diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/events.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/events.py
index aa41a1cc44..cb55b7a779 100644
--- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/events.py
+++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/events.py
@@ -573,9 +573,6 @@ def apply_external_force_torque_duration(
     asset_cfg: SceneEntityCfg = SceneEntityCfg("robot"),
 ):
     """
-    force/torque维持一段时间 然后取消
-    和原有的apply_external_force_torque在reset以后整个episode一直保持不同
-
     apply the force/torque for a time, then cancel it
     changes the above function apply_external_force_torque that apply the force/torque in the whole episode
     """
@@ -595,9 +592,8 @@ def apply_external_force_torque_duration(
         torques = math_utils.sample_uniform(*torque_range, size, asset.device).clone()
     else:
         size = (len(env_ids), num_bodies, 3)
-        forces = torch.zeros(size, asset.device)
-        torques = torch.zeros(size, asset.device)
-
+        forces = torch.zeros(size=size, device=asset.device)
+        torques = torch.zeros(size=size, device=asset.device)
 
     # set the forces and torques into the buffers
     # note: these are only applied when you call: `asset.write_data_to_sim()`
diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/event_manager.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/event_manager.py
index c072b589db..ed49189d6a 100644
--- a/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/event_manager.py
+++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/event_manager.py
@@ -222,7 +222,7 @@ def apply(
                     if time_left < 1e-6:
                         lower, upper = term_cfg.interval_range_s
                         sampled_interval = torch.rand(1) * (upper - lower) + lower
-                        self._interval_term_time_left[index][:] = sampled_interval
+                        self._duration_term_interval_time_left[index][:] = sampled_interval
 
                         # call the event term (with None for env_ids)
                         term_cfg.params["open"]=True
@@ -244,7 +244,7 @@ def apply(
                     if len(valid_env_ids) > 0:
                         lower, upper = term_cfg.interval_range_s
                         sampled_time = torch.rand(len(valid_env_ids), device=self.device) * (upper - lower) + lower
-                        self._interval_term_time_left[index][valid_env_ids] = sampled_time
+                        self._duration_term_interval_time_left[index][valid_env_ids] = sampled_time
                         
                         # call the event term
                         term_cfg.params["open"]=True
@@ -255,8 +255,8 @@ def apply(
                     valid_env_ids_duration = (duration_left < 1e-6).nonzero().flatten()
                     if len(valid_env_ids_duration) > 0:
                         term_cfg.params["open"]=False
-                        term_cfg.func(self._env, valid_env_ids, **term_cfg.params)
-                        self._duration_term_started[index][valid_env_ids] = False
+                        term_cfg.func(self._env, valid_env_ids_duration, **term_cfg.params)
+                        self._duration_term_started[index][valid_env_ids_duration] = False
 
                         lower, upper = term_cfg.duration_range_s
                         duration_left = torch.rand(len(valid_env_ids_duration), device=self.device) * (upper - lower) + lower