动台运动方向一致。

值得一提的是，扫描检测需要提供稳定的周期性高匀速运动。而单程扫描运动一般可分为启动阶段、调整阶段、匀速扫描阶段和减速阶段。为了消除周期扫描运动中的重复性扰动分量，如磁场周期波动、系统装配误差，复合力切换扰动等，可以采用分段迭代学习算法进行前馈补偿。将迭代学习率进行加权处理，增强期望的学习控制作用，从而消除不希望的学习控制作用。

在一种可行的实施例中，分段迭代学习控制的表达形式可以是：

；

其中，L表示总控制率，为各段学习的加权矩阵，为第m段的控制率，n为分段的段总数。

请参照图5，图5为本发明micro-LED的坏点检测方法一实施例所需的检测设备图。其中，1表示运动台，2表示XYZ机械臂，3表示色度计，4表示激光光路，5表示高速相机，6表示显示屏，7表示晶圆台。在通过图5给出的检测设备进行micro-LED的坏点检测的步骤可以是：

1）将晶圆放置在复合驱动运动台上表面，利用高速相机对晶圆上的发光器件进行成像，利用清晰度函数对成像系统进行自动调焦；当相机获得清晰图像后，利用运动台调整晶圆位置，使发光器件排列方向与运动台运动方向一致。

2）通过运动台将晶圆左上角发光器件运动到成像视场中，并将其编为（1,1）号发光器件，其他发光器件模仿矩阵编号方式依次进行编号。

3）启动色度计和高速相机，引入激发激光。

4）运动平台进行栅格扫描运动。

5）通过数据分析，对PL检测和AOI检测结果进行分析。

6）对部分好点和所有疑似点进行EL检测。将检测中的疑似点坐标整理出来，好点中则随机抽取部分点并记录坐标位置。将所有位置坐标通过优化方法寻找最优路径。基于最优路径进行EL检测。

7）对EL检测结果进行分析。

在本实施例中，本发明通过迭代学习，消除了周期扫描运动中磁场周期波动、系统装配误差、复合力切换扰动等因素对自动发光检测和光致发光检测的影响，从而能够提高自动发光检测和光致发光检测检测坏点的准确率。

此外，本发明还提出一种micro-LED的坏点检测系统。

请参照图6，所述micro-LED的坏点检测系统包括：

扫描检测模块10，用于对晶圆上的micro-LED进行自动光学检测，得到自动光学检测结果，并对所述晶圆上的micro-LED进行光致发光检测，得到光致发光检测结果；

发光点分类模块20，用于根据所述自动光学检测结果和所述光致发光检测结果确定疑似点集合、好点集合和第一坏点集合；

电致发光检测模块30，用于对所述疑似点集合和所述好点集合中的各个micro-LED进行电致发光检测，得到第二坏点集合；

坏点汇总模块40，用于将所述第一坏点集合和所述第二坏点集合的并集作为坏点检测结果。

可选地，发光点分类模块20还用于：

基于所述自动光学检测结果中的好点与所述光致发光检测结果中的好点的交集，得到好点集合；

基于所述自动光学检测结果中的坏点与所述光致发光检测结果中的坏点的并集，得到第一坏点集合；

将所述晶圆上不属于所述好点集合，且，不属于所述第一坏点集合的点作为疑似点，得到疑似点集合。

可选地，micro-LED的坏点检测系统还包括：

好点抽取模块，用于随机抽取所述好点集合中的好点，得到随机好点集合；

基于此，电致发光检测模块30，还用于：

对所述疑似点集合和所述随机好点集合中的各个micro-LED进行电致发光检测，得到第二坏点集合。

可选地，电致发光检测模块30，还用于：

获取所述疑似点集合和所述随机好点集合中各个micro-LED各自对应的坐标，并基于各所述坐标确定最短路径；

按照所述最短路径对所述疑似点集合和所述随机好点集合中各个micro-LED进行电致发光检测，得到第二坏点集合。

可选地，电致发光检测模块30，还用于：

基于预设的轨迹规划原则对所述最短路径进行优化；

基于此，电致发光检测模块30，还用于：

按照优化后的所述最短路径对所述疑似点集合和所述好点集合中各个micro-LED进行电致发光检测，得到第二坏点集合。

可选地，micro-LED的坏点检测系统还包括：

第一数量计算模块，用于确定所述好点集合和所述第二坏点集合的交集，并确定所述交集中micro-LED的第一数量；

准确率计算模块，用于确定所述好点集合中micro-LED的第二数量，并将所述第一数量和所述第二数量的比值作为坏点检出率。

可选地，micro-LED的坏点检测系统还包括：

迭代控制模块，用于通过迭代学习算法控制预设的运动台进行栅格扫描运动，其中，所述运动台上固定有所述晶圆。

其中，上述micro-LED的坏点检测系统中各个模块的功能实现与上述micro-LED的坏点检测方法实施例中各步骤相对应，其功能和实现过程在此处不再一一赘述。

此外，本发明还提出一种micro-LED的坏点检测设备，该micro-LED的坏点检测设备包括：存储器、处理器及存储在所述存储器上并可在所述处理器上运行的micro-LED的坏点检测程序，所述micro-LED的坏点检测程序被所述处理器执行时实现如上所述本发明micro-LED的坏点检测方法的步骤。

本发明micro-LED的坏点检测设备的具体实施例与上述micro-LED的坏点检测方法各实施例基本相同，在此不作赘述。

此外，本发明还提出一种存储介质，该存储介质上存储有micro-LED的坏点检测程序，该micro-LED的坏点检测程序被处理器执行时实现如上所述本发明micro-LED的坏点检测方法的步骤。

本发明存储介质的具体实施例与上述micro-LED的坏点检测方法各实施例基本相同，在此不作赘述。

需要说明的是，在本文中，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、物品或者装置不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、物品或者装置所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括该要素的过程、方法、物品或者装置中还存在另外的相同要素。

上述本申请实施例序号仅仅为了描述，不代表实施例的优劣。

通过以上的实施方式的描述，本领域的技术人员可以清楚地了解到上述实施例方法可借助软件加必需的通用硬件平台的方式来实现，当然也可以通过硬件，但很多情况下前者是更佳的实施方式。基于这样的理解，本申请的技术方案本质上或者说对现有技术做出贡献的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质（如ROM/RAM、磁碟、光盘）中，包括若干指令用以使得一台终端设备（可以是车载电脑，智能手机，计算机，或者服务器等）执行本申请各个实施例所述的方法。

以上仅为本申请的优选实施例，并非因此限制本申请的专利范围，凡是利用本申请说明书及附图内容所作的等效结构或等效流程变换，或直接或间接运用在其他相关的技术领域，均同理包括在本申请的专利保护范围内。

The specific embodiment

It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to qualify the invention.

The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only part of the embodiments of the present invention, not all embodiments. Based on the embodiments in the present invention, all other embodiments obtained by a person skilled in the art without making creative labor belong to the scope of protection of the present invention.

It should be noted that all directional indications (such as up, down, left, right, front, rear, ......) in the embodiment of the present invention It is only used to explain the relative position relationship between the parts and the movement of each part in a specific posture (as shown in the attached drawing), and if the specific attitude changes, the directional indication will change accordingly.

In the present invention, unless otherwise expressly specified or qualified, the terms "connected", "fixed", etc., shall be construed broadly, for example, "fixed" may be a fixed connection, a detachable connection, or a whole; It can be mechanically or electrically connected; It can be directly connected or indirectly connected by an intermediate medium, it may be an internal connection between two elements or an interaction between two elements, unless otherwise expressly specified. For a person of ordinary skill in the art, the specific meaning of the above terms in the present invention may be understood according to the specific circumstances.

In addition, descriptions such as "first", "second", etc., in the present invention are for descriptive purposes only and cannot be construed as indicating or implying their relative importance or implying the number of technical features indicated. Thus, defining the "first" and "second" features may explicitly or implicitly include at least one of those features. In addition, the technical solutions between the various embodiments may be combined with each other, but they must be based on those who are skilled in the art and can be realized, and when the combination of technical solutions is contradictory or impossible to realize, it shall be deemed that the combination of such technical solutions does not exist and is not within the scope of protection claimed by the present invention.

As shown in FIG. 1, FIG. 1 is a schematic diagram of the equipment structure of the hardware operating environment of the hardware operating environment of the micro-LED dead pixel detection equipment involved in the embodiment scheme of the present invention.

As shown in Figure 1, in the hardware operating environment of the micro-LED dead pixel detection device, the micro-LED dead pixel detection device may include: a processor 1001, such as a CPU, a network interface 1004, a user interface 1003, a memory 1005, and a communication bus 1002. wherein, the communication bus 1002 is used to realize the connection communication between these components. The user interface 1003 can include a display screen (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 can also include a standard wired interface and a wireless interface. NETWORK INTERFACE 1004 CAN OPTIONALLY INCLUDE STANDARD WIRED INTERFACES AND WIRELESS INTERFACES (SUCH AS WI-FI INTERFACES). Memory 1005 can be either high-speed RAM memory or non-volatile memory, such as disk memory. Memory 1005 may also be an optional storage device independent of the aforementioned processor 1001.

Those skilled in the art can understand that the structure of the micro-LED dead pixel detection equipment shown in Figure 1 does not constitute a limitation of the micro-LED dead pixel detection equipment, and may include more or fewer parts than illustrated, or combine certain parts, or arrange different parts.

As shown in Figure 1, memory 1005, which is a computer storage medium, may include an operating system, a network communication module, a user interface module, and a micro-LED dead pixel detection program.

In the device shown in Figure 1, the network interface 1004 is mainly used to connect to the background server and carry out data communication with the background server; The user interface 1003 is mainly used for connecting the client (user terminal) and carrying out data communication with the client; The processor 1001 can be used to invoke the dead pixel detection program of the micro-LED stored in memory 1005 and perform the following operations:

an automatic optical detection is carried out on the micro-LED on the wafer to obtain an automatic optical detection result, and a photoluminescence detection is carried out on the micro-LED on the wafer to obtain a photoluminescence detection result;

determining a set of suspected points, a set of good points and a set of first bad points according to the automatic optical detection result and the photoluminescence detection result;

electroluminescence detection is carried out on each micro-LED in the suspected point set and the good point set to obtain a second bad pixel set;

the union of the first set of dead pixels and the second set of dead pixels as the result of the detection of dead pixels.

Based on the above-mentioned hardware structure, the overall conception of each embodiment of the dead pixel detection method of micro-LED of the present invention is proposed.

Nowadays, micro-LED inspection can be divided into non-contact inspection and contact detection. Among them, the non-contact detection speed is fast, but the detection accuracy is low; The contact detection accuracy is high, but the detection speed is slow. On the one hand, although non-contact detection can meet the demand for speed, due to the low accuracy, it may lead to missed detection or false detection, which affects the quality of micro-LED dead pixel detection. On the other hand, contact detection, although highly accurate, is slow to detect, thus limiting its application on high-speed production lines.

Therefore, how to improve the efficiency of micro-LED dead pixel detection is a technical problem that has yet to be solved by those skilled in the art.

In order to solve the above problem, the invention proposes a dead pixel detection method of micro-LED.

Based on the overall conception of each embodiment of the dead pixel detection method of micro-LED of the present invention, each embodiment of the dead pixel detection method of micro-LED of the present invention is proposed.

It should be noted that the execution body of the dead pixel detection method of the present invention micro-LED is the bad pixel detection equipment of micro-LED, and the equipment can be a computer, a server and other terminal equipment. For ease of explanation, in the following embodiments, the executive body is omitted for elaboration.

Please refer to Figure 2, and Figure 2 is a schematic diagram of the flow of the first embodiment of the dead pixel detection method of micro-LED of the present invention. It should be noted that, although the logical order is shown in the flow diagram, in some cases, of course, the individual steps of the dead pixel detection method of the present invention micro-LED can be executed in a different order than here.

In this embodiment, the dead pixel detection method of described micro-LED comprises:

step S10, perform an automatic optical detection on the micro-LED on the wafer to obtain an automatic optical detection result, and perform a photoluminescence detection on the micro-LED on the wafer to obtain a photoluminescence detection result;

It should be noted that micro-LED on the wafer refers to the light-emitting point on the wafer, automatic optical inspection refers to AOI detection, and photoluminescence inspection refers to PL detection.

In this embodiment, when performing automatic optical detection of micro-LED on a wafer, the luminescence image of the micro-LED can be collected through an image sensor, and then the luminescence image is processed by machine learning, big data analysis, etc., so that an automatic optical detection result can be obtained; When photoluminescence detection is performed on micro-LEDs on wafers, luminescence information can be obtained through spectrometers, photometers, and colorimeters, so that photoluminescence results can be obtained based on luminous intensity, chromaticity, and brightness information in the luminescence information.

It should be noted that the present invention does not limit the realization mode of automatic optical detection and photoluminescence detection.

step S20, determining a set of suspected points, a set of good points and a set of first bad points according to the automatic optical detection result and the photoluminescence detection result;

It should be noted that the collection of suspicious points refers to the set composed of suspicious points, and the suspicious points refer to the luminous points that are suspected of not emitting light. A good spot is a collection of luminous points that can emit light normally, and a set of good dots is a collection of luminous dots that emit light normally. A bad pixel is a collection of luminous dots that cannot emit light, and a set of dead pixels is a collection of luminous dots that cannot emit light.

In the present embodiment, the automated optical detection result comprises a suspicious, good, and bad pixel detected by automated optics, and the photoluminescence detection result also comprises a suspicious, good, and bad pixel detected by photoluminescence. Therefore, the good points detected by automatic optics and the good points detected by photoluminescence can be sorted out to obtain a set of good points, and the suspicious points detected by automatic optics and the suspected points detected by photoluminescence can be sorted out to obtain a collection of suspected points, and the bad pixels detected by automatic optics and the bad points detected by photoluminescence can be sorted out to obtain the first set of bad pixels.

As an example, the union of good points detected by automated optics and good points detected by photoluminescence can be used as a good point set.

Optionally, in a feasible embodiment, the preceding step S20 further comprises:

step S201, obtaining a set of good points based on the intersection of the good points in the automatic optical detection result and the good points in the photoluminescence detection results;

step S202, obtaining a first set of dead pixels based on the union of the dead pixels in the automatic optical detection result and the dead pixels in the photoluminescence detection result;

step S203, a point on the wafer that does not belong to the set of good points and does not belong to the first set of bad points is taken as a suspicious point to obtain a set of suspicious points.

As an example, in order to improve the accuracy of dead pixel detection, the intersection of the good pixels in the AE detection results and the good pixels in the photoluminescence detection results can also be used as a set of good pixels, and the union of the bad pixels in the AE results and the bad pixels in the photoluminescence detection results can be used as the first bad pixel set. Then, the points on the wafer that belong to neither the good point set nor the first bad point set are taken as the suspicious points, and then multiple suspicious points are summarized to obtain the suspicious point set.

step S30, electroluminescence detection is carried out on each micro-LED in the suspected point set and the good point set to obtain a second bad pixel set;

In this embodiment, after obtaining a set of suspected points and a set of good points, an electroluminescence detection can also be performed on each micro-LED in the set of suspected points and a set of good points, so as to obtain a second set of bad points.

As an example, luminescent point 1 is a luminous point in the suspected set of points, and if luminescent point 1 is detected in electroluminescence detection, if it is detected that luminous point 1 cannot emit light, then luminescent point 1 is a bad dot. After the luminous dots in the collection of suspicious and good dots are detected, all the bad pixels can be aggregated into a second set of bad pixels.

step S40, the union of the first set of bad pixels and the second set of bad pixels is taken as the result of the detection of bad pixels.

In this embodiment, after obtaining a first set of dead pixels and a set of second bad pixels, the union of the first set of dead pixels and the set of second dead pixels can be used as the result of bad pixel detection.

In this embodiment, an automatic optical detection result is obtained by performing an automatic optical detection on a micro-LED on a wafer, and a photoluminescence detection result is performed on a micro-LED on the wafer to obtain a photoluminescence detection result, and the micro-LED on the wafer can be rapidly detected by automatic optical detection and photoluminescence detection; then determine a set of suspected points, a set of good points and a set of first bad pixels according to the results of the automatic optical detection and the photoluminescence detection results, and preliminarily screen out the bad pixels according to the results of the rapid detection; then electroluminescence detection is carried out on each micro-LED in the suspect point set and the good point set to obtain a second bad pixel set, which can be further detected for the suspected point and the good point, so that the bad pixel can be accurately detected on the basis of reducing the detection time; then the union of the first bad pixel set and the second bad pixel set is taken as the bad pixel detection result to obtain the dead pixel set on the wafer.

The present invention screens out the first bad pixel set through a rapid detection result, can determine part of the bad pixel in a relatively short time, and then carries out electroluminescence detection on the good spot set and the suspected point set, not only can reduce the overall time consumption of electroluminescence detection, but also can take into account the accuracy of micro-LED detection, thereby realizing the effect of taking into account the bad pixel detection speed and the bad pixel detection accuracy, thereby achieving the purpose of improving the efficiency of micro-LED bad pixel detection.

Further, based on the first embodiment of the dead pixel detection method of micro-LED of the present invention, a second embodiment of the dead pixel detection method of micro-LED of the present invention is proposed.

In this embodiment, after the above step S20, the method further comprises:

step S100, randomly select the good points in the set of good points to obtain a set of random good points;

It should be noted that the random set of good points refers to the set of good points that are extracted.

In the present embodiment, after obtaining a set of good points, a part of the good points in the set of good points can also be randomly selected so as to facilitate the verification of the good points. That is, the extracted good points are detected twice by electroluminescence detection to judge the accuracy of automatic optical detection and photoluminescence detection.

Based on this, the above step S30 further comprises:

step S301, each micro-LED in the suspected point set and the random good point set are electroluminescently detected to obtain a second bad point set.

In a feasible embodiment, electroluminescence detection can also be performed on each micro-LED in the suspected point set and the random good point set, so as to obtain a second bad pixel set.

In the present embodiment, the invention can further reduce the number of luminescent spots to be detected during electroluminescence detection by extracting some good points for electroluminescence detection, so that the overall required time for bad pixel detection can be further reduced.

Optionally, in a feasible embodiment, the preceding step S301 further comprises:

step S3011, obtaining the coordinates corresponding to each micro-LED in the suspected point set and the random good point set, and determining the shortest path based on each coordinate;

step S3012, electroluminescence detection is carried out on each micro-LED in the suspected point set and the random good point set according to the shortest path to obtain a second bad pixel set.

It should be noted that the coordinates of each micro-LED on the wafer need to be determined when performing automatic optical inspection of micro-LEDs on wafers as well as photoluminescence inspection. For example, it is possible to set the coordinates of the micro-LEDs in the upper left corner of the wafer to (1,1) and then number the coordinates of the other micro-LEDs according to the matrix numbering scheme.

In the present embodiment, the coordinates of each micro-LED in the suspected point set and the random good point set can also be obtained, and then the shortest path between the coordinates is determined based on algorithms such as Dijkstra algorithm and Floyd algorithm. Then, according to the shortest path, electroluminescence detection is carried out on each suspected point and good point on the shortest path in turn, so that each suspected point and the bad point in the good point can be further determined. The dead pixels detected by electroluminescence detection can then be summarized to obtain a second set of dead pixels.

Please refer to Fig. 3, Fig. 3 is the electroluminescence path diagram when the dead pixel detection method of micro-LED of the present invention does not carry out the shortest path planning. The star in Figure 3 indicates the position of the micro-LED, the x is horizontal, the y is vertical, and the line indicates the test path. When the shortest path is not planned, the lines are interleaved, resulting in a long inspection time.

Please refer to Figure 4, and Figure 4 is the electroluminescence detection path diagram of the dead spot detection method of micro-LED of the present invention for example. In particular, after path planning, the lines between the individual micro-LEDs are no longer interlaced, which reduces the detection time.

In this embodiment, the invention can reduce the time required to move back and forth in each micro-LED in the electroluminescence detection by calculating the shortest path and then carrying out electroluminescence detection on each micro-LED according to the shortest path, so that the electroluminescence detection of each micro-LED can be completed in a relatively short time.

Optionally, in a feasible embodiment, after the preceding step S3011, the method further comprises:

step S3013, optimizing the shortest path based on the preset trajectory planning principle;

It should be noted that electroluminescence detection is a point-to-point motion, and point-to-point motion requires that the effective motion time account for as much as possible while ensuring the positioning accuracy, so as to improve the detection efficiency. For example, if you continue to refer to Figure 3, the length of the lines in Figure 3 is inconsistent, in order to reduce the time spent on the path between points, when the lines are long, it is also necessary to increase the speed of moving between points, so as to reduce the time required for movement, and thus increase the proportion of effective movement time. However, the shortest path determined by Dijkstra algorithm and Floyd algorithm can only ensure that the overall time consumption is short, but cannot guarantee that the effective movement time accounts for a large proportion. Therefore, the shortest path obtained by Dijkstra algorithm and Floyd algorithm can be optimized based on the preset trajectory planning principle to further improve the movement speed between luminescence points during electroluminescence detection.

As an example, trajectory planning principles can be:

where is the parameter velocity, is the parameter acceleration, is the displacement, Vmax and are the maximum speed and maximum acceleration that the motion system can provide, v(0) and v() represent the velocity at 0 time and time respectively, and represent the position of the motion system when the displacement is time, Px represents the position in the x direction, Py represents the position in the y direction, and Px(u) represents the displacement when u, The position in the x-direction, Py(u) denotes the position in the y-direction when the displacement is u, is the differential, is the derivative, is the derivative, is the derivative.

Based on this, the above step S3012 further comprises:

step S3012-A, each micro-LED in the suspected point set and the good point set is electroluminescently detected according to the shortest path after optimization, and a second bad point set is obtained.

In the present embodiment, the invention further further increases the proportion of effective motion time through the preset trajectory planning principle, thereby improving the efficiency of dead pixel detection.

Further, based on the first embodiment and the second embodiment of the dead pixel detection method of micro-LED of the present invention, a third embodiment of the dead pixel detection method of micro-LED of the present invention is proposed.

In this embodiment, after the preceding step S30, the method further comprises:

step S200, determining the intersection of the set of good points and the set of second bad points, and determining the first quantity of micro-LEDs in the intersection;

step S300, determining the second quantity of micro-LEDs in the set of good spots, and taking the ratio of the first quantity and the second quantity as the bad pixel detection rate.

It should be noted that the bad pixel detection rate refers to the probability of detecting a bad pixel from a good spot.

In this embodiment, after obtaining a second set of bad points, the intersection of the set of good points and the set of second bad points can also be determined, and then the number of micro-LEDs in the intersection can be determined, that is, the first quantity is obtained. The number of luminous dots in the set of good dots can then be determined, i.e., the second number can be obtained, and the bad pixel detection rate can be obtained based on the ratio of the first and second quantities. As a result, the reliability of automated optical inspection and photoluminescence detection can be determined based on the numerical value of the dead pixel detection rate.

Optionally, in a feasible embodiment, the method further comprises, prior to the preceding step S10:

step S400, controlling a preset motion table to carry out a grid scanning motion through an iterative learning algorithm, wherein the motion table is fixed with the wafer.

It is understandable that when scanning and inspecting through the motion table, the wafer to be detected needs to be fixed on the motion table in advance, and the position of the wafer is adjusted by using the motion table to make the alignment direction of the light-emitting device consistent with the motion direction of the motion table.

It is worth mentioning that scanning detection needs to provide stable periodic high uniform motion. The single-pass scanning motion can generally be divided into the start-up stage, the adjustment stage, the constant scanning stage and the deceleration stage. In order to eliminate the repetitive disturbance components in the periodic scanning motion, such as the periodic fluctuation of the magnetic field, the system assembly error, the composite force switching disturbance, etc., the piecewise iterative learning algorithm can be used for feedforward compensation. The iterative learning rate is weighted to enhance the desired learning control, so as to eliminate the undesirable learning control.

In a feasible embodiment, the expression of piecewise iterative learning control can be:

；

where L is the total control rate, which is the weighted matrix of each segment learning, which is the control rate of the mth segment, and n is the total number of segments of the segment.

Please refer to Figure 5, and Figure 5 is the detection equipment diagram required for the bad pixel detection method of micro-LED of the present invention for an embodiment. Among them, 1 represents the motion table, 2 represents the XYZ robotic arm, 3 represents the colorimeter, 4 represents the laser optical path, 5 represents the high-speed camera, 6 represents the display screen, and 7 represents the wafer stage. The steps for the dead pixel detection of micro-LEDs by the inspection equipment shown in Figure 5 can be:

1) The wafer is placed on the upper surface of the composite drive motion stage, the light-emitting device on the wafer is imaged with a high-speed camera, and the imaging system is automatically focused by the clarity function; When the camera obtains a clear image, the wafer position is adjusted by using the motion table to make the alignment direction of the light-emitting device consistent with the motion direction of the motion table.

2) The light-emitting devices in the upper left corner of the wafer are moved into the imaging field of view through the motion table, and they are numbered as (1, 1) light-emitting devices, and the other light-emitting devices are numbered sequentially in imitation of the matrix numbering method.

3) Start the colorimeter and high-speed camera and introduce the excitation laser.

4) The motion platform performs raster scanning movements.

5) Through data analysis, the results of PL detection and AOI detection were analyzed.

6) EL detection was performed on some good points and all suspected points. The coordinates of the suspected points in the detection are sorted out, and some points are randomly selected and the coordinate positions are recorded in the good points. All location coordinates are optimized to find the optimal path. EL detection is performed based on the optimal path.

7) Analyze the EL test results.

In the present embodiment, the invention eliminates the influence of factors such as magnetic field periodic fluctuations, system assembly errors, and composite force switching disturbances on automatic luminescence detection and photoluminescence detection through iterative learning, so that the accuracy of automatic luminescence detection and photoluminescence detection of bad pixels can be improved.

In addition, the invention also proposes a dead pixel detection system of micro-LED.

Referring to Figure 6, the dead pixel detection system of the micro-LED comprises:

the scanning detection module 10 is used for carrying out automatic optical detection on the micro-LED on the wafer to obtain the automatic optical detection result, and performing photoluminescence detection on the micro-LED on the wafer to obtain the photoluminescence detection result;

the luminescent spot classification module 20 is used for determining a collection of suspected points, a set of good points and a set of first bad points according to the automatic optical detection result and the photoluminescence detection result;

the electroluminescence detection module 30 is used for electroluminescence detection of each micro-LED in the suspected point set and the good point set, and the second bad point set is obtained;

the bad pixel aggregation module 40 is used for taking the union of the first bad pixel set and the second bad pixel set as the bad pixel detection result.

Optionally, the luminous spot classification module 20 is also used for:

based on the intersection of the good points in the automatic optical detection result and the good points in the photoluminescence detection result, a set of good points is obtained;

the first set of dead pixels is obtained based on the union of the dead pixels in the automatic optical detection result and the dead pixels in the photoluminescence detection result;

a set of suspicious points is obtained by taking a point on the wafer that does not belong to the set of good points and does not belong to the first set of bad points as a suspicious point.

Optionally, the micro-LED dead pixel detection system also includes:

the good point extraction module is used for randomly selecting the good points in the set of good points to obtain a random set of good points;

Based on this, the electroluminescence detection module 30 is also used for:

electroluminescence detection is carried out on each micro-LED in the suspected point set and the random good point set to obtain a second bad pixel set.

Optionally, the electroluminescence detection module 30 is also used for:

obtaining the coordinates corresponding to each micro-LED in the suspected point set and the random good point set, and determining the shortest path based on each coordinate;

electroluminescence detection is carried out on each micro-LED in the suspected point set and the random good point set according to the shortest path to obtain a second bad pixel set.

Optionally, the electroluminescence detection module 30 is also used for:

optimizing the shortest path based on the preset trajectory planning principle;

Based on this, the electroluminescence detection module 30 is also used for:

electroluminescence detection is carried out on each micro-LED in the suspected point set and the good point set according to the shortest path after optimization, and a second bad pixel set is obtained.

Optionally, the micro-LED dead pixel detection system also includes:

the first quantity calculation module is used for determining the intersection of the set of good points and the set of second bad points, and determining the first quantity of micro-LEDs in the intersection;

the accuracy calculation module is used for determining the second quantity of micro-LEDs in the set of good pixels, and taking the ratio of the first quantity and the second quantity as the bad pixel detection rate.

Optionally, the micro-LED dead pixel detection system also includes:

the iterative control module is used for controlling the preset motion table to carry out grid scanning motion through an iterative learning algorithm, wherein the motion table is fixed with the wafer.

Wherein, the functional implementation of each module in the dead pixel detection system of the micro-LED corresponds to each step in the embodiment of the dead pixel detection method of the micro-LED, and its functions and implementation processes are not repeated here.

In addition, the present invention also provides a dead pixel detection device of micro-LED, the dead pixel detection device of micro-LED comprises: a memory, a processor and a dead pixel detection program of micro-LED stored on described memory and can run on described processor, and the dead pixel detection program of described micro-LED is executed by described processor to realize the steps of the dead pixel detection method of micro-LED as described above.

The specific embodiment of the dead pixel detection apparatus of the present invention is basically the same as the embodiment of the dead pixel detection method of the micro-LED described above, and is not repeated herein.

In addition, the invention also provides a storage medium, on which a dead pixel detection program of micro-LED is stored, and the dead pixel detection program of micro-LED is executed by a processor to realize a step for the dead pixel detection method of micro-LED as described above.

The specific embodiments of the storage medium of the present invention are basically the same as the embodiments of the dead pixel detection method of the micro-LED described above, and are not repeated herein.

It should be noted that, for the purposes of this document, the term "including", "including" or any other variation thereof is intended to cover non-exclusive inclusions, so that a process, process, article or apparatus that includes a series of elements includes not only those elements, but also other elements that are not expressly listed, or that are inherent to such a process, method, article or apparatus. In the absence of further restrictions, an element defined by the phrase "including a ......" does not preclude the existence of other identical elements in the process, method, article or apparatus that includes that element.

The above embodiment numbers of the present application are only for description and do not represent the advantages and disadvantages of the embodiments.

Through the description of the above embodiments, those skilled in the art can clearly understand that the above embodiment method can be realized by means of software plus the necessary general hardware platform, and of course it can also be achieved by hardware, but in many cases the former is a better embodiment. Based on this understanding, the essence of the technical solution of the present application or the part that contributes to the prior art may be embodied in the form of a software product that is stored in a storage medium (such as ROM/RAM, a disk disk, an optical disc) and comprises a plurality of instructions to enable a terminal device (which may be a vehicle-mounted computer, a smart phone, a computer, or a server, etc.) to execute the methods described in each embodiment of the present application.

The above is only a preferred embodiment of the present application, and does not limit the scope of the patent of the present application, and all equivalent structural or equivalent process transformations made by using the contents of the description and drawings of the present application, or directly or indirectly used in other related technical fields, are similarly included in the scope of patent protection of the present application.