fix: optimize diagnosis output format and fix inconsistency between fault_status and fault_type

1. 输出格式优化:
   - faults中移除冗余的bbox和confidence字段
   - summary中fault_count改名为detection_count

2. fault_status与fault_type逻辑统一:
   - normal状态时fault_type为'none'，不再使用'suspect'
   - abnormal状态时才进行故障类型分类(hotspot/local_overheating/overheat)

3. 修复usage_example.py图像通道问题:
   - YOLO检测使用彩色图，温度提取时再转灰度图

src/diagnose.py

@@ -67,13 +67,13 @@ class FaultDiagnoser:
 
                 fault_status = self._check_fault(temp_features)
                 temp_features['fault_status'] = fault_status
-                temp_features['fault_type'] = self._classify_fault(temp_features)
+                # abnormal 时才进行故障分类，normal 时类型为 none
+                if fault_status == 'abnormal':
+                    temp_features['fault_type'] = self._classify_fault(temp_features)
+                else:
+                    temp_features['fault_type'] = 'none'
 
-                result['faults'].append({
-                    'bbox': bbox,
-                    'confidence': det['confidence'],
-                    **temp_features
-                })
+                result['faults'].append(temp_features)
         else:
             raise ValueError("Detector not initialized with model")
 
@@ -137,14 +137,14 @@ class FaultDiagnoser:
             摘要信息
         """
         if not faults:
-            return {'status': 'no_detection', 'fault_count': 0}
+            return {'status': 'no_detection', 'detection_count': 0}
 
         abnormal_count = sum(1 for f in faults if f.get('fault_status') == 'abnormal')
         fault_types = [f.get('fault_type', 'unknown') for f in faults]
 
         return {
             'status': 'fault_detected' if abnormal_count > 0 else 'normal',
-            'fault_count': len(faults),
+            'detection_count': len(faults),
             'abnormal_count': abnormal_count,
             'fault_types': list(set(fault_types))
         }